Reliable In Silico Ranking of Engineered Therapeutic TCR Binding Affinities with MMPB/GBSAClick to copy article linkArticle link copied!
- Rory M. Crean*Rory M. Crean*Email: [email protected]Department of Biology and Biochemistry and Doctoral Training Centre in Sustainable Chemical Technologies, University of Bath, Bath BA2 7AY, U.K.More by Rory M. Crean
- Christopher R. PudneyChristopher R. PudneyDepartment of Biology and Biochemistry and Centre for Therapeutic Innovation, University of Bath, Bath BA2 7AY, U.K.More by Christopher R. Pudney
- David K. ColeDavid K. ColeImmunocore Ltd., Milton Park, Abingdon OX14 4RY, U.K.Division of Infection & Immunity, Cardiff University, Cardiff CF14 4XN, U.K.More by David K. Cole
- Marc W. van der Kamp*Marc W. van der Kamp*Email: [email protected]School of Biochemistry, University of Bristol, Biomedical Sciences Building, Bristol BS8 1TD, U.K.More by Marc W. van der Kamp
Abstract
Accurate and efficient in silico ranking of protein–protein binding affinities is useful for protein design with applications in biological therapeutics. One popular approach to rank binding affinities is to apply the molecular mechanics Poisson–Boltzmann/generalized Born surface area (MMPB/GBSA) method to molecular dynamics (MD) trajectories. Here, we identify protocols that enable the reliable evaluation of T-cell receptor (TCR) variants binding to their target, peptide-human leukocyte antigens (pHLAs). We suggest different protocols for variant sets with a few (≤4) or many mutations, with entropy corrections important for the latter. We demonstrate how potential outliers could be identified in advance and that just 5–10 replicas of short (4 ns) MD simulations may be sufficient for the reproducible and accurate ranking of TCR variants. The protocols developed here can be applied toward in silico screening during the optimization of therapeutic TCRs, potentially reducing both the cost and time taken for biologic development.
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You are free to share(copy and redistribute) this article in any medium or format and to adapt(remix, transform, and build upon) the material for any purpose, even commercially within the parameters below:
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License Summary*
You are free to share(copy and redistribute) this article in any medium or format and to adapt(remix, transform, and build upon) the material for any purpose, even commercially within the parameters below:
Creative Commons (CC): This is a Creative Commons license.
Attribution (BY): Credit must be given to the creator.
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Introduction
Figure 1
Figure 1. (A) Overview of the TCR–pHLA complex. The T-cell receptor (TCR) is comprised of two (α and β) domains, which engage the peptide-human leukocyte antigen (pHLA) complex. (B) Zoom in on the TCR–pHLA binding site from two different angles, demonstrating that the binding interface is composed of six complementarity-determining region (CDR) loops on the TCR, which engage both the peptide and two α-helices on the pHLA complex.
Methods
Structure Preparation
Molecular Dynamics Simulations
MMPB/GBSA Theory and Methodology



Solute Entropy Corrections


Assessment of the Quality of Prediction
Simulation Timings
Results and Discussion
Modulation of the Internal Dielectric Constant Drastically Improves Predictability
Figure 2
Figure 2. Modulation of the interior dielectric constant improves MMPBSA predictability. Determined Spearman’s rank (rs) and Pearson’s r (rp) values for MMPB/GBSA calculations for the 1G4 (A) and A6 (B) test sets. Results are plotted with and without the three identified outliers described in the text for both data sets. “Di” followed by a value indicates the internal dielectric constant value used (see the Methods section). Exemplar scatter plots with lines of best fit for the 1G4 (C) and A6 (D) test sets using either MMGBSA or MMPBSA (at different internal dielectric constants) methodology. For (C) and (D), outliers are labeled. Scatter plots in panels (C) and (D) are also colored according to the number of charged mutations made between the variant and the WT. Complete scatter graphs for all results are provided in Figures S1 and S2.
Figure 3
Figure 3. Potential rationale for outliers identified in our MMPB/GBSA Calculations. (A) Sequences of the CDR3α loop of the three 1G4 outliers, with positions mutated shown in bold. All 1G4 variant sequences are provided in Table S4. WT A6 TCR–pHLA structure with the two outlier mutation sites S100 (B) and Q30 (C) labeled. Predicted water sites (using 3D-RISM (37,38) and Placevent, (39) see the Methods section) that form bridged water hydrogen bonds to pHLA residues are shown (here, all donor–acceptor heavy atom distances are within 3 Å). The calculated water density distribution function g(r) is shown for water molecules, demonstrating that they are all predicted to have a very high occupancy.
Effect of Inclusion of Explicit Water Molecules
Figure 4
Figure 4. Impact of explicit water molecules on binding affinity predictions. Determined Spearman’s rank (rs) and Pearson’s r (rp) values for MMPB/GBSA calculations on the 1G4 (A, B) and A6 (C, D) test sets for different numbers of explicit water molecules included in the calculation. Exemplar scatter plots for the 1G4 (E) and A6 (F) test sets showing the impact of the inclusion of an increasing number of explicit water molecules when using the MMPBSA method with ϵint set to 6 (Di 6). Scatter points are colored according to the number of charged mutations made between the variant and the WT. Complete scatter graphs for all results are provided in Figures S5–S8.
Impact of Solute Entropy Corrections
Figure 5
Figure 5. Illustration of the truncated-normal mode analysis (Trunc-NMA) method used to calculate a solute entropy correction for the 1G4 test set. Residues included in Trunc-NMA calculations are colored in blue (TCR) or magenta (pHLA) if they are flexible in NMA calculations or green if they are frozen (and therefore make up part of the buffer region). Residues colored in white are not included in the calculation (see the Methods section). The 1000 water molecules retained in the calculation are shown as transparent spheres.
Figure 6
Figure 6. Impact of solute entropy corrections on our MMPB/GBSA calculations. (A) Spearman’s rank (rs, unhashed bars) and Pearson’s r (rp, hashed bars) values determined for MMPB/GBSA calculations on the 1G4 test set with ϵint set to 6 (Di 6). Results are presented using a variable number of waters without any entropy corrections included as well as with the Trunc-NMA and Int-Entropy approaches. (B) Exemplar scatter plots for the 1G4 test set with the PBSA approach (with ϵint set to 6) including 50 explicit water molecules. Panels compare no entropy corrections (left), with Int-Entropy corrections (middle) and with Trunc-NMA corrections (right). (C) Impact of the inclusion of the Int-Entropy correction to the A6 data set, with the rs and rp values colored as in (A). All results are without any explicit water molecules included. (D) Exemplar scatter plots for the A6 test set with the PBSA approach (with ϵint set to 6) and no explicit water molecules. Panels compare no entropy corrections (left), with Int-Entropy corrections (right). More complete results, including comparing the effect of removing outliers, are provided in Figure S11.
How Many Replicas Are Required for Reproducible MMPB/GBSA Calculations?
Figure 7
Figure 7. Bootstrapping to assess the impact of using different numbers of replicas to obtain Spearman’s rank for some of the protocols evaluated in this study. Panels (A) and (B) focus on GBSA and PBSA approaches with no explicit waters included. Panel (C) focuses on the PBSA method with ϵint set to 6. Panel (D) focuses on the PBSA method (ϵint set to 6) with 50 explicit water molecules included with and without the Trunc-NMA correction applied. Measurements with the 1G4 and A6 test sets are colored black and red, respectively. In each panel, the average of the 1 million bootstrap resamples are used to calculate Spearman’s rank when using a differing number of replicas, with the error bars depicting 95% confidence intervals. The complete data is used in all cases (i.e., the outliers discussed above are included). Equivalent results with the Pearson’s r metric are provided in Figure S12.
Conclusions
Supporting Information
The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jcim.1c00765.
Details of simulation setup and equilibration, truncated-normal mode calculations, and explicit water selection; (additional) plots of computational vs experimental ΔΔG values, residuals, number of water-bridged and solute–solute hydrogen bonds, histograms of gas-phase interaction energies, effect of entropy corrections on Spearman’s rank and Pearson’s r, and bootstrapping analysis of Pearson’s r; tables of histidine tautomers, experimental TCR–pHLA affinities from literature, CDR loop sequences, and mean absolute deviations (MADs) for linear fits (PDF)
Terms & Conditions
Most electronic Supporting Information files are available without a subscription to ACS Web Editions. Such files may be downloaded by article for research use (if there is a public use license linked to the relevant article, that license may permit other uses). Permission may be obtained from ACS for other uses through requests via the RightsLink permission system: http://pubs.acs.org/page/copyright/permissions.html.
Acknowledgments
The authors would like to thank Dr. Dimas Suarez (Univ. of Oviedo, Spain) for assistance in modifying the Nmode program to enable the running of Trunc-NMA calculations.
CDR | complementarity-determining region |
Int-Entropy | interaction entropy |
ϵint; Di | internal dielectric constant |
MD | molecular dynamics |
MMPB/GBSA | molecular mechanics Poisson–Boltzmann/generalized Born surface area |
pHLA | peptide-human leukocyte antigen |
PBA | polar buried area |
PPI | protein–protein interaction |
g(r) | radial distribution function |
TCR | T-cell receptor |
Trunc-NMA | truncated-normal mode analysis |
References
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- 5Miller, B. R.; McGee, T. D.; Swails, J. M.; Homeyer, N.; Gohlke, H.; Roitberg, A. E. MMPBSA.Py: An Efficient Program for End-State Free Energy Calculations. J. Chem. Theory Comput. 2012, 8, 3314– 3321, DOI: 10.1021/ct300418hGoogle Scholar5https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhtV2gtrzP&md5=cc4148bd8f70c7cad94fd3ec6f580e52MMPBSA.py: An Efficient Program for End-State Free Energy CalculationsMiller, Bill R., III; McGee, T. Dwight, Jr.; Swails, Jason M.; Homeyer, Nadine; Gohlke, Holger; Roitberg, Adrian E.Journal of Chemical Theory and Computation (2012), 8 (9), 3314-3321CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)MM-PBSA is a post-processing end-state method to calc. free energies of mols. in soln. MMPBSA.py is a program written in Python for streamlining end-state free energy calcns. using ensembles derived from mol. dynamics (MD) or Monte Carlo (MC) simulations. Several implicit solvation models are available with MMPBSA.py, including the Poisson-Boltzmann Model, the Generalized Born Model, and the Ref. Interaction Site Model. Vibrational frequencies may be calcd. using normal mode or quasi-harmonic anal. to approx. the solute entropy. Specific interactions can also be dissected using free energy decompn. or alanine scanning. A parallel implementation significantly speeds up the calcn. by dividing frames evenly across available processors. MMPBSA.py is an efficient, user-friendly program with the flexibility to accommodate the needs of users performing end-state free energy calcns. The source code can be downloaded at http://ambermd.org/ with AmberTools, released under the GNU General Public License.
- 6Genheden, S.; Ryde, U. The MM/PBSA and MM/GBSA Methods to Estimate Ligand-Binding Affinities. Expert Opin. Drug Discovery 2015, 10, 449– 461, DOI: 10.1517/17460441.2015.1032936Google Scholar6https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXntFGktr8%253D&md5=b123b88809f275564f95a2271ebd159fThe MM/PBSA and MM/GBSA methods to estimate ligand-binding affinitiesGenheden, Samuel; Ryde, UlfExpert Opinion on Drug Discovery (2015), 10 (5), 449-461CODEN: EODDBX; ISSN:1746-0441. (Informa Healthcare)Introduction: The mol. mechanics energies combined with the Poisson-Boltzmann or generalized Born and surface area continuum solvation (MM/PBSA and MM/GBSA) methods are popular approaches to est. the free energy of the binding of small ligands to biol. macromols. They are typically based on mol. dynamics simulations of the receptor-ligand complex and are therefore intermediate in both accuracy and computational effort between empirical scoring and strict alchem. perturbation methods. They have been applied to a large no. of systems with varying success. Areas covered: The authors review the use of MM/PBSA and MM/GBSA methods to calc. ligand-binding affinities, with an emphasis on calibration, testing and validation, as well as attempts to improve the methods, rather than on specific applications. Expert opinion: MM/PBSA and MM/GBSA are attractive approaches owing to their modular nature and that they do not require calcns. on a training set. They have been used successfully to reproduce and rationalize exptl. findings and to improve the results of virtual screening and docking. However, they contain several crude and questionable approxns., for example, the lack of conformational entropy and information about the no. and free energy of water mols. in the binding site. Moreover, there are many variants of the method and their performance varies strongly with the tested system. Likewise, most attempts to ameliorate the methods with more accurate approaches, for example, quantum-mech. calcns., polarizable force fields or improved solvation have deteriorated the results.
- 7Holland, C. J.; Crean, R. M.; Pentier, J. M.; de Wet, B.; Lloyd, A.; Srikannathasan, V.; Lissin, N.; Lloyd, K. A.; Blicher, T. H.; Conroy, P. J.; Hock, M.; Pengelly, R. J.; Spinner, T. E.; Cameron, B.; Potter, E. A.; Jeyanthan, A.; Molloy, P. E.; Sami, M.; Aleksic, M.; Liddy, N.; Robinson, R. A.; Harper, S.; Lepore, M.; Pudney, C. R.; van der Kamp, M. W.; Rizkallah, P. J.; Jakobsen, B. K.; Vuidepot, A.; Cole, D. K. Specificity of Bispecific T Cell Receptors and Antibodies Targeting Peptide-HLA. J. Clin. Invest. 2020, 130, 2673– 2688, DOI: 10.1172/JCI130562Google Scholar7https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXpt12lu7w%253D&md5=201d6c772bb649358f25d8f8c5ef5f46Specificity of bispecific T cell receptors and antibodies targeting peptide-HLAHolland, Christopher J.; Crean, Rory M.; Pentier, Johanne M.; de Wet, Ben; Lloyd, Angharad; Srikannathasan, Velupillai; Lissin, Nikolai; Lloyd, Katy A.; Blicher, Thomas H.; Conroy, Paul J.; Hock, Miriam; Pengelly, Robert J.; Spinner, Thomas E.; Cameron, Brian; Potter, Elizabeth A.; Jeyanthan, Anitha; Molloy, Peter E.; Sami, Malkit; Aleksic, Milos; Liddy, Nathaniel; Robinson, Ross A.; Harper, Stephen; Lepore, Marco; Pudney, Chris R.; van der Kamp, Marc W.; Rizkallah, Pierre J.; Jakobsen, Bent K.; Vuidepot, Annelise; Cole, David K.Journal of Clinical Investigation (2020), 130 (5), 2673-2688CODEN: JCINAO; ISSN:1558-8238. (American Society for Clinical Investigation)Tumor-assocd. peptide-human leukocyte antigen complexes (pHLAs) represent the largest pool of cell surface-expressed cancer-specific epitopes, making them attractive targets for cancer therapies. Sol. bispecific mols. that incorporate an anti-CD3 effector function are being developed to redirect T cells against these targets using 2 different approaches. The first achieves pHLA recognition via affinity-enhanced versions of natural TCRs (e.g., immune-mobilizing monoclonal T cell receptors against cancer [ImmTAC] mols.), whereas the second harnesses an antibody-based format (TCR-mimic antibodies). For both classes of reagent, target specificity is vital, considering the vast universe of potential pHLA mols. that can be presented on healthy cells. Here, we made use of structural, biochem., and computational approaches to investigate the mol. rules underpinning the reactivity patterns of pHLA-targeting bispecifics. We demonstrate that affinity-enhanced TCRs engage pHLA using a comparatively broad and balanced energetic footprint, with interactions distributed over several HLA and peptide side chains. As ImmTAC mols., these TCRs also retained a greater degree of pHLA selectivity, with less off-target activity in cellular assays. Conversely, TCR-mimic antibodies tended to exhibit binding modes focused more toward hot spots on the HLA surface and exhibited a greater degree of crossreactivity. Our findings extend our understanding of the basic principles that underpin pHLA selectivity and exemplify a no. of mol. approaches that can be used to probe the specificity of pHLA-targeting mols., aiding the development of future reagents.
- 8Zoete, V.; Irving, M. B.; Michielin, O. MM-GBSA Binding Free Energy Decomposition and T Cell Receptor Engineering. J. Mol. Recognit. 2010, 23, 142– 152, DOI: 10.1002/jmr.1005Google Scholar8https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXitVShsbs%253D&md5=aad0420c4d0c70babd6470d05926d551MM-GBSA binding free energy decomposition and T cell receptor engineeringZoete, V.; Irving, M. B.; Michielin, O.Journal of Molecular Recognition (2010), 23 (2), 142-152CODEN: JMORE4; ISSN:0952-3499. (John Wiley & Sons Ltd.)A review. Recognition by the T-cell receptor (TCR) of immunogenic peptides (p) presented by class I major histocompatibility complexes (MHC) is the key event in the immune response against virus infected cells or tumor cells. The major determinant of T cell activation is the affinity of the TCR for the peptide-MHC complex, though kinetic parameters are also important. A study of the 2C TCR/SIYR/H-2Kb system using a binding free energy decompn. (BFED) based on the MM-GBSA approach had been performed to assess the performance of the approach on this system. The results showed that the TCR-p-MHC BFED including entropic terms provides a detailed and reliable description of the energetics of the interaction (Zoete and Michielin, ). Based on these results, we have developed a new approach to design sequence modifications for a TCR recognizing the human leukocyte antigen (HLA)-A2 restricted tumor epitope NY-ESO-1. NY-ESO-1 is a cancer testis antigen expressed not only in melanoma, but also on several other types of cancers. It has been obsd. at high frequencies in melanoma patients with unusually pos. clin. outcome and, therefore, represents an interesting target for adoptive transfer with modified TCR. Sequence modifications of TCR potentially increasing the affinity for this epitope have been proposed and tested in vitro. T cells expressing some of the proposed TCR mutants showed better T cell functionality, with improved killing of peptide-loaded T2 cells and better proliferative capacity compared to the wild type TCR expressing cells. These results open the door of rational TCR design for adoptive transfer cancer therapy. Copyright © 2010 John Wiley & Sons, Ltd.
- 9Crean, R. M.; MacLachlan, B. J.; Madura, F.; Whalley, T.; Rizkallah, P. J.; Holland, C. J.; McMurran, C.; Harper, S.; Godkin, A.; Sewell, A. K.; Pudney, C. R.; van der Kamp, M. W.; Cole, D. K. Molecular Rules Underpinning Enhanced Affinity Binding of Human T Cell Receptors Engineered for Immunotherapy. Mol. Ther.─Oncolytics 2020, 18, 443– 456, DOI: 10.1016/j.omto.2020.07.008Google Scholar9https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXit1Kqu7vO&md5=0793f2e46638c90ffe471d23bd7eaf0eMolecular Rules Underpinning Enhanced Affinity Binding of Human T Cell Receptors Engineered for ImmunotherapyCrean, Rory M.; MacLachlan, Bruce J.; Madura, Florian; Whalley, Thomas; Rizkallah, Pierre J.; Holland, Christopher J.; McMurran, Catriona; Harper, Stephen; Godkin, Andrew; Sewell, Andrew K.; Pudney, Christopher R.; van der Kamp, Marc W.; Cole, David K.Molecular Therapy--Oncolytics (2020), 18 (), 443-456CODEN: MTOHDL; ISSN:2372-7705. (Elsevier Inc.)Immuno-oncol. approaches that utilize T cell receptors (TCRs) are becoming highly attractive because of their potential to target virtually all cellular proteins, including cancer-specific epitopes, via the recognition of peptide-human leukocyte antigen (pHLA) complexes presented at the cell surface. However, because natural TCRs generally recognize cancer-derived pHLAs with very weak affinities, efforts have been made to enhance their binding strength, in some cases by several million-fold. In this study, we investigated the mechanisms underpinning human TCR affinity enhancement by comparing the crystal structures of engineered enhanced affinity TCRs with those of their wild-type progenitors. Addnl., we performed mol. dynamics simulations to better understand the energetic mechanisms driving the affinity enhancements. These data demonstrate that supra-physiol. binding affinities can be achieved without altering native TCR-pHLA binding modes via relatively subtle modifications to the interface contacts, often driven through the addn. of buried hydrophobic residues. Individual energetic components of the TCR-pHLA interaction governing affinity enhancements were distinct and highly variable for each TCR, often resulting from additive, or knock-on, effects beyond the mutated residues. This comprehensive anal. of affinity-enhanced TCRs has important implications for the future rational design of engineered TCRs as efficacious and safe drugs for cancer treatment.
- 10Zoete, V.; Irving, M.; Ferber, M.; Cuendet, M. A.; Michielin, O. Structure-Based, Rational Design of T Cell Receptors. Front. Immunol. 2013, 4, 268 DOI: 10.3389/fimmu.2013.00268Google Scholar10https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC2cflt1yksA%253D%253D&md5=86915a4ce37665203344aee030a5c316Structure-Based, Rational Design of T Cell ReceptorsZoete V; Irving M; Ferber M; Cuendet M A; Michielin OFrontiers in immunology (2013), 4 (), 268 ISSN:1664-3224.Adoptive cell transfer using engineered T cells is emerging as a promising treatment for metastatic melanoma. Such an approach allows one to introduce T cell receptor (TCR) modifications that, while maintaining the specificity for the targeted antigen, can enhance the binding and kinetic parameters for the interaction with peptides (p) bound to major histocompatibility complexes (MHC). Using the well-characterized 2C TCR/SIYR/H-2K(b) structure as a model system, we demonstrated that a binding free energy decomposition based on the MM-GBSA approach provides a detailed and reliable description of the TCR/pMHC interactions at the structural and thermodynamic levels. Starting from this result, we developed a new structure-based approach, to rationally design new TCR sequences, and applied it to the BC1 TCR targeting the HLA-A2 restricted NY-ESO-1157-165 cancer-testis epitope. Fifty-four percent of the designed sequence replacements exhibited improved pMHC binding as compared to the native TCR, with up to 150-fold increase in affinity, while preserving specificity. Genetically engineered CD8(+) T cells expressing these modified TCRs showed an improved functional activity compared to those expressing BC1 TCR. We measured maximum levels of activities for TCRs within the upper limit of natural affinity, K D = ∼1 - 5 μM. Beyond the affinity threshold at K D < 1 μM we observed an attenuation in cellular function, in line with the "half-life" model of T cell activation. Our computer-aided protein-engineering approach requires the 3D-structure of the TCR-pMHC complex of interest, which can be obtained from X-ray crystallography. We have also developed a homology modeling-based approach, TCRep 3D, to obtain accurate structural models of any TCR-pMHC complexes when experimental data is not available. Since the accuracy of the models depends on the prediction of the TCR orientation over pMHC, we have complemented the approach with a simplified rigid method to predict this orientation and successfully assessed it using all non-redundant TCR-pMHC crystal structures available. These methods potentially extend the use of our TCR engineering method to entire TCR repertoires for which no X-ray structure is available. We have also performed a steered molecular dynamics study of the unbinding of the TCR-pMHC complex to get a better understanding of how TCRs interact with pMHCs. This entire rational TCR design pipeline is now being used to produce rationally optimized TCRs for adoptive cell therapies of stage IV melanoma.
- 11Maffucci, I.; Contini, A. Improved Computation of Protein–Protein Relative Binding Energies with the Nwat-MMGBSA Method. J. Chem. Inf. Model. 2016, 56, 1692– 1704, DOI: 10.1021/acs.jcim.6b00196Google Scholar11https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28Xht12mtbbJ&md5=74aa27e8eaf6c304edc80e432beb7653Improved Computation of Protein-Protein Relative Binding Energies with the Nwat-MMGBSA MethodMaffucci, Irene; Contini, AlessandroJournal of Chemical Information and Modeling (2016), 56 (9), 1692-1704CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)A MMGBSA variant (here referred to as Nwat-MMGBSA), based on the inclusion of a certain no. of explicit water mols. (Nwat) during the calcns., has been tested on a set of 20 protein-protein complexes, using the correlation between predicted and exptl. binding energy as the evaluation metric. Beside the Nwat parameter, the effect of the force field, the mol. dynamics simulation length, and the implicit solvent model used in the MMGBSA anal. have been also evaluated. Considering 30 interfacial water mols. improved the correlation between predicted and exptl. binding energies by up to 30%, compared to the std. approach. Moreover, the correlation resulted rather sensitively to the force field and, to a minor extent, to the implicit solvent model, and to the length of the MD simulation.
- 12Wang, C.; Greene, D.; Xiao, L.; Qi, R.; Luo, R. Recent Developments and Applications of the MMPBSA Method. Front. Mol. Biosci. 2018, 4, 87 DOI: 10.3389/fmolb.2017.00087Google ScholarThere is no corresponding record for this reference.
- 13Sun, H.; Li, Y.; Tian, S.; Xu, L.; Hou, T. Assessing the Performance of MM/PBSA and MM/GBSA Methods. 4. Accuracies of MM/PBSA and MM/GBSA Methodologies Evaluated by Various Simulation Protocols Using PDBbind Data Set. Phys. Chem. Chem. Phys. 2014, 16, 16719– 16729, DOI: 10.1039/C4CP01388CGoogle Scholar13https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhtFSltrzI&md5=d0271f6d49fb026bba944a121aa2a8fdAssessing the performance of MM/PBSA and MM/GBSA methods. 4. Accuracies of MM/PBSA and MM/GBSA methodologies evaluated by various simulation protocols using PDBbind data setSun, Huiyong; Li, Youyong; Tian, Sheng; Xu, Lei; Hou, TingjunPhysical Chemistry Chemical Physics (2014), 16 (31), 16719-16729CODEN: PPCPFQ; ISSN:1463-9076. (Royal Society of Chemistry)By using different evaluation strategies, we systemically evaluated the performance of Mol. Mechanics/Generalized Born Surface Area (MM/GBSA) and Mol. Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) methodologies based on more than 1800 protein-ligand crystal structures in the PDBbind database. The results can be summarized as follows: (1) for the one-protein-family/one-binding-ligand case which represents the unbiased protein-ligand complex sampling, both MM/GBSA and MM/PBSA methodologies achieve approx. equal accuracies at the interior dielec. const. of 4 (with rp = 0.408 ± 0.006 of MM/GBSA and rp = 0.388 ± 0.006 of MM/PBSA based on the minimized structures); while for the total dataset (1864 crystal structures), the overall best Pearson correlation coeff. (rp = 0.579 ± 0.002) based on MM/GBSA is better than that of MM/PBSA (rp = 0.491 ± 0.003), indicating that biased sampling may significantly affect the accuracy of the predicted result (some protein families contain too many instances and can bias the overall predicted accuracy). Therefore, family based classification is needed to evaluate the two methodologies; (2) the prediction accuracies of MM/GBSA and MM/PBSA for different protein families are quite different with rp ranging from 0 to 0.9, whereas the correlation and ranking scores (an averaged rp/rs over a list of protein folds and also representing the unbiased sampling) given by MM/PBSA (rp-score = 0.506 ± 0.050 and rs-score = 0.481 ± 0.052) are comparable to those given by MM/GBSA (rp-score = 0.516 ± 0.047 and rs-score = 0.463 ± 0.047) at the fold family level; (3) for the overall prediction accuracies, mol. dynamics (MD) simulation may not be quite necessary for MM/GBSA (rp-minimized = 0.579 ± 0.002 and rp-1ns = 0.564 ± 0.002), but is needed for MM/PBSA (rp-minimized = 0.412 ± 0.003 and rp-1ns = 0.491 ± 0.003). However, for the individual systems, whether to use MD simulation is depended. (4) both MM/GBSA and MM/PBSA may be unable to give successful predictions for the ligands with high formal charges, with the Pearson correlation coeff. ranging from 0.621 ± 0.003 (neutral ligands) to 0.125 ± 0.142 (ligands with a formal charge of 5). Therefore, it can be summarized that, although MM/GBSA and MM/PBSA perform similarly in the unbiased dataset, for the currently available crystal structures in the PDBbind database, compared with MM/GBSA, which may be used in multi-target comparisons, MM/PBSA is more sensitive to the investigated systems, and may be more suitable for individual-target-level binding free energy ranking. This study may provide useful guidance for the post-processing of docking based studies.
- 14Zhu, Y.-L.; Beroza, P.; Artis, D. R. Including Explicit Water Molecules as Part of the Protein Structure in MM/PBSA Calculations. J. Chem. Inf. Model. 2014, 54, 462– 469, DOI: 10.1021/ci4001794Google Scholar14https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXitVWnsb7J&md5=285d8818f326df9f889912aaf0313e7dIncluding Explicit Water Molecules as Part of the Protein Structure in MM/PBSA CalculationsZhu, Yong-Liang; Beroza, Paul; Artis, Dean R.Journal of Chemical Information and Modeling (2014), 54 (2), 462-469CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)Water is the natural medium of mols. in the cell and plays an important role in protein structure, function and interaction with small mol. ligands. However, the widely used mol. mechanics Poisson-Boltzmann surface area (MM/PBSA) method for binding energy calcn. does not explicitly take account of water mols. that mediate key protein-ligand interactions. We have developed a protocol to include water mols. that mediate ligand-protein interactions as part of the protein structure in calcn. of MM/PBSA binding energies (a method we refer to as water-MM/PBSA) for a series of JNK3 kinase inhibitors. Improved correlation between water-MM/PBSA binding energies and exptl. IC50 values was obtained compared to that obtained from classical MM/PBSA binding energy. This improved correlation was further validated using sets of neuraminidase and avidin inhibitors. The obsd. improvement, however, appears to be limited to systems in which there are water-mediated ligand-protein hydrogen bond interactions. We conclude that the water-MM/PBSA method performs better than classical MM/PBSA in predicting binding affinities when water mols. play a direct role in mediating ligand-protein hydrogen bond interactions.
- 15Godschalk, F.; Genheden, S.; Söderhjelm, P.; Ryde, U. Comparison of MM/GBSA Calculations Based on Explicit and Implicit Solvent Simulations. Phys. Chem. Chem. Phys. 2013, 15, 7731, DOI: 10.1039/c3cp00116dGoogle Scholar15https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXmvVSgurc%253D&md5=00b6fa66b6215d07c52bec4af6300d80Comparison of MM/GBSA calculations based on explicit and implicit solvent simulationsGodschalk, Frithjof; Genheden, Samuel; Soederhjelm, Paer; Ryde, UlfPhysical Chemistry Chemical Physics (2013), 15 (20), 7731-7739CODEN: PPCPFQ; ISSN:1463-9076. (Royal Society of Chemistry)Mol. mechanics with generalized Born and surface area solvation (MM/GBSA) is a popular method to calc. the free energy of the binding of ligands to proteins. It involves mol. dynamics (MD) simulations with an explicit solvent of the protein-ligand complex to give a set of snapshots for which energies are calcd. with an implicit solvent. This change in the solvation method (explicit implicit) would strictly require that the energies are reweighted with the implicit-solvent energies, which is normally not done. In this paper we calc. MM/GBSA energies with two generalized Born models for snapshots generated by the same methods or by explicit-solvent simulations for five synthetic N-acetyllactosamine derivs. binding to galectin-3. We show that the resulting energies are very different both in abs. and relative terms, showing that the change in the solvent model is far from innocent and that std. MM/GBSA is not a consistent method. The ensembles generated with the various solvent models are quite different with root-mean-square deviations of 1.2-1.4 Å. The ensembles can be converted to each other by performing short MD simulations with the new method, but the convergence is slow, showing mean abs. differences in the calcd. energies of 6-7 kJ mol-1 after 2 ps simulations. Minimisations show even slower convergence and there are strong indications that the energies obtained from minimized structures are different from those obtained by MD.
- 16Liu, X.; Peng, L.; Zhang, J. Z. H. Accurate and Efficient Calculation of Protein–Protein Binding Free Energy-Interaction Entropy with Residue Type-Specific Dielectric Constants. J. Chem. Inf. Model. 2019, 59, 272– 281, DOI: 10.1021/acs.jcim.8b00248Google Scholar16https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXit1Sgsb7F&md5=bd2735b50518cd7951bca4a98b1580f6Accurate and Efficient Calculation of Protein-Protein Binding Free Energy-Interaction Entropy with Residue Type-Specific Dielectric ConstantsLiu, Xiao; Peng, Long; Zhang, John Z. H.Journal of Chemical Information and Modeling (2019), 59 (1), 272-281CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)Accurate and efficient computation of protein-protein binding free energy remains a grand challenge. The authors develop a new strategy to achieve efficient calcn. for total protein-protein binding free energies with improved accuracy. The new method combines the recently developed interaction entropy method for efficient computation of entropic change together using residue type-specific dielec. consts. in the framework of MM/GBSA to achieve optimal result for protein-protein binding free energies. The new strategy is computationally efficient and accurate than that using std. MM/GBSA methods in which the entropic computation was performed by the normal model approach and the protein interior is represented by the std. dielec. const. (typically set to 1), both in terms of accuracy and computational efficiency. The authors' study using the new strategy on a set of randomly selected 20 protein-protein binding systems produced an optimal dielec. const. of 2.7 for charged residues and 1.1 for noncharged residues. Using this new strategy, the mean abs. error in computed binding free energies for these 20 selected protein-protein systems is significantly reduced by >3-fold while the computational cost is reduced by >2 orders of magnitude, compared to the result using std. MM/GBSA method with the normal mode approach. A similar improvement in accuracy is confirmed for a test set consisting of 10 protein-protein systems.
- 17Goebeler, M.-E.; Bargou, R. C. T Cell-Engaging Therapies ─ BiTEs and Beyond. Nat. Rev. Clin. Oncol. 2020, 17, 418– 434, DOI: 10.1038/s41571-020-0347-5Google Scholar17https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BB38zgsVWnsA%253D%253D&md5=2beedd06773540f367596f6e621e5f9dT cell-engaging therapies - BiTEs and beyondGoebeler Maria-Elisabeth; Goebeler Maria-Elisabeth; Bargou Ralf CNature reviews. Clinical oncology (2020), 17 (7), 418-434 ISSN:.Immuno-oncology approaches have entered clinical practice, with tremendous progress particularly in the field of T cell-engaging therapies over the past decade. Herein, we provide an overview of the current status of bispecific T cell engager (BiTE) therapy, considering the unprecedented new indication for such therapy in combating minimal (or measurable) residual disease in patients with acute lymphoblastic leukaemia, and the development of novel approaches based on this concept. Key aspects that we discuss include the current clinical data, challenges relating to treatment administration and patient monitoring, toxicities and resistance to treatment, and novel strategies to overcome these hurdles as well as to broaden the indications for BiTE therapy, particularly to common solid cancers. Elucidation of mechanisms of resistance and immune escape and new technologies used in drug development pave the way for new and more-effective therapies and rational combinatorial approaches. In particular, we highlight novel therapeutic agents, such as bifunctional checkpoint-inhibitory T cell engagers (CiTEs), simultaneous multiple interaction T cell engagers (SMITEs), trispecific killer engagers (TriKEs) and BiTE-expressing chimeric antigen receptor (CAR) T cells (CART.BiTE cells), designed to integrate various immune functions into one molecule or a single cellular vector and thereby enhance efficacy without compromising safety. We also discuss the targeting of intracellular tumour-associated epitopes using bispecific constructs with T cell receptor (TCR)-derived, rather than an antibody-based, antigen-recognition domains, termed immune-mobilizing monoclonal TCRs against cancer (ImmTACs), which might broaden the armamentarium of T cell-engaging therapies.
- 18Hewitt, E. W. The MHC Class I Antigen Presentation Pathway: Strategies for Viral Immune Evasion. Immunology 2003, 110, 163– 169, DOI: 10.1046/j.1365-2567.2003.01738.xGoogle Scholar18https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3sXotFSmtbk%253D&md5=c669b243791ce0c2a3e6e6dad5665c12The MHC class I antigen presentation pathway: Strategies for viral immune evasionHewitt, Eric W.Immunology (2003), 110 (2), 163-169CODEN: IMMUAM; ISSN:0019-2805. (Blackwell Publishing Ltd.)A review. Presumably because of the selective pressure exerted by the immune system, many viruses have evolved proteins that interfere with antigen presentation by major histocompatibility complex (MHC) class I mols. These viruses utilize a whole variety of ingenious strategies to inhibit the MHC class I pathway. Viral proteins have been characterized that exploit bottlenecks in the MHC class I pathway, such as peptide translocation by the transporter assocd. with antigen processing. Alternatively, viral proteins can cause the degrdn. or mislocalization of MHC class I mols. This is often achieved by the subversion of the host cell's own protein degrdn. and trafficking pathways. As a consequence elucidation of how these viral proteins act to subvert host cell function will continue to give important insights not only into virus-host interactions but also the function and mechanism of cellular pathways.
- 19Oates, J.; Jakobsen, B. K. ImmTACs. Oncoimmunology 2013, 2, e22891 DOI: 10.4161/onci.22891Google ScholarThere is no corresponding record for this reference.
- 20Singh, N. K.; Riley, T. P.; Baker, S. C. B.; Borrman, T.; Weng, Z.; Baker, B. M. Emerging Concepts in TCR Specificity: Rationalizing and (Maybe) Predicting Outcomes. J. Immunol. 2017, 199, 2203– 2213, DOI: 10.4049/jimmunol.1700744Google Scholar20https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXhsFSmsrfI&md5=1bdf2bb4639bbb3074fe2b13969db69cEmerging Concepts in TCR Specificity: Rationalizing and (Maybe) Predicting OutcomesSingh, Nishant K.; Riley, Timothy P.; Baker, Sarah Catherine B.; Borrman, Tyler; Weng, Zhiping; Baker, Brian M.Journal of Immunology (2017), 199 (7), 2203-2213CODEN: JOIMA3; ISSN:0022-1767. (American Association of Immunologists)T cell specificity emerges from a myriad of processes, ranging from the biol. pathways that control T cell signaling to the structural and phys. mechanisms that influence how TCRs bind peptides and MHC proteins. Of these processes, the binding specificity of the TCR is a key component. However, TCR specificity is enigmatic: TCRs are at once specific but also cross-reactive. Although long appreciated, this duality continues to puzzle immunologists and has implications for the development of TCR-based therapeutics. In this review, we discuss TCR specificity, emphasizing results that have emerged from structural and phys. studies of TCR binding. We show how the TCR specificity/cross-reactivity duality can be rationalized from structural and biophys. principles. There is excellent agreement between predictions from these principles and classic predictions about the scope of TCR cross-reactivity. We demonstrate how these same principles can also explain amino acid preferences in immunogenic epitopes and highlight opportunities for structural considerations in predictive immunol.
- 21Aleksic, M.; Liddy, N.; Molloy, P. E.; Pumphrey, N.; Vuidepot, A.; Chang, K.-M.; Jakobsen, B. K. Different Affinity Windows for Virus and Cancer-Specific T-Cell Receptors: Implications for Therapeutic Strategies. Eur. J. Immunol. 2012, 42, 3174– 3179, DOI: 10.1002/eji.201242606Google Scholar21https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhsFWiu73E&md5=e3092ecba5cc0f263a48648659e896aaDifferent affinity windows for virus and cancer-specific T-cell receptors: Implications for therapeutic strategiesAleksic, Milos; Liddy, Nathaniel; Molloy, Peter E.; Pumphrey, Nick; Vuidepot, Annelise; Chang, Kyong-Mi; Jakobsen, Bent K.European Journal of Immunology (2012), 42 (12), 3174-3179CODEN: EJIMAF; ISSN:0014-2980. (Wiley-VCH Verlag GmbH & Co. KGaA)T-cell destiny during thymic selection depends on the affinity of the TCR for autologous peptide ligands presented in the context of MHC mols. This is a delicately balanced process; robust binding leads to neg. selection, yet some affinity for the antigen complex is required for pos. selection. All TCRs of the resulting repertoire thus have some intrinsic affinity for an MHC type presenting an assortment of peptides. Generally, TCR affinities of peripheral T cells will be low toward self-derived peptides, as these would have been presented during thymic selection, whereas, by serendipity, binding to pathogen-derived peptides that are encountered de novo could be stronger. A crucial question in assessing immunotherapeutic strategies for cancer is whether natural TCR repertoires have the capacity for efficiently recognizing tumor-assocd. peptide antigens. Here, we report a comprehensive comparison of TCR affinities to a range of HLA-A2 presented antigens. TCRs that bind viral antigens fall within a strikingly higher affinity range than those that bind cancer-related antigens. This difference may be one of the key explanations for tumor immune escape and for the deficiencies of T-cell vaccines against cancer.
- 22Richman, S. A.; Healan, S. J.; Weber, K. S.; Donermeyer, D. L.; Dossett, M. L.; Greenberg, P. D.; Allen, P. M.; Kranz, D. M. Development of a Novel Strategy for Engineering High-Affinity Proteins by Yeast Display. Protein Eng., Des. Sel. 2006, 19, 255– 264, DOI: 10.1093/protein/gzl008Google Scholar22https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28XmsVehsLk%253D&md5=4e79d4c21267d100f947758d560ef6c2Development of a novel strategy for engineering high-affinity proteins by yeast displayRichman, S. A.; Healan, S. J.; Weber, K. S.; Donermeyer, D. L.; Dossett, M. L.; Greenberg, P. D.; Allen, P. M.; Kranz, D. M.Protein Engineering, Design & Selection (2006), 19 (6), 255-264CODEN: PEDSBR; ISSN:1741-0126. (Oxford University Press)Yeast display provides a system for engineering high-affinity proteins using a fluorescent-labeled ligand and fluorescence-activated cell sorting (FACS). In cases where it is difficult to obtain purified ligands, or to access FACS instrumentation, an alternative selection strategy would be useful. Here we show that yeast expressing high-affinity proteins against a mammalian cell surface ligand could be rapidly selected by d. centrifugation. Yeast cell-mammalian cell conjugates were retained at the d. interface, sepd. from unbound yeast. High-affinity T cell receptors (TCRs) displayed on yeast were isolated using antigen presenting cells that expressed TCR ligands, peptides bound to products of the major histocompatibility complex (MHC). The procedure yielded 1000-fold enrichments, in a single centrifugation, of yeast displaying high-affinity TCRs. We defined the affinity limits of the method and isolated high-affinity TCR mutants against peptide variants that differed by only a single residue. The approach was applied to TCRs specific for class I or class II MHC, an important finding since peptide-class II MHC ligands have been particularly difficult to purify. As yeast display has also been used previously to identify antigen-specific antibodies, the method should be applicable to the selection of antibodies, as well as TCRs, with high-affinity for tumor cell-surface antigens.
- 23Harris, D. T.; Wang, N.; Riley, T. P.; Anderson, S. D.; Singh, N. K.; Procko, E.; Baker, B. M.; Kranz, D. M. Deep Mutational Scans as a Guide to Engineering High Affinity T Cell Receptor Interactions with Peptide-Bound Major Histocompatibility Complex. J. Biol. Chem. 2016, 291, 24566– 24578, DOI: 10.1074/jbc.M116.748681Google Scholar23https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XhvV2gurbM&md5=5970f622e9e00834e79a184d0425190aDeep mutational scans as a guide to engineering high affinity T cell receptor interactions with peptide-bound major histocompatibility complexHarris, Daniel T.; Wang, Ningyan; Riley, Timothy P.; Anderson, Scott D.; Singh, Nishant K.; Procko, Erik; Baker, Brian M.; Kranz, David M.Journal of Biological Chemistry (2016), 291 (47), 24566-24578CODEN: JBCHA3; ISSN:0021-9258. (American Society for Biochemistry and Molecular Biology)Proteins are often engineered to have higher affinity for their ligands to achieve therapeutic benefit. For example, many studies have used phage or yeast display libraries of mutants within complementarity-detg. regions to affinity mature antibodies and T cell receptors (TCRs). However, these approaches do not allow rapid assessment or evolution across the entire interface. By combining directed evolution with deep sequencing, it is now possible to generate sequence fitness landscapes that survey the impact of every amino acid substitution across the entire protein-protein interface. Here we used the results of deep mutational scans of a TCR-peptide-MHC interaction to guide mutational strategies. The approach yielded stable TCRs with affinity increases of >200-fold. The substitutions with the greatest enrichments based on the deep sequencing were validated to have higher affinity and could be combined to yield addnl. improvements. We also conducted in silico binding analyses for every substitution to compare them with the fitness landscape. Computational modeling did not effectively predict the impacts of mutations distal to the interface and did not account for yeast display results that depended on combinations of affinity and protein stability. However, computation accurately predicted affinity changes for mutations within or near the interface, highlighting the complementary strengths of computational modeling and yeast surface display coupled with deep mutational scanning for engineering high affinity TCRs.
- 24Chervin, A. S.; Aggen, D. H.; Raseman, J. M.; Kranz, D. M. Engineering Higher Affinity T Cell Receptors Using a T Cell Display System. J. Immunol. Methods 2008, 339, 175– 184, DOI: 10.1016/j.jim.2008.09.016Google Scholar24https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXhtl2qtb%252FK&md5=5a01b7c76c86837c1944570e3ba0e5fcEngineering higher affinity T cell receptors using a T cell display systemChervin, Adam S.; Aggen, David H.; Raseman, John M.; Kranz, David M.Journal of Immunological Methods (2008), 339 (2), 175-184CODEN: JIMMBG; ISSN:0022-1759. (Elsevier B.V.)The T cell receptor (TCR) dets. the cellular response to antigens, which are presented on the surface of target cells in the form of a peptide bound to a product of the major histocompatibility complex (pepMHC). The response of the T cell depends on the affinity of the TCR for the pepMHC, yet many TCRs have been shown to be of low affinity, and some naturally occurring T cell responses are poor due to low affinities. Accordingly, engineering the TCR for increased affinity for pepMHC, particularly tumor-assocd. antigens, has become an increasingly desirable goal, esp. with the advent of adoptive T cell therapies. For largely tech. reasons, to date there have been only a handful of TCRs engineered in vitro for higher affinity using well established methods of protein engineering. Here the authors report the use of a T cell display system, using a retroviral vector, for generating a high-affinity TCR from the mouse T cell clone 2C. The method relies on the display of the TCR, in its normal, signaling competent state, as a CD3 complex on the T cell surface. A library in the CDR3α of the 2C TCR was generated in the MSCV retroviral vector and transduced into a TCR-neg. hybridoma. Selection of a high-affinity, CD8-independent TCR was accomplished after only two rounds of flow cytometric sorting using the pepMHC SIYRYYGL/Kb (SIY/Kb). The selected TCR contained a sequence motif in the CDR3α with characteristics of several other TCRs previously selected by yeast display. In addn., it was possible to directly use the selected T cell hybridoma in functional assays without the need for sub-cloning, revealing that the selected TCR was capable of mediating CD8-independent activity. The method may be useful in the direct isolation and characterization of TCRs that could be used in therapies with adoptive transferred T cells.
- 25Sharma, P.; Kranz, D. M. Subtle Changes at the Variable Domain Interface of the T-Cell Receptor Can Strongly Increase Affinity. J. Biol. Chem. 2018, 293, 1820– 1834, DOI: 10.1074/jbc.M117.814152Google Scholar25https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXnsVygtbw%253D&md5=edae742c79a4914cebbc858a7fc307bbSubtle changes at the variable domain interface of the T-cell receptor can strongly increase affinitySharma, Preeti; Kranz, David M.Journal of Biological Chemistry (2018), 293 (5), 1820-1834CODEN: JBCHA3; ISSN:0021-9258. (American Society for Biochemistry and Molecular Biology)Most affinity-maturation campaigns for antibodies and T-cell receptors (TCRs) operate on the residues at the binding site, located within the loops known as complementarity-detg. regions (CDRs). Accordingly, mutations in contact residues, or so-called "second shell" residues, that increase affinity are typically identified by directed evolution involving combinatorial libraries. To det. the impact of residues located at a distance from the binding site, here we used single-codon libraries of both CDR and non-CDR residues to generate a deep mutational scan of a human TCR against the cancer antigen MART1-HLA-A2. Non-CDR residues included those at the interface of the TCR variable domains (Vα and βV) and surface-exposed framework residues. Mutational analyses showed that both Vα/Vβ interface and CDR residues were important in maintaining binding to MART-1-HLA-A2, probably due to either structural requirements for proper Vα/Vβ assocn. or direct contact with the ligand. More surprisingly, many V/V interface substitutions yielded improved binding to MART-1·HLA-A2. To further explore this finding, we constructed interface libraries and selected them for improved stability or affinity. Among the variants identified, one conservative substitution (F45βY) was most prevalent. Further anal. of F45βY showed that it enhanced thermostability and increased affinity by 60-fold. Thus, introducing a single hydroxyl group at the Vα/Vβ interface, at a significant distance from the TCR·peptide·MHC-binding site, remarkably affected ligand binding. The variant retained a high degree of specificity for MART-1HLA-A2, indicating that our approach provides a general strategy for engineering improvements in either sol. or cell-based TCRs for therapeutic purposes.
- 26Li, Y.; Moysey, R.; Molloy, P. E.; Vuidepot, A. L.; Mahon, T.; Baston, E.; Dunn, S.; Liddy, N.; Jacob, J.; Jakobsen, B. K.; Boulter, J. M. Directed Evolution of Human T-Cell Receptors with Picomolar Affinities by Phage Display. Nat. Biotechnol. 2005, 23, 349– 354, DOI: 10.1038/nbt1070Google Scholar26https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2MXitF2nt7o%253D&md5=925e7e535add7d4ce63b3b451b0bc8d4Directed evolution of human T-cell receptors with picomolar affinities by phage displayLi, Yi; Moysey, Ruth; Molloy, Peter E.; Vuidepot, Anne-Lise; Mahon, Tara; Baston, Emma; Dunn, Steven; Liddy, Nathaniel; Jacob, Jansen; Jakobsen, Bent K.; Boulter, Jonathan M.Nature Biotechnology (2005), 23 (3), 349-354CODEN: NABIF9; ISSN:1087-0156. (Nature Publishing Group)Peptides derived from almost all proteins, including disease-assocd. proteins, can be presented on the cell surface as peptide-human leukocyte antigen (pHLA) complexes. T cells specifically recognize pHLA with their clonally rearranged T-cell receptors (TCRs), whose natural affinities are limited to ∼1-100 μM. Here we describe the display of ten different human TCRs on the surface of bacteriophage, stabilized by a nonnative interchain disulfide bond. We report the directed evolution of high-affinity TCRs specific for two different pHLAs: the human T-cell lymphotropic virus type 1 (HTLV-1) tax11-19 peptide-HLA-A*0201 complex and the NY-ESO-157-165 tumor-assocd. peptide antigen-HLA-A*0201 complex, with affinities of up to 2.5 nM and 26 pM, resp., and we demonstrate their high specificity and sensitivity for targeting of cell-surface pHLAs.
- 27Madura, F.; Rizkallah, P. J.; Miles, K. M.; Holland, C. J.; Bulek, A. M.; Fuller, A.; Schauenburg, A. J. A.; Miles, J. J.; Liddy, N.; Sami, M.; Li, Y.; Hossain, M.; Baker, B. M.; Jakobsen, B. K.; Sewell, A. K.; Cole, D. K. T-Cell Receptor Specificity Maintained by Altered Thermodynamics. J. Biol. Chem. 2013, 288, 18766– 18775, DOI: 10.1074/jbc.M113.464560Google Scholar27https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhtVehsLbK&md5=15fa2cd1da454eec5b1ec4df85b7bd4dT-cell receptor specificity maintained by altered thermodynamicsMadura, Florian; Rizkallah, Pierre J.; Miles, Kim M.; Holland, Christopher J.; Bulek, Anna M.; Fuller, Anna; Schauenburg, Andrea J. A.; Miles, John J.; Liddy, Nathaniel; Sami, Malkit; Li, Yi; Hossain, Moushumi; Baker, Brian M.; Jakobsen, Bent K.; Sewell, Andrew K.; Cole, David K.Journal of Biological Chemistry (2013), 288 (26), 18766-18775CODEN: JBCHA3; ISSN:0021-9258. (American Society for Biochemistry and Molecular Biology)The T-cell receptor (TCR) recognizes peptides bound to major histocompatibility mols. (MHC) and allows T-cells to interrogate the cellular proteome for internal anomalies from the cell surface. The TCR contacts both MHC and peptide in an interaction characterized by weak affinity (KD = 100 nm to 270 μm). We used phage-display to produce a melanoma-specific TCR (α24β17) with a 30,000-fold enhanced binding affinity (KD = 0.6 nm) to aid our exploration of the mol. mechanisms utilized to maintain peptide specificity. Remarkably, although the enhanced affinity was mediated primarily through new TCR-MHC contacts, α24β17 remained acutely sensitive to modifications at every position along the peptide backbone, mimicking the specificity of the wild type TCR. Thermodn. analyses revealed an important role for solvation in directing peptide specificity. These findings advance our understanding of the mol. mechanisms that can govern the exquisite peptide specificity characteristic of TCR recognition.
- 28Pierce, B. G.; Hellman, L. M.; Hossain, M.; Singh, N. K.; Vander Kooi, C. W.; Weng, Z.; Baker, B. M. Computational Design of the Affinity and Specificity of a Therapeutic T Cell Receptor. PLoS Comput. Biol. 2014, 10, e1003478 DOI: 10.1371/journal.pcbi.1003478Google Scholar28https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXkvVOitLo%253D&md5=29ffc1ef992eb181b754b61e37f56b56Computational design of the affinity and specificity of a therapeutic T cell receptorPierce, Brian G.; Hellman, Lance M.; Hossain, Moushumi; Singh, Nishant K.; Vander Kooi, Craig W.; Weng, Zhiping; Baker, Brian M.PLoS Computational Biology (2014), 10 (2), e1003478/1-e1003478/11, 11 pp.CODEN: PCBLBG; ISSN:1553-7358. (Public Library of Science)T cell receptors (TCRs) are key to antigen-specific immunity and are increasingly being explored as therapeutics, most visibly in cancer immunotherapy. As TCRs typically possess only low-to-moderate affinity for their peptide/MHC (pMHC) ligands, there is a recognized need to develop affinity-enhanced TCR variants. Previous in vitro engineering efforts have yielded remarkable improvements in TCR affinity, yet concerns exist about the maintenance of peptide specificity and the biol. impacts of ultra-high affinity. As opposed to in vitro engineering, computational design can directly address these issues, in theory permitting the rational control of peptide specificity together with relatively controlled increments in affinity. Here we explored the efficacy of computational design with the clin. relevant TCR DMF5, which recognizes nonameric and decameric epitopes from the melanoma-assocd. Melan-A/MART-1 protein presented by the class I MHC HLA-A2. We tested multiple mutations selected by flexible and rigid modeling protocols, assessed impacts on affinity and specificity, and utilized the data to examine and improve algorithmic performance. We identified multiple mutations that improved binding affinity, and characterized the structure, affinity, and binding kinetics of a previously reported double mutant that exhibits an impressive 400-fold affinity improvement for the decameric pMHC ligand without detectable binding to non-cognate ligands. The structure of this high affinity mutant indicated very little conformational consequences and emphasized the high fidelity of our modeling procedure. Overall, our work showcases the capability of computational design to generate TCRs with improved pMHC affinities while explicitly accounting for peptide specificity, as well as its potential for generating TCRs with customized antigen targeting capabilities.
- 29Haidar, J. N.; Pierce, B.; Yu, Y.; Tong, W.; Li, M.; Weng, Z. Structure-Based Design of a T-Cell Receptor Leads to Nearly 100-Fold Improvement in Binding Affinity for PepMHC. Proteins: Struct., Funct., Bioinf. 2009, 74, 948– 960, DOI: 10.1002/prot.22203Google Scholar29https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXitlGjt7g%253D&md5=455aac53bf93bcb817d5862d5b86dc7eStructure-based design of a T-cell receptor leads to nearly 100-fold improvement in binding affinity for pepMHCHaidar, Jaafar N.; Pierce, Brian; Yu, Yong; Tong, Weiwei; Li, Michael; Weng, ZhipingProteins: Structure, Function, and Bioinformatics (2009), 74 (4), 948-960CODEN: PSFBAF ISSN:. (Wiley-Liss, Inc.)T-cell receptors (TCRs) are proteins that recognize peptides from foreign proteins bound to the major histocompatibility complex (MHC) on the surface of an antigen-presenting cell. This interaction enables the T cells to initiate a cell-mediated immune response to terminate cells displaying the foreign peptide on their MHC. Naturally occurring TCRs have high specificity but low affinity toward the peptide-MHC (pepMHC) complex. This prevents the usage of solubilized TCRs for diagnosis and treatment of viral infections or cancers. Efforts to enhance the binding affinity of several TCRs have been reported in recent years, through randomized libraries and in vitro selection. However, there have been no reported efforts to enhance the affinity via structure-based design, which allows more control and understanding of the mechanism of improvement. Here, we have applied structure-based design to a human TCR to improve its pepMHC binding. Our design method evolved based on iterative steps of prediction, testing, and generating more predictions based on the new data. The final design function, named ZAFFI, has a correlation of 0.77 and av. error of 0.35 kcal/mol with the binding free energies of 26 point mutations for this system that we measured by surface plasmon resonance (SPR). Applying the filter that we developed to remove nonbinding predictions, this correlation increases to 0.85, and the av. error decreases to 0.3 kcal/mol. Using this algorithm, we predicted and tested several point mutations that improved binding, with one giving over sixfold binding improvement. Four of the point mutations that improved binding were then combined to give a mutant TCR that binds the pepMHC 99 times more strongly than the wild-type TCR.
- 30Hellman, L. M.; Foley, K. C.; Singh, N. K.; Alonso, J. A.; Riley, T. P.; Devlin, J. R.; Ayres, C. M.; Keller, G. L. J.; Zhang, Y.; Vander Kooi, C. W.; Nishimura, M. I.; Baker, B. M. Improving T Cell Receptor On-Target Specificity via Structure-Guided Design. Mol. Ther. 2019, 27, 300– 313, DOI: 10.1016/j.ymthe.2018.12.010Google Scholar30https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXis1Wqu78%253D&md5=c8f1f4b0f174f1f5e94b26e3a4c39386Improving T Cell Receptor On-Target Specificity via Structure-Guided DesignHellman, Lance M.; Foley, Kendra C.; Singh, Nishant K.; Alonso, Jesus A.; Riley, Timothy P.; Devlin, Jason R.; Ayres, Cory M.; Keller, Grant L. J.; Zhang, Yuting; Vander Kooi, Craig W.; Nishimura, Michael I.; Baker, Brian M.Molecular Therapy (2019), 27 (2), 300-313CODEN: MTOHCK; ISSN:1525-0024. (Cell Press)T cell receptors (TCRs) have emerged as a new class of immunol. therapeutics. However, though antigen specificity is a hallmark of adaptive immunity, TCRs themselves do not possess the high specificity of monoclonal antibodies. Although a necessary function of T cell biol., the resulting cross-reactivity presents a significant challenge for TCR-based therapeutic development, as it creates the potential for off-target recognition and immune toxicity. Efforts to enhance TCR specificity by mimicking the antibody maturation process and enhancing affinity can inadvertently exacerbate TCR cross-reactivity. Here we demonstrate this concern by showing that even peptide-targeted mutations in the TCR can introduce new reactivities against peptides that bear similarity to the original target. To counteract this, we explored a novel structure-guided approach for enhancing TCR specificity independent of affinity. Tested with the MART-1-specific TCR DMF5, our approach had a small but discernible impact on cross-reactivity toward MART-1 homologs yet was able to eliminate DMF5 cross-recognition of more divergent, unrelated epitopes. Our study provides a proof of principle for the use of advanced structure-guided design techniques for improving TCR specificity, and it suggests new ways forward for enhancing TCRs for therapeutic use.
- 31Chen, J.-L.; Stewart-Jones, G.; Bossi, G.; Lissin, N. M.; Wooldridge, L.; Choi, E. M. L.; Held, G.; Dunbar, P. R.; Esnouf, R. M.; Sami, M.; Boulter, J. M.; Rizkallah, P.; Renner, C.; Sewell, A.; van der Merwe, P. A.; Jakobsen, B. K.; Griffiths, G.; Jones, E. Y.; Cerundolo, V. Structural and Kinetic Basis for Heightened Immunogenicity of T Cell Vaccines. J. Exp. Med. 2005, 201, 1243– 1255, DOI: 10.1084/jem.20042323Google Scholar31https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2MXjs1CitLc%253D&md5=82d72a355878315f2406366379021bf5Structural and kinetic basis for heightened immunogenicity of T cell vaccinesChen, Ji-Li; Stewart-Jones, Guillaume; Bossi, Giovanna; Lissin, Nikolai M.; Wooldridge, Linda; Choi, Ed Man Lik; Held, Gerhard; Dunbar, P. Rod; Esnouf, Robert M.; Sami, Malkit; Boulter, Jonathan M.; Rizkallah, Pierre; Renner, Christoph; Sewell, Andrew; van der Merwe, P. Anton; Jakobsen, Bent K.; Griffiths, Gillian; Jones, E. Yvonne; Cerundolo, VincenzoJournal of Experimental Medicine (2005), 201 (8), 1243-1255CODEN: JEMEAV; ISSN:0022-1007. (Rockefeller University Press)Analog peptides with enhanced binding affinity to major histocompatibility class (MHC) I mols. are currently being used in cancer patients to elicit stronger T cell responses. However, it remains unclear as to how alterations of anchor residues may affect T cell receptor (TCR) recognition. We correlate functional, thermodn., and structural parameters of TCR-peptide-MHC binding and demonstrate the effect of anchor residue modifications of the human histocompatibility leukocyte antigens (HLA)-A2 tumor epitope NY-ESO-1157-165-SLLMWITQC on TCR recognition. The crystal structure of the wild-type peptide complexed with a specific TCR shows that TCR binding centers on two prominent, sequential, peptide side chains, methionine-tryptophan. Cysteine-to-valine substitution at peptide position 9, while optimizing peptide binding to the MHC, repositions the peptide main chain and generates subtly enhanced interactions between the analog peptide and the TCR. Binding analyses confirm tighter binding of the analog peptide to HLA-A2 and improved sol. TCR binding. Recognition of analog peptide stimulates faster polarization of lytic granules to the immunol. synapse, reduces dependence on CD8 binding, and induces greater nos. of cross-reactive cytotoxic T lymphocyte to SLLMWITQC. These results provide important insights into heightened immunogenicity of analog peptides and highlight the importance of incorporating structural data into the process of rational optimization of superagonist peptides for clin. trials.
- 32Garboczi, D. N.; Ghosh, P.; Utz, U.; Fan, Q. R.; Biddison, W. E.; Wiley, D. C. Structure of the Complex between Human T-Cell Receptor, Viral Peptide and HLA-A2. Nature 1996, 384, 134– 141, DOI: 10.1038/384134a0Google Scholar32https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK28XmvFGitbY%253D&md5=813f1d65110a725173c0de9ac803afcaStructure of the complex between human T-cell receptor, viral peptide and HLA-A2Garboczi, David N.; Ghosh, Partho; Utz, Ursula; Fan, Qing R.; Biddison, William E.; Wiley, Don C.Nature (London) (1996), 384 (6605), 134-141CODEN: NATUAS; ISSN:0028-0836. (Macmillan Magazines)Recognition by a T-cell antigen receptor (TCR) of peptide complexed with a major histocompatibility complex (MHC) mol. occurs through variable loops in the TCR structure which bury almost all the available peptide and a much lager area of the MHC mol. The TCR fits diagonally across the MHC peptide-binding site in a surface feature common to all class I and class II MHC mols., providing evidence that the nature of binding is general. A broadly applicable binding mode has implications for the mechanism of repertoire selection and the magnitude of alloreactions.
- 33Cole, D. K.; Sami, M.; Scott, D. R.; Rizkallah, P. J.; Borbulevych, O. Y.; Todorov, P. T.; Moysey, R. K.; Jakobsen, B. K.; Boulter, J. M.; Baker, B. M.; Li, Y.; Yi, Li. Increased Peptide Contacts Govern High Affinity Binding of a Modified TCR Whilst Maintaining a Native PMHC Docking Mode. Front. Immunol. 2013, 4, 168 DOI: 10.3389/fimmu.2013.00168Google Scholar33https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC3sjmtFWlsA%253D%253D&md5=59bcb168675a7cb436908c24f5d57717Increased Peptide Contacts Govern High Affinity Binding of a Modified TCR Whilst Maintaining a Native pMHC Docking ModeCole David K; Sami Malkit; Scott Daniel R; Rizkallah Pierre J; Borbulevych Oleg Y; Todorov Penio T; Moysey Ruth K; Jakobsen Bent K; Boulter Jonathan M; Baker Brian M; Yi LiFrontiers in immunology (2013), 4 (), 168 ISSN:1664-3224.Natural T cell receptors (TCRs) generally bind to their cognate pMHC molecules with weak affinity and fast kinetics, limiting their use as therapeutic agents. Using phage display, we have engineered a high affinity version of the A6 wild-type TCR (A6wt), specific for the human leukocyte antigen (HLA-A(*)0201) complexed with human T cell lymphotropic virus type 111-19 peptide (A2-Tax). Mutations in just 4 residues in the CDR3β loop region of the A6wt TCR were selected that improved binding to A2-Tax by nearly 1000-fold. Biophysical measurements of this mutant TCR (A6c134) demonstrated that the enhanced binding was derived through favorable enthalpy and a slower off-rate. The structure of the free A6c134 TCR and the A6c134/A2-Tax complex revealed a native binding mode, similar to the A6wt/A2-Tax complex. However, concordant with the more favorable binding enthalpy, the A6c134 TCR made increased contacts with the Tax peptide compared with the A6wt/A2-Tax complex, demonstrating a peptide-focused mechanism for the enhanced affinity that directly involved the mutated residues in the A6c134 TCR CDR3β loop. This peptide-focused enhanced TCR binding may represent an important approach for developing antigen specific high affinity TCR reagents for use in T cell based therapies.
- 34Schrödinger. PyMOL Molecular Graphics System (v. 2.1.0); 2018, Schrödinger, LLC.Google ScholarThere is no corresponding record for this reference.
- 35Chen, V. B.; Arendall, W. B.; Headd, J. J.; Keedy, D. A.; Immormino, R. M.; Kapral, G. J.; Murray, L. W.; Richardson, J. S.; Richardson, D. C. MolProbity: All-Atom Structure Validation for Macromolecular Crystallography. Acta Crystallogr., Sect. D: Biol. Crystallogr. 2010, 66, 12– 21, DOI: 10.1107/S0907444909042073Google Scholar35https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXit1Kktg%253D%253D&md5=b5fc7574f43f01dd6e43c3663ca4f779MolProbity: all-atom structure validation for macromolecular crystallographyChen, Vincent B.; Arendall, W. Bryan, III; Headd, Jeffrey J.; Keedy, Daniel A.; Immormino, Robert M.; Kapral, Gary J.; Murray, Laura W.; Richardson, Jane S.; Richardson, David C.Acta Crystallographica, Section D: Biological Crystallography (2010), 66 (1), 12-21CODEN: ABCRE6; ISSN:0907-4449. (International Union of Crystallography)MolProbity is a structure-validation web service that provides broad-spectrum solidly based evaluation of model quality at both the global and local levels for both proteins and nucleic acids. It relies heavily on the power and sensitivity provided by optimized hydrogen placement and all-atom contact anal., complemented by updated versions of covalent-geometry and torsion-angle criteria. Some of the local corrections can be performed automatically in MolProbity and all of the diagnostics are presented in chart and graphical forms that help guide manual rebuilding. X-ray crystallog. provides a wealth of biol. important mol. data in the form of at. three-dimensional structures of proteins, nucleic acids and increasingly large complexes in multiple forms and states. Advances in automation, in everything from crystn. to data collection to phasing to model building to refinement, have made solving a structure using crystallog. easier than ever. However, despite these improvements, local errors that can affect biol. interpretation are widespread at low resoln. and even high-resoln. structures nearly all contain at least a few local errors such as Ramachandran outliers, flipped branched protein side chains and incorrect sugar puckers. It is crit. both for the crystallographer and for the end user that there are easy and reliable methods to diagnose and correct these sorts of errors in structures. MolProbity is the authors' contribution to helping solve this problem and this article reviews its general capabilities, reports on recent enhancements and usage, and presents evidence that the resulting improvements are now beneficially affecting the global database.
- 36Søndergaard, C. R.; Olsson, M. H. M.; Rostkowski, M.; Jensen, J. H. Improved Treatment of Ligands and Coupling Effects in Empirical Calculation and Rationalization of PKa Values. J. Chem. Theory Comput. 2011, 7, 2284– 2295, DOI: 10.1021/ct200133yGoogle Scholar36https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXnt1Gnsrs%253D&md5=cf4d4e20d6daa70de6ac623915e78160Improved Treatment of Ligands and Coupling Effects in Empirical Calculation and Rationalization of pKa ValuesSondergaard, Chresten R.; Olsson, Mats H. M.; Rostkowski, Michal; Jensen, Jan H.Journal of Chemical Theory and Computation (2011), 7 (7), 2284-2295CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The new empirical rules for protein pKa predictions implemented in the PROPKA3.0 software package have been extended to the prediction of pKa shifts of active site residues and ionizable ligand groups in protein-ligand complexes. The authors present new algorithms that allow pKa shifts due to inductive (i.e., covalently coupled) intraligand interactions, as well as noncovalently coupled interligand interactions in multiligand complexes, to be included in the prediction. The no. of different ligand chem. groups that are automatically recognized has been increased to 18, and the general implementation has been changed so that new functional groups can be added easily by the user, aided by a new and more general protonation scheme. Except for a few cases, the new algorithms in PROPKA3.1 are found to yield results similar to or better than those obtained with PROPKA2.0. Finally, the authors present a novel algorithm that identifies noncovalently coupled ionizable groups, where pKa prediction may be esp. difficult. This is a general improvement to PROPKA and is applied to proteins with and without ligands.
- 37Beglov, D.; Roux, B. An Integral Equation To Describe the Solvation of Polar Molecules in Liquid Water. J. Phys. Chem. B 1997, 101, 7821– 7826, DOI: 10.1021/jp971083hGoogle Scholar37https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2sXlslGgt74%253D&md5=400c9449f40638c9a1ea9692b697c9eaIntegral Equation To Describe the Solvation of Polar Molecules in Liquid WaterBeglov, Dmitrii; Roux, BenoitJournal of Physical Chemistry B (1997), 101 (39), 7821-7826CODEN: JPCBFK; ISSN:1089-5647. (American Chemical Society)We developed and implemented a statistical mech. integral equation theory to describe the hydration structure of complex mols. The theory, which is an extension of the ref. interaction site model (RISM) in three dimensions, yields the av. d. from the solvent interactions sites at all points r around a mol. solute of arbitrary shape. Both solute-solvent electrostatic and van der Waals interactions are fully included, and solvent packing is taken into account. The approach is illustrated by calcg. the av. oxygen and hydrogen d. of liq. water around two mol. solutes: water and N-methylacetamide. Mol.-dynamics simulations are performed to test the results obtained from the integral equation. It is obsd. that important microscopic structural features of the av. water d. due to hydrogen bonding are reproduced by the integral equation. The integral equation has a simple formal structure and is easy to implement numerically. It offers a powerful alternative to computer simulations with explicit solvent mols. and to continuum solvent representations for incorporating solvation effects in a wide range of applications.
- 38Kovalenko, A.; Hirata, F. Potential of Mean Force between Two Molecular Ions in a Polar Molecular Solvent: A Study by the Three-Dimensional Reference Interaction Site Model. J. Phys. Chem. B 1999, 103, 7942– 7957, DOI: 10.1021/jp991300+Google Scholar38https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK1MXlsFSrsbk%253D&md5=70620cb15d05198fbb88af00386984acPotential of Mean Force between Two Molecular Ions in a Polar Molecular Solvent: A Study by the Three-Dimensional Reference Interaction Site ModelKovalenko, Andriy; Hirata, FumioJournal of Physical Chemistry B (1999), 103 (37), 7942-7957CODEN: JPCBFK; ISSN:1089-5647. (American Chemical Society)The orientationally dependent potential of mean force (PMF) between two charged polyat. solutes immersed in a polar mol. solvent was obtained by using the three-dimensional ref. interaction site model (3D RISM) of the integral equation theory and partially linearized hypernetted chain (PLHNC) closure. The method was applied to the N,N-dimethylaniline cation (DMA+) and the anthracene anion (AN-) in acetonitrile solvent (CH3CN). We solved the 3D RISM integral equations by employing the modified direct inversion in the iterative subspace (MDIIS) method. The 3D site distributions of solvent around each solute were obtained and discussed. The PMF between the solutes was calcd. as a 3D profile dependent on the relative position of the solutes at six characteristic relative orientations. The PMF obtained is in qual. agreement with the results of mol. dynamics simulations. In the solvent, the AN- solute effectively attracts the DMA+ dimethylamino group and repels its Ph ring. The most stable relative arrangement of the DMA+ and AN- mols. in acetonitrile solvent is different from that in gas phase.
- 39Sindhikara, D. J.; Yoshida, N.; Hirata, F. Placevent: An Algorithm for Prediction of Explicit Solvent Atom Distribution-Application to HIV-1 Protease and F-ATP Synthase. J. Comput. Chem. 2012, 33, 1536– 1543, DOI: 10.1002/jcc.22984Google Scholar39https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XlslyktLk%253D&md5=f80d4c1a0b2c5d87695481674da31814Placevent: An algorithm for prediction of explicit solvent atom distribution - Application to HIV-1 protease and F-ATP synthaseSindhikara, Daniel J.; Yoshida, Norio; Hirata, FumioJournal of Computational Chemistry (2012), 33 (18), 1536-1543CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)We have created a simple algorithm for automatically predicting the explicit solvent atom distribution of biomols. The explicit distribution is coerced from the three-dimensional (3D) continuous distribution resulting from a 3D ref. interaction site model (3D-RISM) calcn. This procedure predicts optimal location of solvent mols. and ions given a rigid biomol. structure and the solvent compn. We show examples of predicting water mols. near the KNI-272 bound form of HIV-1 protease and predicting both sodium ions and water mols. near the rotor ring of F-ATP synthase. Our results give excellent agreement with exptl. structure with an av. prediction error of 0.39-0.65 Å. Further, unlike exptl. methods, this method does not suffer from the partial occupancy limit. Our method can be performed directly on 3D-RISM output within minutes. It is extremely useful for examg. multiple specific solvent-solute interactions, as a convenient method for generating initial solvent structures for mol. dynamics calcns., and may assist in refinement of exptl. structures. © 2012 Wiley Periodicals, Inc.
- 40Case, D. A.; Cerutti, D. S.; Cheatham, T. E., III; Darden, T. A.; Duke, R. E.; Giese, T. J.; Gohlke, H.; Goetz, A. W.; Greene, D.; Homeyer, N.; Izadi, S.; Kovalenko, A.; Lee, T. S.; LeGrand, S.; Li, P.; Lin, C.; Liu, J.; Luchko, T.; Luo, R.; Mermelstein, D.; Merz, K. M.; Monard, G.; Nguyen, H.; Omelyan, I.; Onufriev, A.; Pan, F.; Qi, R.; Roe, D. R.; Roitberg, A.; Sagui, C.; Simmerling, C. L.; Botello-Smith, W. M.; Swails, J.; Walker, R. C.; Wang, J.; Wolf, R. M.; Wu, X.; Xiao, L.; York, D. M.; Kollman, P. A. Amber; University of California: San Francisco, 2016.Google ScholarThere is no corresponding record for this reference.
- 41Maier, J. A.; Martinez, C.; Kasavajhala, K.; Wickstrom, L.; Hauser, K. E.; Simmerling, C. Ff14SB: Improving the Accuracy of Protein Side Chain and Backbone Parameters from Ff99SB. J. Chem. Theory Comput. 2015, 11, 3696– 3713, DOI: 10.1021/acs.jctc.5b00255Google Scholar41https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhtFequ7rN&md5=7b803577b3b6912cc6750cfbd356596eff14SB: Improving the Accuracy of Protein Side Chain and Backbone Parameters from ff99SBMaier, James A.; Martinez, Carmenza; Kasavajhala, Koushik; Wickstrom, Lauren; Hauser, Kevin E.; Simmerling, CarlosJournal of Chemical Theory and Computation (2015), 11 (8), 3696-3713CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)Mol. mechanics is powerful for its speed in atomistic simulations, but an accurate force field is required. The Amber ff99SB force field improved protein secondary structure balance and dynamics from earlier force fields like ff99, but weaknesses in side chain rotamer and backbone secondary structure preferences have been identified. Here, we performed a complete refit of all amino acid side chain dihedral parameters, which had been carried over from ff94. The training set of conformations included multidimensional dihedral scans designed to improve transferability of the parameters. Improvement in all amino acids was obtained as compared to ff99SB. Parameters were also generated for alternate protonation states of ionizable side chains. Av. errors in relative energies of pairs of conformations were under 1.0 kcal/mol as compared to QM, reduced 35% from ff99SB. We also took the opportunity to make empirical adjustments to the protein backbone dihedral parameters as compared to ff99SB. Multiple small adjustments of φ and ψ parameters were tested against NMR scalar coupling data and secondary structure content for short peptides. The best results were obtained from a phys. motivated adjustment to the φ rotational profile that compensates for lack of ff99SB QM training data in the β-ppII transition region. Together, these backbone and side chain modifications (hereafter called ff14SB) not only better reproduced their benchmarks, but also improved secondary structure content in small peptides and reprodn. of NMR χ1 scalar coupling measurements for proteins in soln. We also discuss the Amber ff12SB parameter set, a preliminary version of ff14SB that includes most of its improvements.
- 42Roe, D. R.; Cheatham, T. E. PTRAJ and CPPTRAJ: Software for Processing and Analysis of Molecular Dynamics Trajectory Data. J. Chem. Theory Comput. 2013, 9, 3084– 3095, DOI: 10.1021/ct400341pGoogle Scholar42https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXptFehtr8%253D&md5=6f1bee934f13f180bd7e1feb6b78036dPTRAJ and CPPTRAJ: Software for Processing and Analysis of Molecular Dynamics Trajectory DataRoe, Daniel R.; Cheatham, Thomas E.Journal of Chemical Theory and Computation (2013), 9 (7), 3084-3095CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)We describe PTRAJ and its successor CPPTRAJ, two complementary, portable, and freely available computer programs for the anal. and processing of time series of three-dimensional at. positions (i.e., coordinate trajectories) and the data therein derived. Common tools include the ability to manipulate the data to convert among trajectory formats, process groups of trajectories generated with ensemble methods (e.g., replica exchange mol. dynamics), image with periodic boundary conditions, create av. structures, strip subsets of the system, and perform calcns. such as RMS fitting, measuring distances, B-factors, radii of gyration, radial distribution functions, and time correlations, among other actions and analyses. Both the PTRAJ and CPPTRAJ programs and source code are freely available under the GNU General Public License version 3 and are currently distributed within the AmberTools 12 suite of support programs that make up part of the Amber package of computer programs (see http://ambermd.org). This overview describes the general design, features, and history of these two programs, as well as algorithmic improvements and new features available in CPPTRAJ.
- 43Nguyen, H.; Roe, D. R.; Simmerling, C. Improved Generalized Born Solvent Model Parameters for Protein Simulations. J. Chem. Theory Comput. 2013, 9, 2020– 2034, DOI: 10.1021/ct3010485Google Scholar43https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXjsFaqs7c%253D&md5=1d674f02a81c7c2f0da0715aa657a89dImproved Generalized Born Solvent Model Parameters for Protein SimulationsNguyen, Hai; Roe, Daniel R.; Simmerling, CarlosJournal of Chemical Theory and Computation (2013), 9 (4), 2020-2034CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The generalized Born (GB) model is one of the fastest implicit solvent models, and it has become widely adopted for Mol. Dynamics (MD) simulations. This speed comes with trade-offs, and many reports in the literature have pointed out weaknesses with GB models. Because the quality of a GB model is heavily affected by empirical parameters used in calcg. solvation energy, in this work we have refit these parameters for GB-Neck, a recently developed GB model, in order to improve the accuracy of both the solvation energy and effective radii calcns. The data sets used for fitting are significantly larger than those used in the past. Comparing to other pairwise GB models like GB-OBC and the original GB-Neck, the new GB model (GB-Neck2) has better agreement with Poisson-Boltzmann (PB) in terms of reproducing solvation energies for a variety of systems ranging from peptides to proteins. Secondary structure preferences are also in much better agreement with those obtained from explicit solvent MD simulations. We also obtain near-quant. reprodn. of exptl. structure and thermal stability profiles for several model peptides with varying secondary structure motifs. Extension to nonprotein systems will be explored in the future.
- 44Duan, L.; Liu, X.; Zhang, J. Z. H. Interaction Entropy: A New Paradigm for Highly Efficient and Reliable Computation of Protein-Ligand Binding Free Energy. J. Am. Chem. Soc. 2016, 138, 5722– 5728, DOI: 10.1021/jacs.6b02682Google Scholar44https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28Xls1Kjuro%253D&md5=696a28a2660cc96dcd51d81a505923ddInteraction Entropy: A New Paradigm for Highly Efficient and Reliable Computation of Protein-Ligand Binding Free EnergyDuan, Lili; Liu, Xiao; Zhang, John Z. H.Journal of the American Chemical Society (2016), 138 (17), 5722-5728CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)Efficient and reliable calcn. of protein-ligand binding free energy is a grand challenge in computational biol. and is of crit. importance in drug design and many other mol. recognition problems. The main challenge lies in the calcn. of entropic contribution to protein-ligand binding or interaction systems. In this report, we present a new interaction entropy method which is theor. rigorous, computationally efficient, and numerically reliable for calcg. entropic contribution to free energy in protein-ligand binding and other interaction processes. Drastically different from the widely employed but extremely expensive normal mode method for calcg. entropy change in protein-ligand binding, the new method calcs. the entropic component (interaction entropy or -TΔS) of the binding free energy directly from mol. dynamics simulation without any extra computational cost. Extensive study of over a dozen randomly selected protein-ligand binding systems demonstrated that this interaction entropy method is both computationally efficient and numerically reliable and is vastly superior to the std. normal mode approach. This interaction entropy paradigm introduces a novel and intuitive conceptual understanding of the entropic effect in protein-ligand binding and other general interaction systems as well as a practical method for highly efficient calcn. of this effect.
- 45Kongsted, J.; Ryde, U. An Improved Method to Predict the Entropy Term with the MM/PBSA Approach. J. Comput.-Aided Mol. Des. 2009, 23, 63– 71, DOI: 10.1007/s10822-008-9238-zGoogle Scholar45https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXmtFGn&md5=770f5b34c7c279e0944f81b83d8b3170An improved method to predict the entropy term with the MM/PBSA approachKongsted, Jacob; Ryde, UlfJournal of Computer-Aided Molecular Design (2009), 23 (2), 63-71CODEN: JCADEQ; ISSN:0920-654X. (Springer)A method is suggested to calc. improved entropies within the MM/PBSA approach (mol. mechanics combined with Poisson-Boltzmann and surface area calcns.) to est. protein-ligand binding affinities. In the conventional approach, the protein is truncated outside ∼8 Å from the ligand. This system is freely minimized using a distance-dependent dielec. const. (to simulate the removed protein and solvent). However, this can lead to extensive changes in the mol. geometry, giving rise to a large std. deviation in this term. In our new approach, we introduce a buffer region ∼4 Å outside the truncated protein (including solvent mols.) and keep it fixed during the minimization. Thereby, we reduce the std. deviation by a factor of 2-4, ensuring that the entropy term no longer limits the precision of the MM/PBSA predictions. The new method is tested for the binding of seven biotin analogs to avidin, eight amidinobenzyl-indole-carboxamide inhibitors to factor Xa, and two substrates to cytochrome P 450 3A4 and 2C9. It is shown that it gives more stable results and often improved predictions of the relative binding affinities.
- 46Dunn, S. M.; Rizkallah, P. J.; Baston, E.; Mahon, T.; Cameron, B.; Moysey, R.; Gao, F.; Sami, M.; Boulter, J.; Li, Y.; Jakobsen, B. K. Directed Evolution of Human T Cell Receptor CDR2 Residues by Phage Display Dramatically Enhances Affinity for Cognate Peptide-MHC without Increasing Apparent Cross-Reactivity. Protein Sci. 2006, 15, 710– 721, DOI: 10.1110/ps.051936406Google Scholar46https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28XjsFCqsb0%253D&md5=669fe7d2739b669e8bce45ff0a89ab9dDirected evolution of human T cell receptor CDR2 residues by phage display dramatically enhances affinity for cognate peptide-MHC without increasing apparent cross-reactivityDunn, Steven M.; Rizkallah, Pierre J.; Baston, Emma; Mahon, Tara; Cameron, Brian; Moysey, Ruth; Gao, Feng; Sami, Malkit; Boulter, Jonathan; Li, Yi; Jakobsen, Bent K.Protein Science (2006), 15 (4), 710-721CODEN: PRCIEI; ISSN:0961-8368. (Cold Spring Harbor Laboratory Press)The mammalian α/β T cell receptor (TCR) repertoire plays a pivotal role in adaptive immunity by recognizing short, processed, peptide antigens bound in the context of a highly diverse family of cell-surface major histocompatibility complexes (pMHCs). Despite the extensive TCR-MHC interaction surface, peptide-independent cross-reactivity of native TCRs is generally avoided through cell-mediated selection of mols. with low inherent affinity for MHC. Here we show that, contrary to expectations, the germ line-encoded complementarity detg. regions (CDRs) of human TCRs, namely the CDR2s, which appear to contact only the MHC surface and not the bound peptide, can be engineered to yield sol. low nanomolar affinity ligands that retain a surprisingly high degree of specificity for the cognate pMHC target. Structural investigation of one such CDR2 mutant implicates shape complementarity of the mutant CDR2 contact interfaces as being a key determinant of the increased affinity. Our results suggest that manipulation of germ line CDR2 loops may provide a useful route to the prodn. of high-affinity TCRs with therapeutic and diagnostic potential.
- 47Wan, S.; Knapp, B.; Wright, D. W.; Deane, C. M.; Coveney, P. V. Rapid, Precise, and Reproducible Prediction of Peptide-MHC Binding Affinities from Molecular Dynamics That Correlate Well with Experiment. J. Chem. Theory Comput. 2015, 11, 3346– 3356, DOI: 10.1021/acs.jctc.5b00179Google Scholar47https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhtVaksLjN&md5=860aa35a6e8e4013e2b0c7f0ae99170fRapid, precise, and reproducible prediction of peptide-MHC binding affinities from molecular dynamics that correlate well with experimentWan, Shunzhou; Knapp, Bernhard; Wright, David W.; Deane, Charlotte M.; Coveney, Peter V.Journal of Chemical Theory and Computation (2015), 11 (7), 3346-3356CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The presentation of potentially pathogenic peptides by major histocompatibility complex (MHC) mols. is one of the most important processes in adaptive immune defense. Prediction of peptide-MHC (pMHC) binding affinities is therefore a principal objective of theor. immunol. Machine learning techniques achieve good results if substantial exptl. training data are available. Approaches based on structural information become necessary if sufficiently similar training data are unavailable for a specific MHC allele, although they have often been deemed to lack accuracy. In this study, we use a free energy method to rank the binding affinities of 12 diverse peptides bound by a class I MHC mol. HLA-A*02:01. The method is based on enhanced sampling of mol. dynamics calcns. in combination with a continuum solvent approxn. and includes ests. of the configurational entropy based on either a one or a three trajectory protocol. It produces precise and reproducible free energy ests. which correlate well with exptl. measurements. If the results are combined with an amino acid hydrophobicity scale, then an extremely good ranking of peptide binding affinities emerges. Our approach is rapid, robust, and applicable to a wide range of ligand-receptor interactions without further adjustment.
- 48Wright, D. W.; Hall, B. A.; Kenway, O. A.; Jha, S.; Coveney, P. V. Computing Clinically Relevant Binding Free Energies of HIV-1 Protease Inhibitors. J. Chem. Theory Comput. 2014, 10, 1228– 1241, DOI: 10.1021/ct4007037Google Scholar48https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXht12ltrk%253D&md5=56bc7e7c8f6bbdd694bfc76c20dcec63Computing Clinically Relevant Binding Free Energies of HIV-1 Protease InhibitorsWright, David W.; Hall, Benjamin A.; Kenway, Owain A.; Jha, Shantenu; Coveney, Peter V.Journal of Chemical Theory and Computation (2014), 10 (3), 1228-1241CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The use of mol. simulation to est. the strength of macromol. binding free energies is becoming increasingly widespread, with goals ranging from lead optimization and enrichment in drug discovery to personalizing or stratifying treatment regimes. To realize the potential of such approaches to predict new results, not merely to explain previous exptl. findings, it is necessary that the methods used are reliable and accurate, and that their limitations are thoroughly understood. However, the computational cost of atomistic simulation techniques such as mol. dynamics (MD) has meant that until recently little work has focused on validating and verifying the available free energy methodologies, with the consequence that many of the results published in the literature are not reproducible. Here, we present a detailed anal. of two of the most popular approx. methods for calcg. binding free energies from mol. simulations, mol. mechanics Poisson-Boltzmann surface area (MMPBSA) and mol. mechanics generalized Born surface area (MMGBSA), applied to the nine FDA-approved HIV-1 protease inhibitors. Our results show that the values obtained from replica simulations of the same protease-drug complex, differing only in initially assigned atom velocities, can vary by as much as 10 kcal mol-1, which is greater than the difference between the best and worst binding inhibitors under investigation. Despite this, anal. of ensembles of simulations producing 50 trajectories of 4 ns duration leads to well converged free energy ests. For seven inhibitors, we find that with correctly converged normal mode ests. of the configurational entropy, we can correctly distinguish inhibitors in agreement with exptl. data for both the MMPBSA and MMGBSA methods and thus have the ability to rank the efficacy of binding of this selection of drugs to the protease (no account is made for free energy penalties assocd. with protein distortion leading to the over estn. of the binding strength of the two largest inhibitors ritonavir and atazanavir). We obtain improved rankings and ests. of the relative binding strengths of the drugs by using a novel combination of MMPBSA/MMGBSA with normal mode entropy ests. and the free energy of assocn. calcd. directly from simulation trajectories. Our work provides a thorough assessment of what is required to produce converged and hence reliable free energies for protein-ligand binding.
- 49Genheden, S.; Ryde, U. How to Obtain Statistically Converged MM/GBSA Results. J. Comput. Chem. 2009, 31, 837– 846, DOI: 10.1002/jcc.21366Google ScholarThere is no corresponding record for this reference.
- 50Wan, S.; Bhati, A. P.; Zasada, S. J.; Wall, I.; Green, D.; Bamborough, P.; Coveney, P. V. Rapid and Reliable Binding Affinity Prediction of Bromodomain Inhibitors: A Computational Study. J. Chem. Theory Comput. 2017, 13, 784– 795, DOI: 10.1021/acs.jctc.6b00794Google Scholar50https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XitFektLnF&md5=713436084662420482684fb50db0832eRapid and Reliable Binding Affinity Prediction of Bromodomain Inhibitors: A Computational StudyWan, Shunzhou; Bhati, Agastya P.; Zasada, Stefan J.; Wall, Ian; Green, Darren; Bamborough, Paul; Coveney, Peter V.Journal of Chemical Theory and Computation (2017), 13 (2), 784-795CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)Binding free energies of bromodomain inhibitors are calcd. with recently formulated approaches, namely ESMACS (enhanced sampling of mol. dynamics with approxn. of continuum solvent) and TIES (thermodn. integration with enhanced sampling). A set of compds. is provided by GlaxoSmithKline, which represents a range of chem. functionality and binding affinities. The predicted binding free energies exhibit a good Spearman correlation of 0.78 with the exptl. data from the 3-trajectory ESMACS, and an excellent correlation of 0.92 from the TIES approach where applicable. Given access to suitable high end computing resources and a high degree of automation, the authors can compute individual binding affinities in a few hours with precisions no greater than 0.2 kcal/mol for TIES, and no larger than 0.34 kcal/mol and 1.71 kcal/mol for the 1- and 3-trajectory ESMACS approaches.
- 51Chen, F.; Liu, H.; Sun, H.; Pan, P.; Li, Y.; Li, D.; Hou, T. Assessing the Performance of the MM/PBSA and MM/GBSA Methods. 6. Capability to Predict Protein–Protein Binding Free Energies and Re-Rank Binding Poses Generated by Protein–Protein Docking. Phys. Chem. Chem. Phys. 2016, 18, 22129– 22139, DOI: 10.1039/C6CP03670HGoogle Scholar51https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XhtFKktbvP&md5=ad3658a355db86f1e7cd46f196e7f76eAssessing the performance of the MM/PBSA and MM/GBSA methods. 6. Capability to predict protein-protein binding free energies and re-rank binding poses generated by protein-protein dockingChen, Fu; Liu, Hui; Sun, Huiyong; Pan, Peichen; Li, Youyong; Li, Dan; Hou, TingjunPhysical Chemistry Chemical Physics (2016), 18 (32), 22129-22139CODEN: PPCPFQ; ISSN:1463-9076. (Royal Society of Chemistry)Understanding protein-protein interactions (PPIs) is quite important to elucidate crucial biol. processes and even design compds. that interfere with PPIs with pharmaceutical significance. Protein-protein docking can afford the at. structural details of protein-protein complexes, but the accurate prediction of the three-dimensional structures for protein-protein systems is still notoriously difficult due in part to the lack of an ideal scoring function for protein-protein docking. Compared with most scoring functions used in protein-protein docking, the Mol. Mechanics/Generalized Born Surface Area (MM/GBSA) and Mol. Mechanics/Poisson Boltzmann Surface Area (MM/PBSA) methodologies are more theor. rigorous, but their overall performance for the predictions of binding affinities and binding poses for protein-protein systems has not been systematically evaluated. In this study, we first evaluated the performance of MM/PBSA and MM/GBSA to predict the binding affinities for 46 protein-protein complexes. On the whole, different force fields, solvation models, and interior dielec. consts. have obvious impacts on the prediction accuracy of MM/GBSA and MM/PBSA. The MM/GBSA calcns. based on the ff02 force field, the GB model developed by Onufriev et al. and a low interior dielec. const. (εin = 1) yield the best correlation between the predicted binding affinities and the exptl. data (rp = -0.647), which is better than MM/PBSA (rp = -0.523) and a no. of empirical scoring functions used in protein-protein docking (rp = -0.141 to -0.529). Then, we examd. the capability of MM/GBSA to identify the possible near-native binding structures from the decoys generated by ZDOCK for 43 protein-protein systems. The results illustrate that the MM/GBSA rescoring has better capability to distinguish the correct binding structures from the decoys than the ZDOCK scoring. Besides, the optimal interior dielec. const. of MM/GBSA for re-ranking docking poses may be detd. by analyzing the characteristics of protein-protein binding interfaces. Considering the relatively high prediction accuracy and low computational cost, MM/GBSA may be a good choice for predicting the binding affinities and identifying correct binding structures for protein-protein systems.
- 52Sun, H.; Li, Y.; Shen, M.; Tian, S.; Xu, L.; Pan, P.; Guan, Y.; Hou, T. Assessing the Performance of MM/PBSA and MM/GBSA Methods. 5. Improved Docking Performance Using High Solute Dielectric Constant MM/GBSA and MM/PBSA Rescoring. Phys. Chem. Chem. Phys. 2014, 16, 22035– 22045, DOI: 10.1039/C4CP03179BGoogle Scholar52https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhtlOjsbfJ&md5=3cf9751ee3c05dd7aa6fa27f591fba9eAssessing the performance of MM/PBSA and MM/GBSA methods. 5. Improved docking performance using high solute dielectric constant MM/GBSA and MM/PBSA rescoringSun, Huiyong; Li, Youyong; Shen, Mingyun; Tian, Sheng; Xu, Lei; Pan, Peichen; Guan, Yan; Hou, TingjunPhysical Chemistry Chemical Physics (2014), 16 (40), 22035-22045CODEN: PPCPFQ; ISSN:1463-9076. (Royal Society of Chemistry)With the rapid development of computational techniques and hardware, more rigorous and precise theor. models have been used to predict the binding affinities of a large no. of small mols. to biomols. By employing continuum solvation models, the MM/GBSA and MM/PBSA methodologies achieve a good balance between low computational cost and reasonable prediction accuracy. The authors have thoroughly studied the effects of interior dielec. const., mol. dynamics (MD) simulations, and the no. of top-scored docking poses on the performance of the MM/GBSA and MM/PBSA rescoring of docking poses for three tyrosine kinases, including ABL, ALK, and BRAF. Overall, the MM/PBSA and MM/GBSA rescoring achieved comparative accuracies based on a relatively higher solute (or interior) dielec. const. (i.e. ε = 2, or 4), and could markedly improve the screening power and ranking power given by Autodock. Moreover, with a relatively higher solute dielec. const., the MM/PBSA or MM/GBSA rescoring based on the best scored docking poses and the multiple top-scored docking poses gave similar predictions, implying that much computational cost can be saved by considering the best scored docking poses only. Besides, compared with the rescoring based on the minimized structures, the rescoring based on the MD simulations might not be completely necessary due to its negligible impact on the docking performance. Considering the much higher computational demand of MM/PBSA, MM/GBSA with a high solute dielec. const. (ε = 2 or 4) is recommended for the virtual screening of tyrosine kinases.
- 53Wang, C.; Nguyen, P. H.; Pham, K.; Huynh, D.; Le, T. B. N.; Wang, H.; Ren, P.; Luo, R. Calculating Protein–Ligand Binding Affinities with MMPBSA: Method and Error Analysis. J. Comput. Chem. 2016, 2436– 2446, DOI: 10.1002/jcc.24467Google Scholar53https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28Xhtlalsb3L&md5=a8131b248b24f7f8d1285c4867c39b07Calculating protein-ligand binding affinities with MMPBSA: Method and error analysisWang, Changhao; Nguyen, Peter H.; Pham, Kevin; Huynh, Danielle; Le, Thanh-Binh Nancy; Wang, Hongli; Ren, Pengyu; Luo, RayJournal of Computational Chemistry (2016), 37 (27), 2436-2446CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)Mol. Mechanics Poisson-Boltzmann Surface Area (MMPBSA) methods have become widely adopted in estg. protein-ligand binding affinities due to their efficiency and high correlation with expt. Here different computational alternatives were studied to assess their impact to the agreement of MMPBSA calcns. with expt. Seven receptor families with both high-quality crystal structures and binding affinities were selected. First the performance of nonpolar solvation models was studied and the modern approach that sep. models hydrophobic and dispersion interactions dramatically reduces RMSD's of computed relative binding affinities. The numerical setup of the Poisson-Boltzmann methods was analyzed next. The impact of grid spacing to the quality of MMPBSA calcns. is small: the numerical error at the grid spacing of 0.5 Å is already small enough to be negligible. The impact of different at. radius sets and different mol. surface definitions was further analyzed and weak influences were found on the agreement with expt. The influence of solute dielec. const. was also analyzed: a higher dielec. const. generally improves the overall agreement with expt., esp. for highly charged binding pockets. Also the converged simulations caused slight redn. in the agreement with expt. Finally the direction of estg. abs. binding free energies was briefly explored. Upon correction of the binding-induced rearrangement free energy and the binding entropy lost, the errors in abs. binding affinities were also reduced dramatically when the modern nonpolar solvent model was used, although further developments were apparently necessary to further improve the MMPBSA methods. © 2016 Wiley Periodicals, Inc.
- 54Liu, X.; Peng, L.; Zhou, Y.; Zhang, Y.; Zhang, J. Z. H. Computational Alanine Scanning with Interaction Entropy for Protein–Ligand Binding Free Energies. J. Chem. Theory Comput. 2018, 14, 1772– 1780, DOI: 10.1021/acs.jctc.7b01295Google Scholar54https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXit1ykur8%253D&md5=c808e0f9bf3d32fc8ce9ddade1300048Computational Alanine Scanning with Interaction Entropy for Protein-Ligand Binding Free EnergiesLiu, Xiao; Peng, Long; Zhou, Yifan; Zhang, Youzhi; Zhang, John Z. H.Journal of Chemical Theory and Computation (2018), 14 (3), 1772-1780CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)In protein-ligand binding, only a few residues contribute significantly to the ligand binding. Quant. characterization of binding free energies of specific residues in protein-ligand binding is extremely useful in our understanding of drug resistance and rational drug design. Here, we present an alanine scanning approach combined with an efficient interaction entropy method to compute residue-specific protein-ligand binding free energies in protein-drug binding. In the current approach, the entropic components in the free energies of all residues binding to the ligand are explicitly computed from just a single trajectory mol. dynamics (MD) simulation by using the interaction entropy method. In this approach the entropic contribution to binding free energy is detd. from fluctuations of individual residue-ligand interaction energies contained in the MD trajectory. The calcd. residue-specific binding free energies give relative values between those for ligand binding to the wild-type protein and those to the mutants when specific results mutated to alanine. Computational study for the binding of 2 classes of drugs (1st and 2nd generation drugs) to the target protein, anaplastic leukemia kinase (ALK) and its mutants was performed. Important or hot spot residues with large contributions to the total binding energy were quant. characterized and the mutational effect for the loss of binding affinity for the 1st-generation drug was explained. Finally, it is very interesting to note that the sum of those individual residue-specific binding free energies were in quite good agreement with the exptl. measured total binding free energies for this protein-ligand system.
- 55Vangone, A.; Spinelli, R.; Scarano, V.; Cavallo, L.; Oliva, R. COCOMAPS: A Web Application to Analyze and Visualize Contacts at the Interface of Biomolecular Complexes. Bioinformatics 2011, 27, 2915– 2916, DOI: 10.1093/bioinformatics/btr484Google Scholar55https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXht12qsLvL&md5=67683342e85e9f5ae9637ac55bbe7dcbCOCOMAPS: a web application to analyze and visualize contacts at the interface of biomolecular complexesVangone, Anna; Spinelli, Raffaele; Scarano, Vittorio; Cavallo, Luigi; Oliva, RominaBioinformatics (2011), 27 (20), 2915-2916CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)Summary: Herein we present COCOMAPS, a novel tool for analyzing, visualizing and comparing the interface in protein-protein and protein-nucleic acids complexes. COCOMAPS combines traditional analyses and 3D visualization of the interface with the effectiveness of intermol. contact maps. Availability: COCOMAPS is accessible as a public web tool at http://www.molnac.unisa.it/BioTools/cocomaps Contact: [email protected]; [email protected].
- 56Ramos, R. M.; Moreira, I. S. Computational Alanine Scanning Mutagenesis─An Improved Methodological Approach for Protein–DNA Complexes. J. Chem. Theory Comput. 2013, 9, 4243– 4256, DOI: 10.1021/ct400387rGoogle Scholar56https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXht1Wis73K&md5=8b15ee28b995791e18447c2005d2ce8bComputational Alanine Scanning Mutagenesis-An Improved Methodological Approach for Protein-DNA ComplexesRamos, Rui M.; Moreira, Irina S.Journal of Chemical Theory and Computation (2013), 9 (9), 4243-4256CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)Proteins and protein-based complexes are the basis of many key systems in nature and have been the subject of intense research in the last decades, in an attempt to acquire comprehensive knowledge of reactions that take place in nature. Computational Alanine Scanning Mutagenesis approaches have been extensively used in the study of protein interfaces and in the detn. of the most important residues for complex formation, the Hot-spots. However, as it is usually applied to the study of protein-protein interfaces, the authors tried to modify and apply it to the study of protein-DNA interfaces, which are also crucial in nature but have not been the subject of as much research. The authors carry out MD simulations of seven protein-DNA complexes and tested the influence of the variation of different parameters on the detn. of the binding free energy terms (ΔΔGbinding) of 78 mutations: solvent representation, internal dielec. const., Linear and Nonlinear Poisson-Boltzmann equation, Generalized Born model, simulation time, no. of structures analyzed, no. of MD trajectories, force field used, and energetic terms involved. Overall, this new approach gave an av. error of 1.55 kcal/mol, and P, R, F1, accuracy, and specificity values of 0.78, 0.50, 0.61, 0.77, and 0.92, resp. This improved computational alanine scanning mutagenesis approach may serve as a tool to explore the behavior of this important class of complexes.
- 57Moreira, I. S.; Fernandes, P. A.; Ramos, M. J. Computational Alanine Scanning Mutagenesis─An Improved Methodological Approach. J. Comput. Chem. 2007, 28, 644– 654, DOI: 10.1002/jcc.20566Google Scholar57https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXhsVWntb8%253D&md5=54074b0d0d9b0a28744f3d27697a266cComputational alanine scanning mutagenesis - an improved methodological approachMoreira, Irina S.; Fernandes, Pedro A.; Ramos, Maria J.Journal of Computational Chemistry (2007), 28 (3), 644-654CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)Alanine scanning mutagenesis of protein-protein interfacial residues can be applied to a wide variety of protein complexes to understand the structural and energetic characteristics of the hot-spots. Binding free energies have been estd. with reasonable accuracy with empirical methods, such as Mol. Mechanics/Poisson-Boltzmann surface area (MM-PBSA), and with more rigorous computational approaches like Free Energy Perturbation (FEP) and Thermodn. Integration (TI). The main objective of this work is the development of an improved methodol. approach, with less computational cost, that predicts accurately differences in binding free energies between the wild-type and alanine mutated complexes (ΔΔGbinding). The method was applied to three complexes, and a mean unsigned error of 0.80 kcal/mol was obtained in a set of 46 mutations. The computational method presented here achieved an overall success rate of 80% and an 82% success rate in residues for which alanine mutation causes an increase in the binding free energy > 2.0 kcal/mol (warm- and hot-spots). This fully atomistic computational methodol. approach consists in a computational Mol. Dynamics simulation protocol performed in a continuum medium using the Generalized Born model. A set of three different internal dielec. consts., to mimic the different degree of relaxation of the interface when different types of amino acids are mutated for alanine, have to be used for the proteins, depending on the type of amino acid that is mutated. This method permits a systematic scanning mutagenesis of protein-protein interfaces and it is capable of anticipating the exptl. results of mutagenesis, thus guiding new exptl. investigations.
- 58Martins, S. A.; Perez, M. A. S.; Moreira, I. S.; Sousa, S. F.; Ramos, M. J.; Fernandes, P. A. Computational Alanine Scanning Mutagenesis: MM-PBSA vs TI. J. Chem. Theory Comput. 2013, 9, 1311– 1319, DOI: 10.1021/ct4000372Google Scholar58https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXitlCiurs%253D&md5=8a790e3a8bce51eeb33993d7c84c2112Computational Alanine Scanning Mutagenesis: MM-PBSA vs TIMartins, Silvia A.; Perez, Marta A. S.; Moreira, Irina S.; Sousa, Sergio F.; Ramos, M. J.; Fernandes, P. A.Journal of Chemical Theory and Computation (2013), 9 (3), 1311-1319CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)Understanding protein-protein assocn. and being able to det. the crucial residues responsible for their assocn. (hot-spots) is a key issue with huge practical applications such as rational drug design and protein engineering. A variety of computational methods exist to detect hot-spots residues, but the development of a fast and accurate quant. alanine scanning mutagenesis (ASM) continues to be crucial. Using four protein-protein complexes, we have compared a variation of the std. computational ASM protocol developed at our group, based on the Mol. Mechanics/Poisson-Boltzmann Surface Area (MM-PBSA) approach, against Thermodn. Integration (TI), a well-known and accurate but computationally expensive method. To compare the efficiency and the accuracy of the two methods, we have calcd. the protein-protein binding free energy differences upon alanine mutation of interfacial residues (ΔΔGbind). In relation to the exptl. ΔΔGbind values, the av. error obtained with TI was 1.53 kcal/mol, while the ASM protocol resulted in an av. error of 1.18 kcal/mol. The results demonstrate that the much faster ASM protocol gives results at the same level of accuracy as the TI method but at a fraction of the computational time required to run TI. This ASM protocol is therefore a strong and efficient alternative to the systematic evaluation of protein-protein interfaces, involving hundreds of amino acid residues in search of hot-spots.
- 59Simões, I. C. M.; Costa, I. P. D.; Coimbra, J. T. S.; Ramos, M. J.; Fernandes, P. A. New Parameters for Higher Accuracy in the Computation of Binding Free Energy Differences upon Alanine Scanning Mutagenesis on Protein-Protein Interfaces. J. Chem. Inf. Model. 2017, 57, 60– 72, DOI: 10.1021/acs.jcim.6b00378Google Scholar59https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XitVKqtLzM&md5=5faedefbb4899a041a0c3e7a350709ddNew Parameters for Higher Accuracy in the Computation of Binding Free Energy Differences upon Alanine Scanning Mutagenesis on Protein-Protein InterfacesSimoes, Ines C. M.; Costa, Ines P. D.; Coimbra, Joao T. S.; Ramos, Maria J.; Fernandes, Pedro A.Journal of Chemical Information and Modeling (2017), 57 (1), 60-72CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)Knowing how proteins make stable complexes enables the development of inhibitors to preclude protein-protein (P:P) binding. The identification of the specific interfacial residues that contribute the most for protein binding, denominated as hot-spots, is thus crit. Here the authors refine a computational alanine scanning mutagenesis protocol, based on a residue-dependent dielec. const. version of the Mol. Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) method. The authors used a large data set of structurally diverse P:P complexes to re-define the residue-dependent dielec. consts. used in the calcn. of binding free energies. The accuracy of the method was validated through comparison with exptl. data, considering the per-residue P:P binding free energy (ΔΔGbinding) differences upon alanine mutation. Different protocols were tested, i.e. a geometry optimization protocol and three mol. dynamics (MD) protocols: (1) one using explicit water mols., (2) another with an implicit solvation model, and (3) a third where the authors have carried out an accelerated MD with explicit water mols. Using a set of protein dielec. consts. (within the range of 1 to 20) the dielec. consts. of 7 for non-polar and polar residues and 11 for charged residues (and histidine) provide optimal ΔΔGbinding predictions. An overall mean unsigned error (MUE) of 1.4 kcal.mol-1 relative to expt. was achieved in 210 mutations only with geometry optimization, which was further reduced with MD simulations (MUE of 1.1 kcal.mol-1 for the explicit solvent MD). This recalibrated method allows for a better computational identification of hot-spots, avoiding expensive and time-consuming expts. or thermodn. integration/ free energy perturbation/ uBAR calcns., and will hopefully help new drug discovery campaigns in their quest of searching spots of interest for binding small drug-like mols. at P:P interfaces.
- 60Sheng, Y.; Yin, Y.; Ma, Y.; Ding, H. Improving the Performance of MM/PBSA in Protein–Protein Interactions via the Screening Electrostatic Energy. J. Chem. Inf. Model. 2021, 61, 2454– 2462, DOI: 10.1021/acs.jcim.1c00410Google Scholar60https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3MXpvFKnsrs%253D&md5=7532ed49ab5f2d8cf8b03aac1f73b199Improving the Performance of MM/PBSA in Protein-Protein Interactions via the Screening Electrostatic EnergySheng, Yan-jing; Yin, Yue-wen; Ma, Yu-qiang; Ding, Hong-mingJournal of Chemical Information and Modeling (2021), 61 (5), 2454-2462CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)Accurate calcn. of protein-protein binding free energy is of great importance in biol. and medical science, yet it remains a hugely challenging problem. In this work, we develop a new strategy in which a screened electrostatic energy (i.e., adding an exponential damping factor to the Coulombic interaction energy) is used within the framework of the mol. mechanics/Poisson-Boltzmann surface area (MM/PBSA) method. Our results show that the Pearson correlation coeff. in the modified MM/PBSA is over 0.70, which is much better than that in the std. MM/PBSA, esp. in the Amber14SB force field. In particular, the performance of the std. MM/PBSA is very poor in a system where the proteins carry like charges. Moreover, we also calcd. the mean abs. error (MAE) between the calcd. and exptl. ΔG values and found that the MAE in the modified MM/PBSA was indeed much smaller than that in the std. MM/PBSA. Furthermore, the effect of the dielec. const. of the proteins and the salt conditions on the results was also investigated. The present study highlights the potential power of the modified MM/PBSA for accurately predicting the binding energy in highly charged biosystems.
- 61Pierce, B. G.; Weng, Z. A Flexible Docking Approach for Prediction of T Cell Receptor-Peptide-MHC Complexes. Protein Sci. 2013, 22, 35– 46, DOI: 10.1002/pro.2181Google Scholar61https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhvVeksrjE&md5=300f9098326bcc6d5e1e8a660f5160ddA flexible docking approach for prediction of T cell receptor-peptide-MHC complexesPierce, Brian G.; Weng, ZhipingProtein Science (2013), 22 (1), 35-46CODEN: PRCIEI; ISSN:1469-896X. (Wiley-Blackwell)T cell receptors (TCRs) are immune proteins that specifically bind to antigenic mols., which are often foreign peptides presented by major histocompatibility complex proteins (pMHCs), playing a key role in the cellular immune response. To advance our understanding and modeling of this dynamic immunol. event, we assembled a protein-protein docking benchmark consisting of 20 structures of crystd. TCR/pMHC complexes for which unbound structures exist for both TCR and pMHC. We used our benchmark to compare predictive performance using several flexible and rigid backbone TCR/pMHC docking protocols. Our flexible TCR docking algorithm, TCRFlexDock, improved predictive success over the fixed backbone protocol, leading to near-native predictions for 80% of the TCR/pMHC cases among the top 10 models, and 100% of the cases in the top 30 models. We then applied TCRFlexDock to predict the two distinct docking modes recently described for a single TCR bound to two different antigens, and tested several protein modeling scoring functions for prediction of TCR/pMHC binding affinities. This algorithm and benchmark should enable future efforts to predict, and design of uncharacterized TCR/pMHC complexes.
- 62Jensen, K. K.; Rantos, V.; Jappe, E. C.; Olsen, T. H.; Jespersen, M. C.; Jurtz, V.; Jessen, L. E.; Lanzarotti, E.; Mahajan, S.; Peters, B.; Nielsen, M.; Marcatili, P. TCRpMHCmodels: Structural Modelling of TCR-PMHC Class I Complexes. Sci. Rep. 2019, 9, 14530 DOI: 10.1038/s41598-019-50932-4Google Scholar62https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BB3MnmvVSktA%253D%253D&md5=3d29620d5f2b1aeec26f26b940d4df18TCRpMHCmodels: Structural modelling of TCR-pMHC class I complexesJensen Kamilla Kjaergaard; Rantos Vasileios; Jappe Emma Christine; Olsen Tobias Hegelund; Jespersen Martin Closter; Jessen Leon Eyrich; Nielsen Morten; Marcatili Paolo; Rantos Vasileios; Jappe Emma Christine; Jurtz Vanessa; Lanzarotti Esteban; Nielsen Morten; Mahajan Swapnil; Peters Bjoern; Peters BjoernScientific reports (2019), 9 (1), 14530 ISSN:.The interaction between the class I major histocompatibility complex (MHC), the peptide presented by the MHC and the T-cell receptor (TCR) is a key determinant of the cellular immune response. Here, we present TCRpMHCmodels, a method for accurate structural modelling of the TCR-peptide-MHC (TCR-pMHC) complex. This TCR-pMHC modelling pipeline takes as input the amino acid sequence and generates models of the TCR-pMHC complex, with a median Cα RMSD of 2.31 ÅA. TCRpMHCmodels significantly outperforms TCRFlexDock, a specialised method for docking pMHC and TCR structures. TCRpMHCmodels is simple to use and the modelling pipeline takes, on average, only two minutes. Thanks to its ease of use and high modelling accuracy, we expect TCRpMHCmodels to provide insights into the underlying mechanisms of TCR and pMHC interactions and aid in the development of advanced T-cell-based immunotherapies and rational design of vaccines. The TCRpMHCmodels tool is available at http://www.cbs.dtu.dk/services/TCRpMHCmodels/ .
- 63Wright, D. W.; Wan, S.; Meyer, C.; van Vlijmen, H.; Tresadern, G.; Coveney, P. V. Application of ESMACS Binding Free Energy Protocols to Diverse Datasets: Bromodomain-Containing Protein 4. Sci. Rep. 2019, 9, 6017 DOI: 10.1038/s41598-019-41758-1Google Scholar63https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BB3M%252FkvFaqsQ%253D%253D&md5=b62c5a234b09797af7f8e21846c7815fApplication of ESMACS binding free energy protocols to diverse datasets: Bromodomain-containing protein 4Wright David W; Wan Shunzhou; Coveney Peter V; Meyer Christophe; van Vlijmen Herman; Tresadern GaryScientific reports (2019), 9 (1), 6017 ISSN:.As the application of computational methods in drug discovery pipelines becomes more widespread it is increasingly important to understand how reproducible their results are and how sensitive they are to choices made in simulation setup and analysis. Here we use ensemble simulation protocols, termed ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent), to investigate the sensitivity of the popular molecular mechanics Poisson-Boltzmann surface area (MMPBSA) methodology. Using the bromodomain-containing protein 4 (BRD4) system bound to a diverse set of ligands as our target, we show that robust rankings can be produced only through combining ensemble sampling with multiple trajectories and enhanced solvation via an explicit ligand hydration shell.
- 64Mikulskis, P.; Genheden, S.; Ryde, U. Effect of Explicit Water Molecules on Ligand-Binding Affinities Calculated with the MM/GBSA Approach. J. Mol. Model. 2014, 20, 2273 DOI: 10.1007/s00894-014-2273-xGoogle Scholar64https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC2cjmvFSltQ%253D%253D&md5=9dca49d75be826f8dd37eca977d68fdaEffect of explicit water molecules on ligand-binding affinities calculated with the MM/GBSA approachMikulskis Paulius; Genheden Samuel; Ryde UlfJournal of molecular modeling (2014), 20 (6), 2273 ISSN:.We tested different approaches to including the effect of binding-site water molecules for ligand-binding affinities within the MM/GBSA approach (molecular mechanics combined with generalised Born and surface-area solvation). As a test case, we studied the binding of nine phenol analogues to ferritin. The effect of water molecules mediating the interaction between the receptor and the ligand can be studied by considering a few water molecules as a part of the receptor. We extended previous methods by allowing for a variable number of water molecules in the binding site. The effect of displaced water molecules can also be considered within the MM/GBSA philosophy by calculating the affinities of binding-site water molecules, both before and after binding of the ligand. To obtain proper energies, both the water molecules and the ligand need then to be converted to non-interacting ghost molecules and a single-average approach (i.e., the same structures are used for bound and unbound states) based on the simulations of both the complex and the free receptor can be used to improve the precision. The only problem is to estimate the free energy of an unbound water molecule. With an experimental estimate of this parameter, promising results were obtained for our test case.
- 65Maffucci, I.; Hu, X.; Fumagalli, V.; Contini, A. An Efficient Implementation of the Nwat-MMGBSA Method to Rescore Docking Results in Medium-Throughput Virtual Screenings. Front. Chem. 2018, 6, 43 DOI: 10.3389/fchem.2018.00043Google Scholar65https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXit1egsbrN&md5=b2925a1d0f9323f99cb4c93af53ced04An efficient implementation of the nwat-mmgbsa method to rescore docking results in medium-throughput virtual screeningsMaffucci, Irene; Hu, Xiao; Fumagalli, Valentina; Contini, AlessandroFrontiers in Chemistry (Lausanne, Switzerland) (2018), 6 (), 43/1-43/14CODEN: FCLSAA; ISSN:2296-2646. (Frontiers Media S.A.)Nwat-MMGBSA is a variant of MM-PB/GBSA based on the inclusion of a no. of explicit water mols. that are the closest to the ligand in each frame of a mol. dynamics trajectory. This method demonstrated improved correlations between calcd. and exptl. binding energies in both protein-protein interactions and ligand-receptor complexes, in comparison to the std. MM-GBSA. A protocol optimization, aimed to maximize efficacy and efficiency, is discussed here considering penicillopepsin, HIV1-protease, and BCL-XL as test cases. Calcns. were performed in triplicates on both classic HPC environments and on std. workstations equipped by a GPU card, evidencing no statistical differences in the results. No relevant differences in correlation to expts. were also obsd. when performing Nwat-MMGBSA calcns. on 4 or 1 ns long trajectories. A fully automatic workflow for structure-based virtual screening, performing from library set-up to docking and Nwat-MMGBSA rescoring, has then been developed. The protocol has been tested against no rescoring or std. MM-GBSA rescoring within a retrospective virtual screening of inhibitors of AmpC β-lactamase and of the Rac1-Tiam1 protein-protein interaction. In both cases, Nwat-MMGBSA rescoring provided a statistically significant increase in the ROC AUCs of between 20 and 30%, compared to docking scoring or to std. MM-GBSA rescoring.
- 66Peccati, F.; Jiménez-Osés, G. Enthalpy–Entropy Compensation in Biomolecular Recognition: A Computational Perspective. ACS Omega 2021, 6, 11122– 11130, DOI: 10.1021/acsomega.1c00485Google Scholar66https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3MXptVCnsbc%253D&md5=6dc6836f79c336f41671dd615e119a81Enthalpy-Entropy Compensation in Biomolecular Recognition: A Computational PerspectivePeccati, Francesca; Jimenez-Oses, GonzaloACS Omega (2021), 6 (17), 11122-11130CODEN: ACSODF; ISSN:2470-1343. (American Chemical Society)A review. This mini-review provides an overview of the enthalpy-entropy compensation phenomenon in the simulation of biomacromol. recognition, with particular emphasis on ligand binding. We approach this complex phenomenon from the point of view of practical computational chem. Without providing a detailed description of the plethora of existing methodologies already reviewed in depth elsewhere, we present a series of examples to illustrate different approaches to interpret and predict compensation phenomena at an atomistic level, which is far from trivial to predict using canonical, classic textbook assumptions.
- 67Sun, H.; Duan, L.; Chen, F.; Liu, H.; Wang, Z.; Pan, P.; Zhu, F.; Zhang, J. Z. H.; Hou, T. Assessing the Performance of MM/PBSA and MM/GBSA Methods. 7. Entropy Effects on the Performance of End-Point Binding Free Energy Calculation Approaches. Phys. Chem. Chem. Phys. 2018, 20, 14450– 14460, DOI: 10.1039/C7CP07623AGoogle Scholar67https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXos1Omsrg%253D&md5=04109321f5c9c739a408d439fed21bdaAssessing the performance of MM/PBSA and MM/GBSA methods. 7. Entropy effects on the performance of end-point binding free energy calculation approachesSun, Huiyong; Duan, Lili; Chen, Fu; Liu, Hui; Wang, Zhe; Pan, Peichen; Zhu, Feng; Zhang, John Z. H.; Hou, TingjunPhysical Chemistry Chemical Physics (2018), 20 (21), 14450-14460CODEN: PPCPFQ; ISSN:1463-9076. (Royal Society of Chemistry)Entropy effects play an important role in drug-target interactions, but the entropic contribution to ligand-binding affinity is often neglected by end-point binding free energy calcn. methods, such as MM/GBSA and MM/PBSA, due to the expensive computational cost of normal mode anal. (NMA). Here, the authors systematically investigated entropy effects on the prediction power of MM/GBSA and MM/PBSA using >1500 protein-ligand systems and six representative AMBER force fields. Two computationally efficient methods, including NMA based on truncated structures and the interaction entropy approach, were used to est. the entropic contributions to ligand-target binding free energies. In terms of the overall accuracy, the authors found that, for the minimized structures, in most cases the inclusion of the conformational entropies predicted by truncated NMA (enthalpynmode_min_9Å) compromises the overall accuracy of MM/GBSA and MM/PBSA compared with the enthalpies calcd. based on the minimized structures (enthalpymin). However, for the MD trajectories, the binding free energies can be improved by the inclusion of the conformation entropies predicted by either truncated-NMA for a relatively high dielec. const. (εin = 4) or the interaction entropy method for εin = 1-4. In terms of reproducing the abs. binding free energies, the binding free energies estd. by including the truncated-NMA entropies based on the MD trajectories (ΔGnmode_md_9Å) give the lowest av. abs. deviations against the exptl. data among all the tested strategies for both MM/GBSA and MM/PBSA. Although the inclusion of the truncated NMA based on the MD trajectories (ΔGnmode_md_9Å) for a relatively high dielec. const. gave the overall best result and the lowest av. abs. deviations against the exptl. data (for the ff03 force field), it needs too much computational time. Alternatively, considering that the interaction entropy method does not incur any addnl. computational cost and can give comparable (at high dielec. const., εin = 4) or even better (at low dielec. const., εin = 1-2) results than the truncated-NMA entropy (ΔGnmode_md_9Å), the interaction entropy approach is recommended to est. the entropic component for MM/GBSA and MM/PBSA based on MD trajectories, esp. for a diverse dataset. Furthermore, the authors compared the predictions of MM/GBSA with six different AMBER force fields. The results show that the ff03 force field (ff03 for proteins and gaff with AM1-BCC charges for ligands) performs the best, but the predictions given by the tested force fields are comparable, implying that the MM/GBSA predictions are not very sensitive to force fields.
- 68Genheden, S.; Kuhn, O.; Mikulskis, P.; Hoffmann, D.; Ryde, U. The Normal-Mode Entropy in the MM/GBSA Method: Effect of System Truncation, Buffer Region, and Dielectric Constant. J. Chem. Inf. Model. 2012, 52, 2079– 2088, DOI: 10.1021/ci3001919Google Scholar68https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhtVKlt7%252FP&md5=a82e8b710c3231bfcfc09f25fe6b235dThe Normal-Mode Entropy in the MM/GBSA Method: Effect of System Truncation, Buffer Region, and Dielectric ConstantGenheden, Samuel; Kuhn, Oliver; Mikulskis, Paulius; Hoffmann, Daniel; Ryde, UlfJournal of Chemical Information and Modeling (2012), 52 (8), 2079-2088CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)We have performed a systematic study of the entropy term in the MM/GBSA (mol. mechanics combined with generalized Born and surface-area solvation) approach to calc. ligand-binding affinities. The entropies are calcd. by a normal-mode anal. of harmonic frequencies from minimized snapshots of mol. dynamics simulations. For computational reasons, these calcns. have normally been performed on truncated systems. We have studied the binding of eight inhibitors of blood clotting factor Xa, nine ligands of ferritin, and two ligands of HIV-1 protease and show that removing protein residues with distances larger than 8-16 Å to the ligand, including a 4 Å shell of fixed protein residues and water mols., change the abs. entropies by 1-5 kJ/mol on av. However, the change is systematic, so relative entropies for different ligands change by only 0.7-1.6 kJ/mol on av. Consequently, entropies from truncated systems give relative binding affinities that are identical to those obtained for the whole protein within statistical uncertainty (1-2 kJ/mol). We have also tested to use a distance-dependent dielec. const. in the minimization and frequency calcn. (ε = 4r), but it typically gives slightly different entropies and poorer binding affinities. Therefore, we recommend entropies calcd. with the smallest truncation radius (8 Å) and ε =1. Such an approach also gives an improved precision for the calcd. binding free energies.
- 69Suárez, D.; Díaz, N. Ligand Strain and Entropic Effects on the Binding of Macrocyclic and Linear Inhibitors: Molecular Modeling of Penicillopepsin Complexes. J. Chem. Inf. Model. 2017, 57, 2045– 2055, DOI: 10.1021/acs.jcim.7b00355Google Scholar69https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXht1WgsLfL&md5=c83605b794ab1615e50948f18f15e558Ligand Strain and Entropic Effects on the Binding of Macrocyclic and Linear Inhibitors: Molecular Modeling of Penicillopepsin ComplexesSuarez, Dimas; Diaz, NataliaJournal of Chemical Information and Modeling (2017), 57 (8), 2045-2055CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)Using extensive mol. dynamics simulations, we investigate the structure and dynamics of the complexes formed between penicillopepsin and 2 peptidomimetic inhibitors: a linear compd., isovaleryl(P4)-valine(P3)-asparagine(P2)-leucine(P1)-phosphonate-phenylalanine(P1'), and its macrocyclic analog that includes a methylene bridge between the Asn(P2) and Phe(P1') side-chains. The macrocyclic inhibitor, which has a 420-fold larger affinity than that of the acyclic inhibitor, has been considered to lower the entropic penalty for binding. To better understand this binding preference, the soln. structure of the inhibitors was studied by mol. dynamics simulations. Subsequently, we assessed the influence of the enzyme/inhibitor contacts, the enzyme-induced inhibitor strain, the variation of the ligand configurational entropy, and the enzyme reorganization by combining mol.-mechanics Poisson-Boltzmann surface area and normal mode calcns. with the estn. of the conformational entropy of the inhibitors. We found that there was no relevant entropic stabilization on the binding of the cyclic inhibitor with respect to the acyclic analog because the methylene bridge did not reduce appreciably the conformational flexibility of the free inhibitor. The most important factors explaining the larger affinity of the macrocyclic inhibitor were the conformational filtering and the lower ligand strain induced by the methylene bridge.
- 70Yan, Y.; Yang, M.; Ji, C. G.; Zhang, J. Z. H. Interaction Entropy for Computational Alanine Scanning. J. Chem. Inf. Model. 2017, 57, 1112– 1122, DOI: 10.1021/acs.jcim.6b00734Google Scholar70https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXlvFOqsr8%253D&md5=ae06608eeaa594d31cc2ac9d1b66487fInteraction Entropy for Computational Alanine ScanningYan, Yuna; Yang, Maoyou; Ji, Chang G.; Zhang, John Z. H.Journal of Chemical Information and Modeling (2017), 57 (5), 1112-1122CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)The theor. calcn. of protein-protein binding free energy is a grand challenge in computational biol. Accurate prediction of crit. residues along with their specific and quant. contributions to protein-protein binding free energy is extremely helpful to reveal binding mechanisms and identify drug-like mols. that alter protein-protein interactions. In this paper, we propose an interaction entropy approach combined with the MM/GBSA method for solvation to compute residue-specific protein-protein binding free energy. In the current approach, the entropic loss in binding free energy of individual residues is explicitly computed from MD simulation by using the interaction entropy method. In this approach the entropic contribution to binding free energy is detd. from fluctuation of the interaction in MD simulation. Studies for an extensive set of realistic protein-protein interaction systems showed that by including the entropic contribution, the computed residue-specific binding free energies are in better agreement with the corresponding exptl. data.
- 71Chen, J.; Wang, X.; Zhang, J. Z. H. H.; Zhu, T. Effect of Substituents in Different Positions of Aminothiazole Hinge-Binding Scaffolds on Inhibitor-CDK2 Association Probed by Interaction Entropy Method. ACS Omega 2018, 3, 18052– 18064, DOI: 10.1021/acsomega.8b02354Google Scholar71https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXisFOmt7bO&md5=45bc29bf0a9b77e74bf198ec3ddb905eEffect of Substituents in Different Positions of Aminothiazole Hinge-Binding Scaffolds on Inhibitor-CDK2 Association Probed by Interaction Entropy MethodChen, Jianzhong; Wang, Xingyu; Zhang, John Z. H.; Zhu, TongACS Omega (2018), 3 (12), 18052-18064CODEN: ACSODF; ISSN:2470-1343. (American Chemical Society)Recently, CDK2 has been a promising target of drug development for treatment of the myriad of various human diseases. Mol. dynamics (MD) simulations are integrated with efficient interaction entropy (IE) method to probe effect of substitutions at S1 and S2 positions of the aminothiazole hinge-binding scaffold (1-{4-amino-2-(alkyl(o aryl)amino)thiazol-5-yl}arylmethanones) on bindings of inhibitors to CDK2. The results suggest that a para-sulfonamide moiety or a meta-amino group of a Ph ring introduced into S1 and S2 of the aminothiazole hinge-binding scaffold could not only improve van der Waals interactions of inhibitors with CDK2, but also strengthen their electrostatic interactions. The hot interaction spots of inhibitors with residues of CDK2 were identified by performing scanning of hydrophobic contacts and hydrogen bond contacts of inhibitors with CDK2 on MD trajectories. The results show that the aminothiazole hinge-binding scaffold not only generates stable hydrophobic contacts with conserved residues V18 and L134, but also form stable hydrogen bond contacts with conserved resides E81 and L83. Among the current substitutions, a para-sulfonamide moiety or a meta-amino group of a Ph ring at S1 and S2 of the aminothiazole hinge-binding scaffold display potential to improve binding ability of inhibitors to CDK2. The authors expect that this study can contribute significant guidance to design of potent inhibitors targeting CDK2.
- 72Sun, Z.; Yan, Y. N.; Yang, M.; Zhang, J. Z. H. Interaction Entropy for Protein-Protein Binding. J. Chem. Phys. 2017, 146, 124124 DOI: 10.1063/1.4978893Google Scholar72https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXlsVagtrw%253D&md5=13171a7573f2cf571471c4bd9b749f15Interaction entropy for protein-protein bindingSun, Zhaoxi; Yan, Yu N.; Yang, Maoyou; Zhang, John Z. H.Journal of Chemical Physics (2017), 146 (12), 124124/1-124124/8CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)Protein-protein interactions are at the heart of signal transduction and are central to the function of protein machine in biol. The highly specific protein-protein binding is quant. characterized by the binding free energy whose accurate calcn. from the first principle is a grand challenge in computational biol. In this paper, the authors show how the interaction entropy approach, which was recently proposed for protein-ligand binding free energy calcn., can be applied to computing the entropic contribution to the protein-protein binding free energy. Explicit theor. derivation of the interaction entropy approach for protein-protein interaction system is given in detail from the basic definition. Extensive computational studies for a dozen realistic protein-protein interaction systems are carried out using the present approach and comparisons of the results for these protein-protein systems with those from the std. normal mode method are presented. Anal. of the present method for application in protein-protein binding as well as the limitation of the method in numerical computation is discussed. The study and anal. of the results provided useful information for extg. correct entropic contribution in protein-protein binding from mol. dynamics simulations. (c) 2017 American Institute of Physics.
- 73Ekberg, V.; Ryde, U. On the Use of Interaction Entropy and Related Methods to Estimate Binding Entropies. J. Chem. Theory Comput. 2021, 17, 5379– 5391, DOI: 10.1021/acs.jctc.1c00374Google Scholar73https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3MXhsFaku77I&md5=5f29641ac4bb30b94d28fad15faf4ecbOn the Use of Interaction Entropy and Related Methods to Estimate Binding EntropiesEkberg, Vilhelm; Ryde, UlfJournal of Chemical Theory and Computation (2021), 17 (8), 5379-5391CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)Mol. mechanics combined with Poisson-Boltzmann or generalized Born and solvent-accessible area solvation energies (MM/PBSA and MM/GBSA) are popular methods to est. the free energy for the binding of small mols. to biomacromols. However, the estn. of the entropy was problematic and time-consuming. Traditionally, normal-mode anal. was used to est. the entropy, but more recently, alternative approaches were suggested. In particular, it was suggested that exponential averaging of the electrostatic and Lennard-Jones interaction energies may provide much faster and more accurate entropies, the interaction entropy (IE) approach. This exponential averaging is extremely poorly conditioned. Using stochastic simulations, assuming that the interaction energies follow a Gaussian distribution, if the std. deviation of the interaction energies (σIE) is larger than 15 kJ/mol, it becomes practically impossible to converge the interaction entropies (more than 10 million energies are needed, and the no. increases exponentially). A cumulant approxn. to the second order of the exponential av. shows a better convergence, but for σIE > 25 kJ/mol, it gives entropies that are unrealistically large. Moreover, in practical applications, both methods show a steady increase in the entropy with the no. of energies considered.
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Abstract
Figure 1
Figure 1. (A) Overview of the TCR–pHLA complex. The T-cell receptor (TCR) is comprised of two (α and β) domains, which engage the peptide-human leukocyte antigen (pHLA) complex. (B) Zoom in on the TCR–pHLA binding site from two different angles, demonstrating that the binding interface is composed of six complementarity-determining region (CDR) loops on the TCR, which engage both the peptide and two α-helices on the pHLA complex.
Figure 2
Figure 2. Modulation of the interior dielectric constant improves MMPBSA predictability. Determined Spearman’s rank (rs) and Pearson’s r (rp) values for MMPB/GBSA calculations for the 1G4 (A) and A6 (B) test sets. Results are plotted with and without the three identified outliers described in the text for both data sets. “Di” followed by a value indicates the internal dielectric constant value used (see the Methods section). Exemplar scatter plots with lines of best fit for the 1G4 (C) and A6 (D) test sets using either MMGBSA or MMPBSA (at different internal dielectric constants) methodology. For (C) and (D), outliers are labeled. Scatter plots in panels (C) and (D) are also colored according to the number of charged mutations made between the variant and the WT. Complete scatter graphs for all results are provided in Figures S1 and S2.
Figure 3
Figure 3. Potential rationale for outliers identified in our MMPB/GBSA Calculations. (A) Sequences of the CDR3α loop of the three 1G4 outliers, with positions mutated shown in bold. All 1G4 variant sequences are provided in Table S4. WT A6 TCR–pHLA structure with the two outlier mutation sites S100 (B) and Q30 (C) labeled. Predicted water sites (using 3D-RISM (37,38) and Placevent, (39) see the Methods section) that form bridged water hydrogen bonds to pHLA residues are shown (here, all donor–acceptor heavy atom distances are within 3 Å). The calculated water density distribution function g(r) is shown for water molecules, demonstrating that they are all predicted to have a very high occupancy.
Figure 4
Figure 4. Impact of explicit water molecules on binding affinity predictions. Determined Spearman’s rank (rs) and Pearson’s r (rp) values for MMPB/GBSA calculations on the 1G4 (A, B) and A6 (C, D) test sets for different numbers of explicit water molecules included in the calculation. Exemplar scatter plots for the 1G4 (E) and A6 (F) test sets showing the impact of the inclusion of an increasing number of explicit water molecules when using the MMPBSA method with ϵint set to 6 (Di 6). Scatter points are colored according to the number of charged mutations made between the variant and the WT. Complete scatter graphs for all results are provided in Figures S5–S8.
Figure 5
Figure 5. Illustration of the truncated-normal mode analysis (Trunc-NMA) method used to calculate a solute entropy correction for the 1G4 test set. Residues included in Trunc-NMA calculations are colored in blue (TCR) or magenta (pHLA) if they are flexible in NMA calculations or green if they are frozen (and therefore make up part of the buffer region). Residues colored in white are not included in the calculation (see the Methods section). The 1000 water molecules retained in the calculation are shown as transparent spheres.
Figure 6
Figure 6. Impact of solute entropy corrections on our MMPB/GBSA calculations. (A) Spearman’s rank (rs, unhashed bars) and Pearson’s r (rp, hashed bars) values determined for MMPB/GBSA calculations on the 1G4 test set with ϵint set to 6 (Di 6). Results are presented using a variable number of waters without any entropy corrections included as well as with the Trunc-NMA and Int-Entropy approaches. (B) Exemplar scatter plots for the 1G4 test set with the PBSA approach (with ϵint set to 6) including 50 explicit water molecules. Panels compare no entropy corrections (left), with Int-Entropy corrections (middle) and with Trunc-NMA corrections (right). (C) Impact of the inclusion of the Int-Entropy correction to the A6 data set, with the rs and rp values colored as in (A). All results are without any explicit water molecules included. (D) Exemplar scatter plots for the A6 test set with the PBSA approach (with ϵint set to 6) and no explicit water molecules. Panels compare no entropy corrections (left), with Int-Entropy corrections (right). More complete results, including comparing the effect of removing outliers, are provided in Figure S11.
Figure 7
Figure 7. Bootstrapping to assess the impact of using different numbers of replicas to obtain Spearman’s rank for some of the protocols evaluated in this study. Panels (A) and (B) focus on GBSA and PBSA approaches with no explicit waters included. Panel (C) focuses on the PBSA method with ϵint set to 6. Panel (D) focuses on the PBSA method (ϵint set to 6) with 50 explicit water molecules included with and without the Trunc-NMA correction applied. Measurements with the 1G4 and A6 test sets are colored black and red, respectively. In each panel, the average of the 1 million bootstrap resamples are used to calculate Spearman’s rank when using a differing number of replicas, with the error bars depicting 95% confidence intervals. The complete data is used in all cases (i.e., the outliers discussed above are included). Equivalent results with the Pearson’s r metric are provided in Figure S12.
References
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- 5Miller, B. R.; McGee, T. D.; Swails, J. M.; Homeyer, N.; Gohlke, H.; Roitberg, A. E. MMPBSA.Py: An Efficient Program for End-State Free Energy Calculations. J. Chem. Theory Comput. 2012, 8, 3314– 3321, DOI: 10.1021/ct300418h5https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhtV2gtrzP&md5=cc4148bd8f70c7cad94fd3ec6f580e52MMPBSA.py: An Efficient Program for End-State Free Energy CalculationsMiller, Bill R., III; McGee, T. Dwight, Jr.; Swails, Jason M.; Homeyer, Nadine; Gohlke, Holger; Roitberg, Adrian E.Journal of Chemical Theory and Computation (2012), 8 (9), 3314-3321CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)MM-PBSA is a post-processing end-state method to calc. free energies of mols. in soln. MMPBSA.py is a program written in Python for streamlining end-state free energy calcns. using ensembles derived from mol. dynamics (MD) or Monte Carlo (MC) simulations. Several implicit solvation models are available with MMPBSA.py, including the Poisson-Boltzmann Model, the Generalized Born Model, and the Ref. Interaction Site Model. Vibrational frequencies may be calcd. using normal mode or quasi-harmonic anal. to approx. the solute entropy. Specific interactions can also be dissected using free energy decompn. or alanine scanning. A parallel implementation significantly speeds up the calcn. by dividing frames evenly across available processors. MMPBSA.py is an efficient, user-friendly program with the flexibility to accommodate the needs of users performing end-state free energy calcns. The source code can be downloaded at http://ambermd.org/ with AmberTools, released under the GNU General Public License.
- 6Genheden, S.; Ryde, U. The MM/PBSA and MM/GBSA Methods to Estimate Ligand-Binding Affinities. Expert Opin. Drug Discovery 2015, 10, 449– 461, DOI: 10.1517/17460441.2015.10329366https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXntFGktr8%253D&md5=b123b88809f275564f95a2271ebd159fThe MM/PBSA and MM/GBSA methods to estimate ligand-binding affinitiesGenheden, Samuel; Ryde, UlfExpert Opinion on Drug Discovery (2015), 10 (5), 449-461CODEN: EODDBX; ISSN:1746-0441. (Informa Healthcare)Introduction: The mol. mechanics energies combined with the Poisson-Boltzmann or generalized Born and surface area continuum solvation (MM/PBSA and MM/GBSA) methods are popular approaches to est. the free energy of the binding of small ligands to biol. macromols. They are typically based on mol. dynamics simulations of the receptor-ligand complex and are therefore intermediate in both accuracy and computational effort between empirical scoring and strict alchem. perturbation methods. They have been applied to a large no. of systems with varying success. Areas covered: The authors review the use of MM/PBSA and MM/GBSA methods to calc. ligand-binding affinities, with an emphasis on calibration, testing and validation, as well as attempts to improve the methods, rather than on specific applications. Expert opinion: MM/PBSA and MM/GBSA are attractive approaches owing to their modular nature and that they do not require calcns. on a training set. They have been used successfully to reproduce and rationalize exptl. findings and to improve the results of virtual screening and docking. However, they contain several crude and questionable approxns., for example, the lack of conformational entropy and information about the no. and free energy of water mols. in the binding site. Moreover, there are many variants of the method and their performance varies strongly with the tested system. Likewise, most attempts to ameliorate the methods with more accurate approaches, for example, quantum-mech. calcns., polarizable force fields or improved solvation have deteriorated the results.
- 7Holland, C. J.; Crean, R. M.; Pentier, J. M.; de Wet, B.; Lloyd, A.; Srikannathasan, V.; Lissin, N.; Lloyd, K. A.; Blicher, T. H.; Conroy, P. J.; Hock, M.; Pengelly, R. J.; Spinner, T. E.; Cameron, B.; Potter, E. A.; Jeyanthan, A.; Molloy, P. E.; Sami, M.; Aleksic, M.; Liddy, N.; Robinson, R. A.; Harper, S.; Lepore, M.; Pudney, C. R.; van der Kamp, M. W.; Rizkallah, P. J.; Jakobsen, B. K.; Vuidepot, A.; Cole, D. K. Specificity of Bispecific T Cell Receptors and Antibodies Targeting Peptide-HLA. J. Clin. Invest. 2020, 130, 2673– 2688, DOI: 10.1172/JCI1305627https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXpt12lu7w%253D&md5=201d6c772bb649358f25d8f8c5ef5f46Specificity of bispecific T cell receptors and antibodies targeting peptide-HLAHolland, Christopher J.; Crean, Rory M.; Pentier, Johanne M.; de Wet, Ben; Lloyd, Angharad; Srikannathasan, Velupillai; Lissin, Nikolai; Lloyd, Katy A.; Blicher, Thomas H.; Conroy, Paul J.; Hock, Miriam; Pengelly, Robert J.; Spinner, Thomas E.; Cameron, Brian; Potter, Elizabeth A.; Jeyanthan, Anitha; Molloy, Peter E.; Sami, Malkit; Aleksic, Milos; Liddy, Nathaniel; Robinson, Ross A.; Harper, Stephen; Lepore, Marco; Pudney, Chris R.; van der Kamp, Marc W.; Rizkallah, Pierre J.; Jakobsen, Bent K.; Vuidepot, Annelise; Cole, David K.Journal of Clinical Investigation (2020), 130 (5), 2673-2688CODEN: JCINAO; ISSN:1558-8238. (American Society for Clinical Investigation)Tumor-assocd. peptide-human leukocyte antigen complexes (pHLAs) represent the largest pool of cell surface-expressed cancer-specific epitopes, making them attractive targets for cancer therapies. Sol. bispecific mols. that incorporate an anti-CD3 effector function are being developed to redirect T cells against these targets using 2 different approaches. The first achieves pHLA recognition via affinity-enhanced versions of natural TCRs (e.g., immune-mobilizing monoclonal T cell receptors against cancer [ImmTAC] mols.), whereas the second harnesses an antibody-based format (TCR-mimic antibodies). For both classes of reagent, target specificity is vital, considering the vast universe of potential pHLA mols. that can be presented on healthy cells. Here, we made use of structural, biochem., and computational approaches to investigate the mol. rules underpinning the reactivity patterns of pHLA-targeting bispecifics. We demonstrate that affinity-enhanced TCRs engage pHLA using a comparatively broad and balanced energetic footprint, with interactions distributed over several HLA and peptide side chains. As ImmTAC mols., these TCRs also retained a greater degree of pHLA selectivity, with less off-target activity in cellular assays. Conversely, TCR-mimic antibodies tended to exhibit binding modes focused more toward hot spots on the HLA surface and exhibited a greater degree of crossreactivity. Our findings extend our understanding of the basic principles that underpin pHLA selectivity and exemplify a no. of mol. approaches that can be used to probe the specificity of pHLA-targeting mols., aiding the development of future reagents.
- 8Zoete, V.; Irving, M. B.; Michielin, O. MM-GBSA Binding Free Energy Decomposition and T Cell Receptor Engineering. J. Mol. Recognit. 2010, 23, 142– 152, DOI: 10.1002/jmr.10058https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXitVShsbs%253D&md5=aad0420c4d0c70babd6470d05926d551MM-GBSA binding free energy decomposition and T cell receptor engineeringZoete, V.; Irving, M. B.; Michielin, O.Journal of Molecular Recognition (2010), 23 (2), 142-152CODEN: JMORE4; ISSN:0952-3499. (John Wiley & Sons Ltd.)A review. Recognition by the T-cell receptor (TCR) of immunogenic peptides (p) presented by class I major histocompatibility complexes (MHC) is the key event in the immune response against virus infected cells or tumor cells. The major determinant of T cell activation is the affinity of the TCR for the peptide-MHC complex, though kinetic parameters are also important. A study of the 2C TCR/SIYR/H-2Kb system using a binding free energy decompn. (BFED) based on the MM-GBSA approach had been performed to assess the performance of the approach on this system. The results showed that the TCR-p-MHC BFED including entropic terms provides a detailed and reliable description of the energetics of the interaction (Zoete and Michielin, ). Based on these results, we have developed a new approach to design sequence modifications for a TCR recognizing the human leukocyte antigen (HLA)-A2 restricted tumor epitope NY-ESO-1. NY-ESO-1 is a cancer testis antigen expressed not only in melanoma, but also on several other types of cancers. It has been obsd. at high frequencies in melanoma patients with unusually pos. clin. outcome and, therefore, represents an interesting target for adoptive transfer with modified TCR. Sequence modifications of TCR potentially increasing the affinity for this epitope have been proposed and tested in vitro. T cells expressing some of the proposed TCR mutants showed better T cell functionality, with improved killing of peptide-loaded T2 cells and better proliferative capacity compared to the wild type TCR expressing cells. These results open the door of rational TCR design for adoptive transfer cancer therapy. Copyright © 2010 John Wiley & Sons, Ltd.
- 9Crean, R. M.; MacLachlan, B. J.; Madura, F.; Whalley, T.; Rizkallah, P. J.; Holland, C. J.; McMurran, C.; Harper, S.; Godkin, A.; Sewell, A. K.; Pudney, C. R.; van der Kamp, M. W.; Cole, D. K. Molecular Rules Underpinning Enhanced Affinity Binding of Human T Cell Receptors Engineered for Immunotherapy. Mol. Ther.─Oncolytics 2020, 18, 443– 456, DOI: 10.1016/j.omto.2020.07.0089https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXit1Kqu7vO&md5=0793f2e46638c90ffe471d23bd7eaf0eMolecular Rules Underpinning Enhanced Affinity Binding of Human T Cell Receptors Engineered for ImmunotherapyCrean, Rory M.; MacLachlan, Bruce J.; Madura, Florian; Whalley, Thomas; Rizkallah, Pierre J.; Holland, Christopher J.; McMurran, Catriona; Harper, Stephen; Godkin, Andrew; Sewell, Andrew K.; Pudney, Christopher R.; van der Kamp, Marc W.; Cole, David K.Molecular Therapy--Oncolytics (2020), 18 (), 443-456CODEN: MTOHDL; ISSN:2372-7705. (Elsevier Inc.)Immuno-oncol. approaches that utilize T cell receptors (TCRs) are becoming highly attractive because of their potential to target virtually all cellular proteins, including cancer-specific epitopes, via the recognition of peptide-human leukocyte antigen (pHLA) complexes presented at the cell surface. However, because natural TCRs generally recognize cancer-derived pHLAs with very weak affinities, efforts have been made to enhance their binding strength, in some cases by several million-fold. In this study, we investigated the mechanisms underpinning human TCR affinity enhancement by comparing the crystal structures of engineered enhanced affinity TCRs with those of their wild-type progenitors. Addnl., we performed mol. dynamics simulations to better understand the energetic mechanisms driving the affinity enhancements. These data demonstrate that supra-physiol. binding affinities can be achieved without altering native TCR-pHLA binding modes via relatively subtle modifications to the interface contacts, often driven through the addn. of buried hydrophobic residues. Individual energetic components of the TCR-pHLA interaction governing affinity enhancements were distinct and highly variable for each TCR, often resulting from additive, or knock-on, effects beyond the mutated residues. This comprehensive anal. of affinity-enhanced TCRs has important implications for the future rational design of engineered TCRs as efficacious and safe drugs for cancer treatment.
- 10Zoete, V.; Irving, M.; Ferber, M.; Cuendet, M. A.; Michielin, O. Structure-Based, Rational Design of T Cell Receptors. Front. Immunol. 2013, 4, 268 DOI: 10.3389/fimmu.2013.0026810https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC2cflt1yksA%253D%253D&md5=86915a4ce37665203344aee030a5c316Structure-Based, Rational Design of T Cell ReceptorsZoete V; Irving M; Ferber M; Cuendet M A; Michielin OFrontiers in immunology (2013), 4 (), 268 ISSN:1664-3224.Adoptive cell transfer using engineered T cells is emerging as a promising treatment for metastatic melanoma. Such an approach allows one to introduce T cell receptor (TCR) modifications that, while maintaining the specificity for the targeted antigen, can enhance the binding and kinetic parameters for the interaction with peptides (p) bound to major histocompatibility complexes (MHC). Using the well-characterized 2C TCR/SIYR/H-2K(b) structure as a model system, we demonstrated that a binding free energy decomposition based on the MM-GBSA approach provides a detailed and reliable description of the TCR/pMHC interactions at the structural and thermodynamic levels. Starting from this result, we developed a new structure-based approach, to rationally design new TCR sequences, and applied it to the BC1 TCR targeting the HLA-A2 restricted NY-ESO-1157-165 cancer-testis epitope. Fifty-four percent of the designed sequence replacements exhibited improved pMHC binding as compared to the native TCR, with up to 150-fold increase in affinity, while preserving specificity. Genetically engineered CD8(+) T cells expressing these modified TCRs showed an improved functional activity compared to those expressing BC1 TCR. We measured maximum levels of activities for TCRs within the upper limit of natural affinity, K D = ∼1 - 5 μM. Beyond the affinity threshold at K D < 1 μM we observed an attenuation in cellular function, in line with the "half-life" model of T cell activation. Our computer-aided protein-engineering approach requires the 3D-structure of the TCR-pMHC complex of interest, which can be obtained from X-ray crystallography. We have also developed a homology modeling-based approach, TCRep 3D, to obtain accurate structural models of any TCR-pMHC complexes when experimental data is not available. Since the accuracy of the models depends on the prediction of the TCR orientation over pMHC, we have complemented the approach with a simplified rigid method to predict this orientation and successfully assessed it using all non-redundant TCR-pMHC crystal structures available. These methods potentially extend the use of our TCR engineering method to entire TCR repertoires for which no X-ray structure is available. We have also performed a steered molecular dynamics study of the unbinding of the TCR-pMHC complex to get a better understanding of how TCRs interact with pMHCs. This entire rational TCR design pipeline is now being used to produce rationally optimized TCRs for adoptive cell therapies of stage IV melanoma.
- 11Maffucci, I.; Contini, A. Improved Computation of Protein–Protein Relative Binding Energies with the Nwat-MMGBSA Method. J. Chem. Inf. Model. 2016, 56, 1692– 1704, DOI: 10.1021/acs.jcim.6b0019611https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28Xht12mtbbJ&md5=74aa27e8eaf6c304edc80e432beb7653Improved Computation of Protein-Protein Relative Binding Energies with the Nwat-MMGBSA MethodMaffucci, Irene; Contini, AlessandroJournal of Chemical Information and Modeling (2016), 56 (9), 1692-1704CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)A MMGBSA variant (here referred to as Nwat-MMGBSA), based on the inclusion of a certain no. of explicit water mols. (Nwat) during the calcns., has been tested on a set of 20 protein-protein complexes, using the correlation between predicted and exptl. binding energy as the evaluation metric. Beside the Nwat parameter, the effect of the force field, the mol. dynamics simulation length, and the implicit solvent model used in the MMGBSA anal. have been also evaluated. Considering 30 interfacial water mols. improved the correlation between predicted and exptl. binding energies by up to 30%, compared to the std. approach. Moreover, the correlation resulted rather sensitively to the force field and, to a minor extent, to the implicit solvent model, and to the length of the MD simulation.
- 12Wang, C.; Greene, D.; Xiao, L.; Qi, R.; Luo, R. Recent Developments and Applications of the MMPBSA Method. Front. Mol. Biosci. 2018, 4, 87 DOI: 10.3389/fmolb.2017.00087There is no corresponding record for this reference.
- 13Sun, H.; Li, Y.; Tian, S.; Xu, L.; Hou, T. Assessing the Performance of MM/PBSA and MM/GBSA Methods. 4. Accuracies of MM/PBSA and MM/GBSA Methodologies Evaluated by Various Simulation Protocols Using PDBbind Data Set. Phys. Chem. Chem. Phys. 2014, 16, 16719– 16729, DOI: 10.1039/C4CP01388C13https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhtFSltrzI&md5=d0271f6d49fb026bba944a121aa2a8fdAssessing the performance of MM/PBSA and MM/GBSA methods. 4. Accuracies of MM/PBSA and MM/GBSA methodologies evaluated by various simulation protocols using PDBbind data setSun, Huiyong; Li, Youyong; Tian, Sheng; Xu, Lei; Hou, TingjunPhysical Chemistry Chemical Physics (2014), 16 (31), 16719-16729CODEN: PPCPFQ; ISSN:1463-9076. (Royal Society of Chemistry)By using different evaluation strategies, we systemically evaluated the performance of Mol. Mechanics/Generalized Born Surface Area (MM/GBSA) and Mol. Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) methodologies based on more than 1800 protein-ligand crystal structures in the PDBbind database. The results can be summarized as follows: (1) for the one-protein-family/one-binding-ligand case which represents the unbiased protein-ligand complex sampling, both MM/GBSA and MM/PBSA methodologies achieve approx. equal accuracies at the interior dielec. const. of 4 (with rp = 0.408 ± 0.006 of MM/GBSA and rp = 0.388 ± 0.006 of MM/PBSA based on the minimized structures); while for the total dataset (1864 crystal structures), the overall best Pearson correlation coeff. (rp = 0.579 ± 0.002) based on MM/GBSA is better than that of MM/PBSA (rp = 0.491 ± 0.003), indicating that biased sampling may significantly affect the accuracy of the predicted result (some protein families contain too many instances and can bias the overall predicted accuracy). Therefore, family based classification is needed to evaluate the two methodologies; (2) the prediction accuracies of MM/GBSA and MM/PBSA for different protein families are quite different with rp ranging from 0 to 0.9, whereas the correlation and ranking scores (an averaged rp/rs over a list of protein folds and also representing the unbiased sampling) given by MM/PBSA (rp-score = 0.506 ± 0.050 and rs-score = 0.481 ± 0.052) are comparable to those given by MM/GBSA (rp-score = 0.516 ± 0.047 and rs-score = 0.463 ± 0.047) at the fold family level; (3) for the overall prediction accuracies, mol. dynamics (MD) simulation may not be quite necessary for MM/GBSA (rp-minimized = 0.579 ± 0.002 and rp-1ns = 0.564 ± 0.002), but is needed for MM/PBSA (rp-minimized = 0.412 ± 0.003 and rp-1ns = 0.491 ± 0.003). However, for the individual systems, whether to use MD simulation is depended. (4) both MM/GBSA and MM/PBSA may be unable to give successful predictions for the ligands with high formal charges, with the Pearson correlation coeff. ranging from 0.621 ± 0.003 (neutral ligands) to 0.125 ± 0.142 (ligands with a formal charge of 5). Therefore, it can be summarized that, although MM/GBSA and MM/PBSA perform similarly in the unbiased dataset, for the currently available crystal structures in the PDBbind database, compared with MM/GBSA, which may be used in multi-target comparisons, MM/PBSA is more sensitive to the investigated systems, and may be more suitable for individual-target-level binding free energy ranking. This study may provide useful guidance for the post-processing of docking based studies.
- 14Zhu, Y.-L.; Beroza, P.; Artis, D. R. Including Explicit Water Molecules as Part of the Protein Structure in MM/PBSA Calculations. J. Chem. Inf. Model. 2014, 54, 462– 469, DOI: 10.1021/ci400179414https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXitVWnsb7J&md5=285d8818f326df9f889912aaf0313e7dIncluding Explicit Water Molecules as Part of the Protein Structure in MM/PBSA CalculationsZhu, Yong-Liang; Beroza, Paul; Artis, Dean R.Journal of Chemical Information and Modeling (2014), 54 (2), 462-469CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)Water is the natural medium of mols. in the cell and plays an important role in protein structure, function and interaction with small mol. ligands. However, the widely used mol. mechanics Poisson-Boltzmann surface area (MM/PBSA) method for binding energy calcn. does not explicitly take account of water mols. that mediate key protein-ligand interactions. We have developed a protocol to include water mols. that mediate ligand-protein interactions as part of the protein structure in calcn. of MM/PBSA binding energies (a method we refer to as water-MM/PBSA) for a series of JNK3 kinase inhibitors. Improved correlation between water-MM/PBSA binding energies and exptl. IC50 values was obtained compared to that obtained from classical MM/PBSA binding energy. This improved correlation was further validated using sets of neuraminidase and avidin inhibitors. The obsd. improvement, however, appears to be limited to systems in which there are water-mediated ligand-protein hydrogen bond interactions. We conclude that the water-MM/PBSA method performs better than classical MM/PBSA in predicting binding affinities when water mols. play a direct role in mediating ligand-protein hydrogen bond interactions.
- 15Godschalk, F.; Genheden, S.; Söderhjelm, P.; Ryde, U. Comparison of MM/GBSA Calculations Based on Explicit and Implicit Solvent Simulations. Phys. Chem. Chem. Phys. 2013, 15, 7731, DOI: 10.1039/c3cp00116d15https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXmvVSgurc%253D&md5=00b6fa66b6215d07c52bec4af6300d80Comparison of MM/GBSA calculations based on explicit and implicit solvent simulationsGodschalk, Frithjof; Genheden, Samuel; Soederhjelm, Paer; Ryde, UlfPhysical Chemistry Chemical Physics (2013), 15 (20), 7731-7739CODEN: PPCPFQ; ISSN:1463-9076. (Royal Society of Chemistry)Mol. mechanics with generalized Born and surface area solvation (MM/GBSA) is a popular method to calc. the free energy of the binding of ligands to proteins. It involves mol. dynamics (MD) simulations with an explicit solvent of the protein-ligand complex to give a set of snapshots for which energies are calcd. with an implicit solvent. This change in the solvation method (explicit implicit) would strictly require that the energies are reweighted with the implicit-solvent energies, which is normally not done. In this paper we calc. MM/GBSA energies with two generalized Born models for snapshots generated by the same methods or by explicit-solvent simulations for five synthetic N-acetyllactosamine derivs. binding to galectin-3. We show that the resulting energies are very different both in abs. and relative terms, showing that the change in the solvent model is far from innocent and that std. MM/GBSA is not a consistent method. The ensembles generated with the various solvent models are quite different with root-mean-square deviations of 1.2-1.4 Å. The ensembles can be converted to each other by performing short MD simulations with the new method, but the convergence is slow, showing mean abs. differences in the calcd. energies of 6-7 kJ mol-1 after 2 ps simulations. Minimisations show even slower convergence and there are strong indications that the energies obtained from minimized structures are different from those obtained by MD.
- 16Liu, X.; Peng, L.; Zhang, J. Z. H. Accurate and Efficient Calculation of Protein–Protein Binding Free Energy-Interaction Entropy with Residue Type-Specific Dielectric Constants. J. Chem. Inf. Model. 2019, 59, 272– 281, DOI: 10.1021/acs.jcim.8b0024816https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXit1Sgsb7F&md5=bd2735b50518cd7951bca4a98b1580f6Accurate and Efficient Calculation of Protein-Protein Binding Free Energy-Interaction Entropy with Residue Type-Specific Dielectric ConstantsLiu, Xiao; Peng, Long; Zhang, John Z. H.Journal of Chemical Information and Modeling (2019), 59 (1), 272-281CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)Accurate and efficient computation of protein-protein binding free energy remains a grand challenge. The authors develop a new strategy to achieve efficient calcn. for total protein-protein binding free energies with improved accuracy. The new method combines the recently developed interaction entropy method for efficient computation of entropic change together using residue type-specific dielec. consts. in the framework of MM/GBSA to achieve optimal result for protein-protein binding free energies. The new strategy is computationally efficient and accurate than that using std. MM/GBSA methods in which the entropic computation was performed by the normal model approach and the protein interior is represented by the std. dielec. const. (typically set to 1), both in terms of accuracy and computational efficiency. The authors' study using the new strategy on a set of randomly selected 20 protein-protein binding systems produced an optimal dielec. const. of 2.7 for charged residues and 1.1 for noncharged residues. Using this new strategy, the mean abs. error in computed binding free energies for these 20 selected protein-protein systems is significantly reduced by >3-fold while the computational cost is reduced by >2 orders of magnitude, compared to the result using std. MM/GBSA method with the normal mode approach. A similar improvement in accuracy is confirmed for a test set consisting of 10 protein-protein systems.
- 17Goebeler, M.-E.; Bargou, R. C. T Cell-Engaging Therapies ─ BiTEs and Beyond. Nat. Rev. Clin. Oncol. 2020, 17, 418– 434, DOI: 10.1038/s41571-020-0347-517https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BB38zgsVWnsA%253D%253D&md5=2beedd06773540f367596f6e621e5f9dT cell-engaging therapies - BiTEs and beyondGoebeler Maria-Elisabeth; Goebeler Maria-Elisabeth; Bargou Ralf CNature reviews. Clinical oncology (2020), 17 (7), 418-434 ISSN:.Immuno-oncology approaches have entered clinical practice, with tremendous progress particularly in the field of T cell-engaging therapies over the past decade. Herein, we provide an overview of the current status of bispecific T cell engager (BiTE) therapy, considering the unprecedented new indication for such therapy in combating minimal (or measurable) residual disease in patients with acute lymphoblastic leukaemia, and the development of novel approaches based on this concept. Key aspects that we discuss include the current clinical data, challenges relating to treatment administration and patient monitoring, toxicities and resistance to treatment, and novel strategies to overcome these hurdles as well as to broaden the indications for BiTE therapy, particularly to common solid cancers. Elucidation of mechanisms of resistance and immune escape and new technologies used in drug development pave the way for new and more-effective therapies and rational combinatorial approaches. In particular, we highlight novel therapeutic agents, such as bifunctional checkpoint-inhibitory T cell engagers (CiTEs), simultaneous multiple interaction T cell engagers (SMITEs), trispecific killer engagers (TriKEs) and BiTE-expressing chimeric antigen receptor (CAR) T cells (CART.BiTE cells), designed to integrate various immune functions into one molecule or a single cellular vector and thereby enhance efficacy without compromising safety. We also discuss the targeting of intracellular tumour-associated epitopes using bispecific constructs with T cell receptor (TCR)-derived, rather than an antibody-based, antigen-recognition domains, termed immune-mobilizing monoclonal TCRs against cancer (ImmTACs), which might broaden the armamentarium of T cell-engaging therapies.
- 18Hewitt, E. W. The MHC Class I Antigen Presentation Pathway: Strategies for Viral Immune Evasion. Immunology 2003, 110, 163– 169, DOI: 10.1046/j.1365-2567.2003.01738.x18https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3sXotFSmtbk%253D&md5=c669b243791ce0c2a3e6e6dad5665c12The MHC class I antigen presentation pathway: Strategies for viral immune evasionHewitt, Eric W.Immunology (2003), 110 (2), 163-169CODEN: IMMUAM; ISSN:0019-2805. (Blackwell Publishing Ltd.)A review. Presumably because of the selective pressure exerted by the immune system, many viruses have evolved proteins that interfere with antigen presentation by major histocompatibility complex (MHC) class I mols. These viruses utilize a whole variety of ingenious strategies to inhibit the MHC class I pathway. Viral proteins have been characterized that exploit bottlenecks in the MHC class I pathway, such as peptide translocation by the transporter assocd. with antigen processing. Alternatively, viral proteins can cause the degrdn. or mislocalization of MHC class I mols. This is often achieved by the subversion of the host cell's own protein degrdn. and trafficking pathways. As a consequence elucidation of how these viral proteins act to subvert host cell function will continue to give important insights not only into virus-host interactions but also the function and mechanism of cellular pathways.
- 19Oates, J.; Jakobsen, B. K. ImmTACs. Oncoimmunology 2013, 2, e22891 DOI: 10.4161/onci.22891There is no corresponding record for this reference.
- 20Singh, N. K.; Riley, T. P.; Baker, S. C. B.; Borrman, T.; Weng, Z.; Baker, B. M. Emerging Concepts in TCR Specificity: Rationalizing and (Maybe) Predicting Outcomes. J. Immunol. 2017, 199, 2203– 2213, DOI: 10.4049/jimmunol.170074420https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXhsFSmsrfI&md5=1bdf2bb4639bbb3074fe2b13969db69cEmerging Concepts in TCR Specificity: Rationalizing and (Maybe) Predicting OutcomesSingh, Nishant K.; Riley, Timothy P.; Baker, Sarah Catherine B.; Borrman, Tyler; Weng, Zhiping; Baker, Brian M.Journal of Immunology (2017), 199 (7), 2203-2213CODEN: JOIMA3; ISSN:0022-1767. (American Association of Immunologists)T cell specificity emerges from a myriad of processes, ranging from the biol. pathways that control T cell signaling to the structural and phys. mechanisms that influence how TCRs bind peptides and MHC proteins. Of these processes, the binding specificity of the TCR is a key component. However, TCR specificity is enigmatic: TCRs are at once specific but also cross-reactive. Although long appreciated, this duality continues to puzzle immunologists and has implications for the development of TCR-based therapeutics. In this review, we discuss TCR specificity, emphasizing results that have emerged from structural and phys. studies of TCR binding. We show how the TCR specificity/cross-reactivity duality can be rationalized from structural and biophys. principles. There is excellent agreement between predictions from these principles and classic predictions about the scope of TCR cross-reactivity. We demonstrate how these same principles can also explain amino acid preferences in immunogenic epitopes and highlight opportunities for structural considerations in predictive immunol.
- 21Aleksic, M.; Liddy, N.; Molloy, P. E.; Pumphrey, N.; Vuidepot, A.; Chang, K.-M.; Jakobsen, B. K. Different Affinity Windows for Virus and Cancer-Specific T-Cell Receptors: Implications for Therapeutic Strategies. Eur. J. Immunol. 2012, 42, 3174– 3179, DOI: 10.1002/eji.20124260621https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhsFWiu73E&md5=e3092ecba5cc0f263a48648659e896aaDifferent affinity windows for virus and cancer-specific T-cell receptors: Implications for therapeutic strategiesAleksic, Milos; Liddy, Nathaniel; Molloy, Peter E.; Pumphrey, Nick; Vuidepot, Annelise; Chang, Kyong-Mi; Jakobsen, Bent K.European Journal of Immunology (2012), 42 (12), 3174-3179CODEN: EJIMAF; ISSN:0014-2980. (Wiley-VCH Verlag GmbH & Co. KGaA)T-cell destiny during thymic selection depends on the affinity of the TCR for autologous peptide ligands presented in the context of MHC mols. This is a delicately balanced process; robust binding leads to neg. selection, yet some affinity for the antigen complex is required for pos. selection. All TCRs of the resulting repertoire thus have some intrinsic affinity for an MHC type presenting an assortment of peptides. Generally, TCR affinities of peripheral T cells will be low toward self-derived peptides, as these would have been presented during thymic selection, whereas, by serendipity, binding to pathogen-derived peptides that are encountered de novo could be stronger. A crucial question in assessing immunotherapeutic strategies for cancer is whether natural TCR repertoires have the capacity for efficiently recognizing tumor-assocd. peptide antigens. Here, we report a comprehensive comparison of TCR affinities to a range of HLA-A2 presented antigens. TCRs that bind viral antigens fall within a strikingly higher affinity range than those that bind cancer-related antigens. This difference may be one of the key explanations for tumor immune escape and for the deficiencies of T-cell vaccines against cancer.
- 22Richman, S. A.; Healan, S. J.; Weber, K. S.; Donermeyer, D. L.; Dossett, M. L.; Greenberg, P. D.; Allen, P. M.; Kranz, D. M. Development of a Novel Strategy for Engineering High-Affinity Proteins by Yeast Display. Protein Eng., Des. Sel. 2006, 19, 255– 264, DOI: 10.1093/protein/gzl00822https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28XmsVehsLk%253D&md5=4e79d4c21267d100f947758d560ef6c2Development of a novel strategy for engineering high-affinity proteins by yeast displayRichman, S. A.; Healan, S. J.; Weber, K. S.; Donermeyer, D. L.; Dossett, M. L.; Greenberg, P. D.; Allen, P. M.; Kranz, D. M.Protein Engineering, Design & Selection (2006), 19 (6), 255-264CODEN: PEDSBR; ISSN:1741-0126. (Oxford University Press)Yeast display provides a system for engineering high-affinity proteins using a fluorescent-labeled ligand and fluorescence-activated cell sorting (FACS). In cases where it is difficult to obtain purified ligands, or to access FACS instrumentation, an alternative selection strategy would be useful. Here we show that yeast expressing high-affinity proteins against a mammalian cell surface ligand could be rapidly selected by d. centrifugation. Yeast cell-mammalian cell conjugates were retained at the d. interface, sepd. from unbound yeast. High-affinity T cell receptors (TCRs) displayed on yeast were isolated using antigen presenting cells that expressed TCR ligands, peptides bound to products of the major histocompatibility complex (MHC). The procedure yielded 1000-fold enrichments, in a single centrifugation, of yeast displaying high-affinity TCRs. We defined the affinity limits of the method and isolated high-affinity TCR mutants against peptide variants that differed by only a single residue. The approach was applied to TCRs specific for class I or class II MHC, an important finding since peptide-class II MHC ligands have been particularly difficult to purify. As yeast display has also been used previously to identify antigen-specific antibodies, the method should be applicable to the selection of antibodies, as well as TCRs, with high-affinity for tumor cell-surface antigens.
- 23Harris, D. T.; Wang, N.; Riley, T. P.; Anderson, S. D.; Singh, N. K.; Procko, E.; Baker, B. M.; Kranz, D. M. Deep Mutational Scans as a Guide to Engineering High Affinity T Cell Receptor Interactions with Peptide-Bound Major Histocompatibility Complex. J. Biol. Chem. 2016, 291, 24566– 24578, DOI: 10.1074/jbc.M116.74868123https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XhvV2gurbM&md5=5970f622e9e00834e79a184d0425190aDeep mutational scans as a guide to engineering high affinity T cell receptor interactions with peptide-bound major histocompatibility complexHarris, Daniel T.; Wang, Ningyan; Riley, Timothy P.; Anderson, Scott D.; Singh, Nishant K.; Procko, Erik; Baker, Brian M.; Kranz, David M.Journal of Biological Chemistry (2016), 291 (47), 24566-24578CODEN: JBCHA3; ISSN:0021-9258. (American Society for Biochemistry and Molecular Biology)Proteins are often engineered to have higher affinity for their ligands to achieve therapeutic benefit. For example, many studies have used phage or yeast display libraries of mutants within complementarity-detg. regions to affinity mature antibodies and T cell receptors (TCRs). However, these approaches do not allow rapid assessment or evolution across the entire interface. By combining directed evolution with deep sequencing, it is now possible to generate sequence fitness landscapes that survey the impact of every amino acid substitution across the entire protein-protein interface. Here we used the results of deep mutational scans of a TCR-peptide-MHC interaction to guide mutational strategies. The approach yielded stable TCRs with affinity increases of >200-fold. The substitutions with the greatest enrichments based on the deep sequencing were validated to have higher affinity and could be combined to yield addnl. improvements. We also conducted in silico binding analyses for every substitution to compare them with the fitness landscape. Computational modeling did not effectively predict the impacts of mutations distal to the interface and did not account for yeast display results that depended on combinations of affinity and protein stability. However, computation accurately predicted affinity changes for mutations within or near the interface, highlighting the complementary strengths of computational modeling and yeast surface display coupled with deep mutational scanning for engineering high affinity TCRs.
- 24Chervin, A. S.; Aggen, D. H.; Raseman, J. M.; Kranz, D. M. Engineering Higher Affinity T Cell Receptors Using a T Cell Display System. J. Immunol. Methods 2008, 339, 175– 184, DOI: 10.1016/j.jim.2008.09.01624https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXhtl2qtb%252FK&md5=5a01b7c76c86837c1944570e3ba0e5fcEngineering higher affinity T cell receptors using a T cell display systemChervin, Adam S.; Aggen, David H.; Raseman, John M.; Kranz, David M.Journal of Immunological Methods (2008), 339 (2), 175-184CODEN: JIMMBG; ISSN:0022-1759. (Elsevier B.V.)The T cell receptor (TCR) dets. the cellular response to antigens, which are presented on the surface of target cells in the form of a peptide bound to a product of the major histocompatibility complex (pepMHC). The response of the T cell depends on the affinity of the TCR for the pepMHC, yet many TCRs have been shown to be of low affinity, and some naturally occurring T cell responses are poor due to low affinities. Accordingly, engineering the TCR for increased affinity for pepMHC, particularly tumor-assocd. antigens, has become an increasingly desirable goal, esp. with the advent of adoptive T cell therapies. For largely tech. reasons, to date there have been only a handful of TCRs engineered in vitro for higher affinity using well established methods of protein engineering. Here the authors report the use of a T cell display system, using a retroviral vector, for generating a high-affinity TCR from the mouse T cell clone 2C. The method relies on the display of the TCR, in its normal, signaling competent state, as a CD3 complex on the T cell surface. A library in the CDR3α of the 2C TCR was generated in the MSCV retroviral vector and transduced into a TCR-neg. hybridoma. Selection of a high-affinity, CD8-independent TCR was accomplished after only two rounds of flow cytometric sorting using the pepMHC SIYRYYGL/Kb (SIY/Kb). The selected TCR contained a sequence motif in the CDR3α with characteristics of several other TCRs previously selected by yeast display. In addn., it was possible to directly use the selected T cell hybridoma in functional assays without the need for sub-cloning, revealing that the selected TCR was capable of mediating CD8-independent activity. The method may be useful in the direct isolation and characterization of TCRs that could be used in therapies with adoptive transferred T cells.
- 25Sharma, P.; Kranz, D. M. Subtle Changes at the Variable Domain Interface of the T-Cell Receptor Can Strongly Increase Affinity. J. Biol. Chem. 2018, 293, 1820– 1834, DOI: 10.1074/jbc.M117.81415225https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXnsVygtbw%253D&md5=edae742c79a4914cebbc858a7fc307bbSubtle changes at the variable domain interface of the T-cell receptor can strongly increase affinitySharma, Preeti; Kranz, David M.Journal of Biological Chemistry (2018), 293 (5), 1820-1834CODEN: JBCHA3; ISSN:0021-9258. (American Society for Biochemistry and Molecular Biology)Most affinity-maturation campaigns for antibodies and T-cell receptors (TCRs) operate on the residues at the binding site, located within the loops known as complementarity-detg. regions (CDRs). Accordingly, mutations in contact residues, or so-called "second shell" residues, that increase affinity are typically identified by directed evolution involving combinatorial libraries. To det. the impact of residues located at a distance from the binding site, here we used single-codon libraries of both CDR and non-CDR residues to generate a deep mutational scan of a human TCR against the cancer antigen MART1-HLA-A2. Non-CDR residues included those at the interface of the TCR variable domains (Vα and βV) and surface-exposed framework residues. Mutational analyses showed that both Vα/Vβ interface and CDR residues were important in maintaining binding to MART-1-HLA-A2, probably due to either structural requirements for proper Vα/Vβ assocn. or direct contact with the ligand. More surprisingly, many V/V interface substitutions yielded improved binding to MART-1·HLA-A2. To further explore this finding, we constructed interface libraries and selected them for improved stability or affinity. Among the variants identified, one conservative substitution (F45βY) was most prevalent. Further anal. of F45βY showed that it enhanced thermostability and increased affinity by 60-fold. Thus, introducing a single hydroxyl group at the Vα/Vβ interface, at a significant distance from the TCR·peptide·MHC-binding site, remarkably affected ligand binding. The variant retained a high degree of specificity for MART-1HLA-A2, indicating that our approach provides a general strategy for engineering improvements in either sol. or cell-based TCRs for therapeutic purposes.
- 26Li, Y.; Moysey, R.; Molloy, P. E.; Vuidepot, A. L.; Mahon, T.; Baston, E.; Dunn, S.; Liddy, N.; Jacob, J.; Jakobsen, B. K.; Boulter, J. M. Directed Evolution of Human T-Cell Receptors with Picomolar Affinities by Phage Display. Nat. Biotechnol. 2005, 23, 349– 354, DOI: 10.1038/nbt107026https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2MXitF2nt7o%253D&md5=925e7e535add7d4ce63b3b451b0bc8d4Directed evolution of human T-cell receptors with picomolar affinities by phage displayLi, Yi; Moysey, Ruth; Molloy, Peter E.; Vuidepot, Anne-Lise; Mahon, Tara; Baston, Emma; Dunn, Steven; Liddy, Nathaniel; Jacob, Jansen; Jakobsen, Bent K.; Boulter, Jonathan M.Nature Biotechnology (2005), 23 (3), 349-354CODEN: NABIF9; ISSN:1087-0156. (Nature Publishing Group)Peptides derived from almost all proteins, including disease-assocd. proteins, can be presented on the cell surface as peptide-human leukocyte antigen (pHLA) complexes. T cells specifically recognize pHLA with their clonally rearranged T-cell receptors (TCRs), whose natural affinities are limited to ∼1-100 μM. Here we describe the display of ten different human TCRs on the surface of bacteriophage, stabilized by a nonnative interchain disulfide bond. We report the directed evolution of high-affinity TCRs specific for two different pHLAs: the human T-cell lymphotropic virus type 1 (HTLV-1) tax11-19 peptide-HLA-A*0201 complex and the NY-ESO-157-165 tumor-assocd. peptide antigen-HLA-A*0201 complex, with affinities of up to 2.5 nM and 26 pM, resp., and we demonstrate their high specificity and sensitivity for targeting of cell-surface pHLAs.
- 27Madura, F.; Rizkallah, P. J.; Miles, K. M.; Holland, C. J.; Bulek, A. M.; Fuller, A.; Schauenburg, A. J. A.; Miles, J. J.; Liddy, N.; Sami, M.; Li, Y.; Hossain, M.; Baker, B. M.; Jakobsen, B. K.; Sewell, A. K.; Cole, D. K. T-Cell Receptor Specificity Maintained by Altered Thermodynamics. J. Biol. Chem. 2013, 288, 18766– 18775, DOI: 10.1074/jbc.M113.46456027https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhtVehsLbK&md5=15fa2cd1da454eec5b1ec4df85b7bd4dT-cell receptor specificity maintained by altered thermodynamicsMadura, Florian; Rizkallah, Pierre J.; Miles, Kim M.; Holland, Christopher J.; Bulek, Anna M.; Fuller, Anna; Schauenburg, Andrea J. A.; Miles, John J.; Liddy, Nathaniel; Sami, Malkit; Li, Yi; Hossain, Moushumi; Baker, Brian M.; Jakobsen, Bent K.; Sewell, Andrew K.; Cole, David K.Journal of Biological Chemistry (2013), 288 (26), 18766-18775CODEN: JBCHA3; ISSN:0021-9258. (American Society for Biochemistry and Molecular Biology)The T-cell receptor (TCR) recognizes peptides bound to major histocompatibility mols. (MHC) and allows T-cells to interrogate the cellular proteome for internal anomalies from the cell surface. The TCR contacts both MHC and peptide in an interaction characterized by weak affinity (KD = 100 nm to 270 μm). We used phage-display to produce a melanoma-specific TCR (α24β17) with a 30,000-fold enhanced binding affinity (KD = 0.6 nm) to aid our exploration of the mol. mechanisms utilized to maintain peptide specificity. Remarkably, although the enhanced affinity was mediated primarily through new TCR-MHC contacts, α24β17 remained acutely sensitive to modifications at every position along the peptide backbone, mimicking the specificity of the wild type TCR. Thermodn. analyses revealed an important role for solvation in directing peptide specificity. These findings advance our understanding of the mol. mechanisms that can govern the exquisite peptide specificity characteristic of TCR recognition.
- 28Pierce, B. G.; Hellman, L. M.; Hossain, M.; Singh, N. K.; Vander Kooi, C. W.; Weng, Z.; Baker, B. M. Computational Design of the Affinity and Specificity of a Therapeutic T Cell Receptor. PLoS Comput. Biol. 2014, 10, e1003478 DOI: 10.1371/journal.pcbi.100347828https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXkvVOitLo%253D&md5=29ffc1ef992eb181b754b61e37f56b56Computational design of the affinity and specificity of a therapeutic T cell receptorPierce, Brian G.; Hellman, Lance M.; Hossain, Moushumi; Singh, Nishant K.; Vander Kooi, Craig W.; Weng, Zhiping; Baker, Brian M.PLoS Computational Biology (2014), 10 (2), e1003478/1-e1003478/11, 11 pp.CODEN: PCBLBG; ISSN:1553-7358. (Public Library of Science)T cell receptors (TCRs) are key to antigen-specific immunity and are increasingly being explored as therapeutics, most visibly in cancer immunotherapy. As TCRs typically possess only low-to-moderate affinity for their peptide/MHC (pMHC) ligands, there is a recognized need to develop affinity-enhanced TCR variants. Previous in vitro engineering efforts have yielded remarkable improvements in TCR affinity, yet concerns exist about the maintenance of peptide specificity and the biol. impacts of ultra-high affinity. As opposed to in vitro engineering, computational design can directly address these issues, in theory permitting the rational control of peptide specificity together with relatively controlled increments in affinity. Here we explored the efficacy of computational design with the clin. relevant TCR DMF5, which recognizes nonameric and decameric epitopes from the melanoma-assocd. Melan-A/MART-1 protein presented by the class I MHC HLA-A2. We tested multiple mutations selected by flexible and rigid modeling protocols, assessed impacts on affinity and specificity, and utilized the data to examine and improve algorithmic performance. We identified multiple mutations that improved binding affinity, and characterized the structure, affinity, and binding kinetics of a previously reported double mutant that exhibits an impressive 400-fold affinity improvement for the decameric pMHC ligand without detectable binding to non-cognate ligands. The structure of this high affinity mutant indicated very little conformational consequences and emphasized the high fidelity of our modeling procedure. Overall, our work showcases the capability of computational design to generate TCRs with improved pMHC affinities while explicitly accounting for peptide specificity, as well as its potential for generating TCRs with customized antigen targeting capabilities.
- 29Haidar, J. N.; Pierce, B.; Yu, Y.; Tong, W.; Li, M.; Weng, Z. Structure-Based Design of a T-Cell Receptor Leads to Nearly 100-Fold Improvement in Binding Affinity for PepMHC. Proteins: Struct., Funct., Bioinf. 2009, 74, 948– 960, DOI: 10.1002/prot.2220329https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXitlGjt7g%253D&md5=455aac53bf93bcb817d5862d5b86dc7eStructure-based design of a T-cell receptor leads to nearly 100-fold improvement in binding affinity for pepMHCHaidar, Jaafar N.; Pierce, Brian; Yu, Yong; Tong, Weiwei; Li, Michael; Weng, ZhipingProteins: Structure, Function, and Bioinformatics (2009), 74 (4), 948-960CODEN: PSFBAF ISSN:. (Wiley-Liss, Inc.)T-cell receptors (TCRs) are proteins that recognize peptides from foreign proteins bound to the major histocompatibility complex (MHC) on the surface of an antigen-presenting cell. This interaction enables the T cells to initiate a cell-mediated immune response to terminate cells displaying the foreign peptide on their MHC. Naturally occurring TCRs have high specificity but low affinity toward the peptide-MHC (pepMHC) complex. This prevents the usage of solubilized TCRs for diagnosis and treatment of viral infections or cancers. Efforts to enhance the binding affinity of several TCRs have been reported in recent years, through randomized libraries and in vitro selection. However, there have been no reported efforts to enhance the affinity via structure-based design, which allows more control and understanding of the mechanism of improvement. Here, we have applied structure-based design to a human TCR to improve its pepMHC binding. Our design method evolved based on iterative steps of prediction, testing, and generating more predictions based on the new data. The final design function, named ZAFFI, has a correlation of 0.77 and av. error of 0.35 kcal/mol with the binding free energies of 26 point mutations for this system that we measured by surface plasmon resonance (SPR). Applying the filter that we developed to remove nonbinding predictions, this correlation increases to 0.85, and the av. error decreases to 0.3 kcal/mol. Using this algorithm, we predicted and tested several point mutations that improved binding, with one giving over sixfold binding improvement. Four of the point mutations that improved binding were then combined to give a mutant TCR that binds the pepMHC 99 times more strongly than the wild-type TCR.
- 30Hellman, L. M.; Foley, K. C.; Singh, N. K.; Alonso, J. A.; Riley, T. P.; Devlin, J. R.; Ayres, C. M.; Keller, G. L. J.; Zhang, Y.; Vander Kooi, C. W.; Nishimura, M. I.; Baker, B. M. Improving T Cell Receptor On-Target Specificity via Structure-Guided Design. Mol. Ther. 2019, 27, 300– 313, DOI: 10.1016/j.ymthe.2018.12.01030https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXis1Wqu78%253D&md5=c8f1f4b0f174f1f5e94b26e3a4c39386Improving T Cell Receptor On-Target Specificity via Structure-Guided DesignHellman, Lance M.; Foley, Kendra C.; Singh, Nishant K.; Alonso, Jesus A.; Riley, Timothy P.; Devlin, Jason R.; Ayres, Cory M.; Keller, Grant L. J.; Zhang, Yuting; Vander Kooi, Craig W.; Nishimura, Michael I.; Baker, Brian M.Molecular Therapy (2019), 27 (2), 300-313CODEN: MTOHCK; ISSN:1525-0024. (Cell Press)T cell receptors (TCRs) have emerged as a new class of immunol. therapeutics. However, though antigen specificity is a hallmark of adaptive immunity, TCRs themselves do not possess the high specificity of monoclonal antibodies. Although a necessary function of T cell biol., the resulting cross-reactivity presents a significant challenge for TCR-based therapeutic development, as it creates the potential for off-target recognition and immune toxicity. Efforts to enhance TCR specificity by mimicking the antibody maturation process and enhancing affinity can inadvertently exacerbate TCR cross-reactivity. Here we demonstrate this concern by showing that even peptide-targeted mutations in the TCR can introduce new reactivities against peptides that bear similarity to the original target. To counteract this, we explored a novel structure-guided approach for enhancing TCR specificity independent of affinity. Tested with the MART-1-specific TCR DMF5, our approach had a small but discernible impact on cross-reactivity toward MART-1 homologs yet was able to eliminate DMF5 cross-recognition of more divergent, unrelated epitopes. Our study provides a proof of principle for the use of advanced structure-guided design techniques for improving TCR specificity, and it suggests new ways forward for enhancing TCRs for therapeutic use.
- 31Chen, J.-L.; Stewart-Jones, G.; Bossi, G.; Lissin, N. M.; Wooldridge, L.; Choi, E. M. L.; Held, G.; Dunbar, P. R.; Esnouf, R. M.; Sami, M.; Boulter, J. M.; Rizkallah, P.; Renner, C.; Sewell, A.; van der Merwe, P. A.; Jakobsen, B. K.; Griffiths, G.; Jones, E. Y.; Cerundolo, V. Structural and Kinetic Basis for Heightened Immunogenicity of T Cell Vaccines. J. Exp. Med. 2005, 201, 1243– 1255, DOI: 10.1084/jem.2004232331https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2MXjs1CitLc%253D&md5=82d72a355878315f2406366379021bf5Structural and kinetic basis for heightened immunogenicity of T cell vaccinesChen, Ji-Li; Stewart-Jones, Guillaume; Bossi, Giovanna; Lissin, Nikolai M.; Wooldridge, Linda; Choi, Ed Man Lik; Held, Gerhard; Dunbar, P. Rod; Esnouf, Robert M.; Sami, Malkit; Boulter, Jonathan M.; Rizkallah, Pierre; Renner, Christoph; Sewell, Andrew; van der Merwe, P. Anton; Jakobsen, Bent K.; Griffiths, Gillian; Jones, E. Yvonne; Cerundolo, VincenzoJournal of Experimental Medicine (2005), 201 (8), 1243-1255CODEN: JEMEAV; ISSN:0022-1007. (Rockefeller University Press)Analog peptides with enhanced binding affinity to major histocompatibility class (MHC) I mols. are currently being used in cancer patients to elicit stronger T cell responses. However, it remains unclear as to how alterations of anchor residues may affect T cell receptor (TCR) recognition. We correlate functional, thermodn., and structural parameters of TCR-peptide-MHC binding and demonstrate the effect of anchor residue modifications of the human histocompatibility leukocyte antigens (HLA)-A2 tumor epitope NY-ESO-1157-165-SLLMWITQC on TCR recognition. The crystal structure of the wild-type peptide complexed with a specific TCR shows that TCR binding centers on two prominent, sequential, peptide side chains, methionine-tryptophan. Cysteine-to-valine substitution at peptide position 9, while optimizing peptide binding to the MHC, repositions the peptide main chain and generates subtly enhanced interactions between the analog peptide and the TCR. Binding analyses confirm tighter binding of the analog peptide to HLA-A2 and improved sol. TCR binding. Recognition of analog peptide stimulates faster polarization of lytic granules to the immunol. synapse, reduces dependence on CD8 binding, and induces greater nos. of cross-reactive cytotoxic T lymphocyte to SLLMWITQC. These results provide important insights into heightened immunogenicity of analog peptides and highlight the importance of incorporating structural data into the process of rational optimization of superagonist peptides for clin. trials.
- 32Garboczi, D. N.; Ghosh, P.; Utz, U.; Fan, Q. R.; Biddison, W. E.; Wiley, D. C. Structure of the Complex between Human T-Cell Receptor, Viral Peptide and HLA-A2. Nature 1996, 384, 134– 141, DOI: 10.1038/384134a032https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK28XmvFGitbY%253D&md5=813f1d65110a725173c0de9ac803afcaStructure of the complex between human T-cell receptor, viral peptide and HLA-A2Garboczi, David N.; Ghosh, Partho; Utz, Ursula; Fan, Qing R.; Biddison, William E.; Wiley, Don C.Nature (London) (1996), 384 (6605), 134-141CODEN: NATUAS; ISSN:0028-0836. (Macmillan Magazines)Recognition by a T-cell antigen receptor (TCR) of peptide complexed with a major histocompatibility complex (MHC) mol. occurs through variable loops in the TCR structure which bury almost all the available peptide and a much lager area of the MHC mol. The TCR fits diagonally across the MHC peptide-binding site in a surface feature common to all class I and class II MHC mols., providing evidence that the nature of binding is general. A broadly applicable binding mode has implications for the mechanism of repertoire selection and the magnitude of alloreactions.
- 33Cole, D. K.; Sami, M.; Scott, D. R.; Rizkallah, P. J.; Borbulevych, O. Y.; Todorov, P. T.; Moysey, R. K.; Jakobsen, B. K.; Boulter, J. M.; Baker, B. M.; Li, Y.; Yi, Li. Increased Peptide Contacts Govern High Affinity Binding of a Modified TCR Whilst Maintaining a Native PMHC Docking Mode. Front. Immunol. 2013, 4, 168 DOI: 10.3389/fimmu.2013.0016833https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC3sjmtFWlsA%253D%253D&md5=59bcb168675a7cb436908c24f5d57717Increased Peptide Contacts Govern High Affinity Binding of a Modified TCR Whilst Maintaining a Native pMHC Docking ModeCole David K; Sami Malkit; Scott Daniel R; Rizkallah Pierre J; Borbulevych Oleg Y; Todorov Penio T; Moysey Ruth K; Jakobsen Bent K; Boulter Jonathan M; Baker Brian M; Yi LiFrontiers in immunology (2013), 4 (), 168 ISSN:1664-3224.Natural T cell receptors (TCRs) generally bind to their cognate pMHC molecules with weak affinity and fast kinetics, limiting their use as therapeutic agents. Using phage display, we have engineered a high affinity version of the A6 wild-type TCR (A6wt), specific for the human leukocyte antigen (HLA-A(*)0201) complexed with human T cell lymphotropic virus type 111-19 peptide (A2-Tax). Mutations in just 4 residues in the CDR3β loop region of the A6wt TCR were selected that improved binding to A2-Tax by nearly 1000-fold. Biophysical measurements of this mutant TCR (A6c134) demonstrated that the enhanced binding was derived through favorable enthalpy and a slower off-rate. The structure of the free A6c134 TCR and the A6c134/A2-Tax complex revealed a native binding mode, similar to the A6wt/A2-Tax complex. However, concordant with the more favorable binding enthalpy, the A6c134 TCR made increased contacts with the Tax peptide compared with the A6wt/A2-Tax complex, demonstrating a peptide-focused mechanism for the enhanced affinity that directly involved the mutated residues in the A6c134 TCR CDR3β loop. This peptide-focused enhanced TCR binding may represent an important approach for developing antigen specific high affinity TCR reagents for use in T cell based therapies.
- 34Schrödinger. PyMOL Molecular Graphics System (v. 2.1.0); 2018, Schrödinger, LLC.There is no corresponding record for this reference.
- 35Chen, V. B.; Arendall, W. B.; Headd, J. J.; Keedy, D. A.; Immormino, R. M.; Kapral, G. J.; Murray, L. W.; Richardson, J. S.; Richardson, D. C. MolProbity: All-Atom Structure Validation for Macromolecular Crystallography. Acta Crystallogr., Sect. D: Biol. Crystallogr. 2010, 66, 12– 21, DOI: 10.1107/S090744490904207335https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXit1Kktg%253D%253D&md5=b5fc7574f43f01dd6e43c3663ca4f779MolProbity: all-atom structure validation for macromolecular crystallographyChen, Vincent B.; Arendall, W. Bryan, III; Headd, Jeffrey J.; Keedy, Daniel A.; Immormino, Robert M.; Kapral, Gary J.; Murray, Laura W.; Richardson, Jane S.; Richardson, David C.Acta Crystallographica, Section D: Biological Crystallography (2010), 66 (1), 12-21CODEN: ABCRE6; ISSN:0907-4449. (International Union of Crystallography)MolProbity is a structure-validation web service that provides broad-spectrum solidly based evaluation of model quality at both the global and local levels for both proteins and nucleic acids. It relies heavily on the power and sensitivity provided by optimized hydrogen placement and all-atom contact anal., complemented by updated versions of covalent-geometry and torsion-angle criteria. Some of the local corrections can be performed automatically in MolProbity and all of the diagnostics are presented in chart and graphical forms that help guide manual rebuilding. X-ray crystallog. provides a wealth of biol. important mol. data in the form of at. three-dimensional structures of proteins, nucleic acids and increasingly large complexes in multiple forms and states. Advances in automation, in everything from crystn. to data collection to phasing to model building to refinement, have made solving a structure using crystallog. easier than ever. However, despite these improvements, local errors that can affect biol. interpretation are widespread at low resoln. and even high-resoln. structures nearly all contain at least a few local errors such as Ramachandran outliers, flipped branched protein side chains and incorrect sugar puckers. It is crit. both for the crystallographer and for the end user that there are easy and reliable methods to diagnose and correct these sorts of errors in structures. MolProbity is the authors' contribution to helping solve this problem and this article reviews its general capabilities, reports on recent enhancements and usage, and presents evidence that the resulting improvements are now beneficially affecting the global database.
- 36Søndergaard, C. R.; Olsson, M. H. M.; Rostkowski, M.; Jensen, J. H. Improved Treatment of Ligands and Coupling Effects in Empirical Calculation and Rationalization of PKa Values. J. Chem. Theory Comput. 2011, 7, 2284– 2295, DOI: 10.1021/ct200133y36https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXnt1Gnsrs%253D&md5=cf4d4e20d6daa70de6ac623915e78160Improved Treatment of Ligands and Coupling Effects in Empirical Calculation and Rationalization of pKa ValuesSondergaard, Chresten R.; Olsson, Mats H. M.; Rostkowski, Michal; Jensen, Jan H.Journal of Chemical Theory and Computation (2011), 7 (7), 2284-2295CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The new empirical rules for protein pKa predictions implemented in the PROPKA3.0 software package have been extended to the prediction of pKa shifts of active site residues and ionizable ligand groups in protein-ligand complexes. The authors present new algorithms that allow pKa shifts due to inductive (i.e., covalently coupled) intraligand interactions, as well as noncovalently coupled interligand interactions in multiligand complexes, to be included in the prediction. The no. of different ligand chem. groups that are automatically recognized has been increased to 18, and the general implementation has been changed so that new functional groups can be added easily by the user, aided by a new and more general protonation scheme. Except for a few cases, the new algorithms in PROPKA3.1 are found to yield results similar to or better than those obtained with PROPKA2.0. Finally, the authors present a novel algorithm that identifies noncovalently coupled ionizable groups, where pKa prediction may be esp. difficult. This is a general improvement to PROPKA and is applied to proteins with and without ligands.
- 37Beglov, D.; Roux, B. An Integral Equation To Describe the Solvation of Polar Molecules in Liquid Water. J. Phys. Chem. B 1997, 101, 7821– 7826, DOI: 10.1021/jp971083h37https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2sXlslGgt74%253D&md5=400c9449f40638c9a1ea9692b697c9eaIntegral Equation To Describe the Solvation of Polar Molecules in Liquid WaterBeglov, Dmitrii; Roux, BenoitJournal of Physical Chemistry B (1997), 101 (39), 7821-7826CODEN: JPCBFK; ISSN:1089-5647. (American Chemical Society)We developed and implemented a statistical mech. integral equation theory to describe the hydration structure of complex mols. The theory, which is an extension of the ref. interaction site model (RISM) in three dimensions, yields the av. d. from the solvent interactions sites at all points r around a mol. solute of arbitrary shape. Both solute-solvent electrostatic and van der Waals interactions are fully included, and solvent packing is taken into account. The approach is illustrated by calcg. the av. oxygen and hydrogen d. of liq. water around two mol. solutes: water and N-methylacetamide. Mol.-dynamics simulations are performed to test the results obtained from the integral equation. It is obsd. that important microscopic structural features of the av. water d. due to hydrogen bonding are reproduced by the integral equation. The integral equation has a simple formal structure and is easy to implement numerically. It offers a powerful alternative to computer simulations with explicit solvent mols. and to continuum solvent representations for incorporating solvation effects in a wide range of applications.
- 38Kovalenko, A.; Hirata, F. Potential of Mean Force between Two Molecular Ions in a Polar Molecular Solvent: A Study by the Three-Dimensional Reference Interaction Site Model. J. Phys. Chem. B 1999, 103, 7942– 7957, DOI: 10.1021/jp991300+38https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK1MXlsFSrsbk%253D&md5=70620cb15d05198fbb88af00386984acPotential of Mean Force between Two Molecular Ions in a Polar Molecular Solvent: A Study by the Three-Dimensional Reference Interaction Site ModelKovalenko, Andriy; Hirata, FumioJournal of Physical Chemistry B (1999), 103 (37), 7942-7957CODEN: JPCBFK; ISSN:1089-5647. (American Chemical Society)The orientationally dependent potential of mean force (PMF) between two charged polyat. solutes immersed in a polar mol. solvent was obtained by using the three-dimensional ref. interaction site model (3D RISM) of the integral equation theory and partially linearized hypernetted chain (PLHNC) closure. The method was applied to the N,N-dimethylaniline cation (DMA+) and the anthracene anion (AN-) in acetonitrile solvent (CH3CN). We solved the 3D RISM integral equations by employing the modified direct inversion in the iterative subspace (MDIIS) method. The 3D site distributions of solvent around each solute were obtained and discussed. The PMF between the solutes was calcd. as a 3D profile dependent on the relative position of the solutes at six characteristic relative orientations. The PMF obtained is in qual. agreement with the results of mol. dynamics simulations. In the solvent, the AN- solute effectively attracts the DMA+ dimethylamino group and repels its Ph ring. The most stable relative arrangement of the DMA+ and AN- mols. in acetonitrile solvent is different from that in gas phase.
- 39Sindhikara, D. J.; Yoshida, N.; Hirata, F. Placevent: An Algorithm for Prediction of Explicit Solvent Atom Distribution-Application to HIV-1 Protease and F-ATP Synthase. J. Comput. Chem. 2012, 33, 1536– 1543, DOI: 10.1002/jcc.2298439https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XlslyktLk%253D&md5=f80d4c1a0b2c5d87695481674da31814Placevent: An algorithm for prediction of explicit solvent atom distribution - Application to HIV-1 protease and F-ATP synthaseSindhikara, Daniel J.; Yoshida, Norio; Hirata, FumioJournal of Computational Chemistry (2012), 33 (18), 1536-1543CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)We have created a simple algorithm for automatically predicting the explicit solvent atom distribution of biomols. The explicit distribution is coerced from the three-dimensional (3D) continuous distribution resulting from a 3D ref. interaction site model (3D-RISM) calcn. This procedure predicts optimal location of solvent mols. and ions given a rigid biomol. structure and the solvent compn. We show examples of predicting water mols. near the KNI-272 bound form of HIV-1 protease and predicting both sodium ions and water mols. near the rotor ring of F-ATP synthase. Our results give excellent agreement with exptl. structure with an av. prediction error of 0.39-0.65 Å. Further, unlike exptl. methods, this method does not suffer from the partial occupancy limit. Our method can be performed directly on 3D-RISM output within minutes. It is extremely useful for examg. multiple specific solvent-solute interactions, as a convenient method for generating initial solvent structures for mol. dynamics calcns., and may assist in refinement of exptl. structures. © 2012 Wiley Periodicals, Inc.
- 40Case, D. A.; Cerutti, D. S.; Cheatham, T. E., III; Darden, T. A.; Duke, R. E.; Giese, T. J.; Gohlke, H.; Goetz, A. W.; Greene, D.; Homeyer, N.; Izadi, S.; Kovalenko, A.; Lee, T. S.; LeGrand, S.; Li, P.; Lin, C.; Liu, J.; Luchko, T.; Luo, R.; Mermelstein, D.; Merz, K. M.; Monard, G.; Nguyen, H.; Omelyan, I.; Onufriev, A.; Pan, F.; Qi, R.; Roe, D. R.; Roitberg, A.; Sagui, C.; Simmerling, C. L.; Botello-Smith, W. M.; Swails, J.; Walker, R. C.; Wang, J.; Wolf, R. M.; Wu, X.; Xiao, L.; York, D. M.; Kollman, P. A. Amber; University of California: San Francisco, 2016.There is no corresponding record for this reference.
- 41Maier, J. A.; Martinez, C.; Kasavajhala, K.; Wickstrom, L.; Hauser, K. E.; Simmerling, C. Ff14SB: Improving the Accuracy of Protein Side Chain and Backbone Parameters from Ff99SB. J. Chem. Theory Comput. 2015, 11, 3696– 3713, DOI: 10.1021/acs.jctc.5b0025541https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhtFequ7rN&md5=7b803577b3b6912cc6750cfbd356596eff14SB: Improving the Accuracy of Protein Side Chain and Backbone Parameters from ff99SBMaier, James A.; Martinez, Carmenza; Kasavajhala, Koushik; Wickstrom, Lauren; Hauser, Kevin E.; Simmerling, CarlosJournal of Chemical Theory and Computation (2015), 11 (8), 3696-3713CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)Mol. mechanics is powerful for its speed in atomistic simulations, but an accurate force field is required. The Amber ff99SB force field improved protein secondary structure balance and dynamics from earlier force fields like ff99, but weaknesses in side chain rotamer and backbone secondary structure preferences have been identified. Here, we performed a complete refit of all amino acid side chain dihedral parameters, which had been carried over from ff94. The training set of conformations included multidimensional dihedral scans designed to improve transferability of the parameters. Improvement in all amino acids was obtained as compared to ff99SB. Parameters were also generated for alternate protonation states of ionizable side chains. Av. errors in relative energies of pairs of conformations were under 1.0 kcal/mol as compared to QM, reduced 35% from ff99SB. We also took the opportunity to make empirical adjustments to the protein backbone dihedral parameters as compared to ff99SB. Multiple small adjustments of φ and ψ parameters were tested against NMR scalar coupling data and secondary structure content for short peptides. The best results were obtained from a phys. motivated adjustment to the φ rotational profile that compensates for lack of ff99SB QM training data in the β-ppII transition region. Together, these backbone and side chain modifications (hereafter called ff14SB) not only better reproduced their benchmarks, but also improved secondary structure content in small peptides and reprodn. of NMR χ1 scalar coupling measurements for proteins in soln. We also discuss the Amber ff12SB parameter set, a preliminary version of ff14SB that includes most of its improvements.
- 42Roe, D. R.; Cheatham, T. E. PTRAJ and CPPTRAJ: Software for Processing and Analysis of Molecular Dynamics Trajectory Data. J. Chem. Theory Comput. 2013, 9, 3084– 3095, DOI: 10.1021/ct400341p42https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXptFehtr8%253D&md5=6f1bee934f13f180bd7e1feb6b78036dPTRAJ and CPPTRAJ: Software for Processing and Analysis of Molecular Dynamics Trajectory DataRoe, Daniel R.; Cheatham, Thomas E.Journal of Chemical Theory and Computation (2013), 9 (7), 3084-3095CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)We describe PTRAJ and its successor CPPTRAJ, two complementary, portable, and freely available computer programs for the anal. and processing of time series of three-dimensional at. positions (i.e., coordinate trajectories) and the data therein derived. Common tools include the ability to manipulate the data to convert among trajectory formats, process groups of trajectories generated with ensemble methods (e.g., replica exchange mol. dynamics), image with periodic boundary conditions, create av. structures, strip subsets of the system, and perform calcns. such as RMS fitting, measuring distances, B-factors, radii of gyration, radial distribution functions, and time correlations, among other actions and analyses. Both the PTRAJ and CPPTRAJ programs and source code are freely available under the GNU General Public License version 3 and are currently distributed within the AmberTools 12 suite of support programs that make up part of the Amber package of computer programs (see http://ambermd.org). This overview describes the general design, features, and history of these two programs, as well as algorithmic improvements and new features available in CPPTRAJ.
- 43Nguyen, H.; Roe, D. R.; Simmerling, C. Improved Generalized Born Solvent Model Parameters for Protein Simulations. J. Chem. Theory Comput. 2013, 9, 2020– 2034, DOI: 10.1021/ct301048543https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXjsFaqs7c%253D&md5=1d674f02a81c7c2f0da0715aa657a89dImproved Generalized Born Solvent Model Parameters for Protein SimulationsNguyen, Hai; Roe, Daniel R.; Simmerling, CarlosJournal of Chemical Theory and Computation (2013), 9 (4), 2020-2034CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The generalized Born (GB) model is one of the fastest implicit solvent models, and it has become widely adopted for Mol. Dynamics (MD) simulations. This speed comes with trade-offs, and many reports in the literature have pointed out weaknesses with GB models. Because the quality of a GB model is heavily affected by empirical parameters used in calcg. solvation energy, in this work we have refit these parameters for GB-Neck, a recently developed GB model, in order to improve the accuracy of both the solvation energy and effective radii calcns. The data sets used for fitting are significantly larger than those used in the past. Comparing to other pairwise GB models like GB-OBC and the original GB-Neck, the new GB model (GB-Neck2) has better agreement with Poisson-Boltzmann (PB) in terms of reproducing solvation energies for a variety of systems ranging from peptides to proteins. Secondary structure preferences are also in much better agreement with those obtained from explicit solvent MD simulations. We also obtain near-quant. reprodn. of exptl. structure and thermal stability profiles for several model peptides with varying secondary structure motifs. Extension to nonprotein systems will be explored in the future.
- 44Duan, L.; Liu, X.; Zhang, J. Z. H. Interaction Entropy: A New Paradigm for Highly Efficient and Reliable Computation of Protein-Ligand Binding Free Energy. J. Am. Chem. Soc. 2016, 138, 5722– 5728, DOI: 10.1021/jacs.6b0268244https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28Xls1Kjuro%253D&md5=696a28a2660cc96dcd51d81a505923ddInteraction Entropy: A New Paradigm for Highly Efficient and Reliable Computation of Protein-Ligand Binding Free EnergyDuan, Lili; Liu, Xiao; Zhang, John Z. H.Journal of the American Chemical Society (2016), 138 (17), 5722-5728CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)Efficient and reliable calcn. of protein-ligand binding free energy is a grand challenge in computational biol. and is of crit. importance in drug design and many other mol. recognition problems. The main challenge lies in the calcn. of entropic contribution to protein-ligand binding or interaction systems. In this report, we present a new interaction entropy method which is theor. rigorous, computationally efficient, and numerically reliable for calcg. entropic contribution to free energy in protein-ligand binding and other interaction processes. Drastically different from the widely employed but extremely expensive normal mode method for calcg. entropy change in protein-ligand binding, the new method calcs. the entropic component (interaction entropy or -TΔS) of the binding free energy directly from mol. dynamics simulation without any extra computational cost. Extensive study of over a dozen randomly selected protein-ligand binding systems demonstrated that this interaction entropy method is both computationally efficient and numerically reliable and is vastly superior to the std. normal mode approach. This interaction entropy paradigm introduces a novel and intuitive conceptual understanding of the entropic effect in protein-ligand binding and other general interaction systems as well as a practical method for highly efficient calcn. of this effect.
- 45Kongsted, J.; Ryde, U. An Improved Method to Predict the Entropy Term with the MM/PBSA Approach. J. Comput.-Aided Mol. Des. 2009, 23, 63– 71, DOI: 10.1007/s10822-008-9238-z45https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXmtFGn&md5=770f5b34c7c279e0944f81b83d8b3170An improved method to predict the entropy term with the MM/PBSA approachKongsted, Jacob; Ryde, UlfJournal of Computer-Aided Molecular Design (2009), 23 (2), 63-71CODEN: JCADEQ; ISSN:0920-654X. (Springer)A method is suggested to calc. improved entropies within the MM/PBSA approach (mol. mechanics combined with Poisson-Boltzmann and surface area calcns.) to est. protein-ligand binding affinities. In the conventional approach, the protein is truncated outside ∼8 Å from the ligand. This system is freely minimized using a distance-dependent dielec. const. (to simulate the removed protein and solvent). However, this can lead to extensive changes in the mol. geometry, giving rise to a large std. deviation in this term. In our new approach, we introduce a buffer region ∼4 Å outside the truncated protein (including solvent mols.) and keep it fixed during the minimization. Thereby, we reduce the std. deviation by a factor of 2-4, ensuring that the entropy term no longer limits the precision of the MM/PBSA predictions. The new method is tested for the binding of seven biotin analogs to avidin, eight amidinobenzyl-indole-carboxamide inhibitors to factor Xa, and two substrates to cytochrome P 450 3A4 and 2C9. It is shown that it gives more stable results and often improved predictions of the relative binding affinities.
- 46Dunn, S. M.; Rizkallah, P. J.; Baston, E.; Mahon, T.; Cameron, B.; Moysey, R.; Gao, F.; Sami, M.; Boulter, J.; Li, Y.; Jakobsen, B. K. Directed Evolution of Human T Cell Receptor CDR2 Residues by Phage Display Dramatically Enhances Affinity for Cognate Peptide-MHC without Increasing Apparent Cross-Reactivity. Protein Sci. 2006, 15, 710– 721, DOI: 10.1110/ps.05193640646https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28XjsFCqsb0%253D&md5=669fe7d2739b669e8bce45ff0a89ab9dDirected evolution of human T cell receptor CDR2 residues by phage display dramatically enhances affinity for cognate peptide-MHC without increasing apparent cross-reactivityDunn, Steven M.; Rizkallah, Pierre J.; Baston, Emma; Mahon, Tara; Cameron, Brian; Moysey, Ruth; Gao, Feng; Sami, Malkit; Boulter, Jonathan; Li, Yi; Jakobsen, Bent K.Protein Science (2006), 15 (4), 710-721CODEN: PRCIEI; ISSN:0961-8368. (Cold Spring Harbor Laboratory Press)The mammalian α/β T cell receptor (TCR) repertoire plays a pivotal role in adaptive immunity by recognizing short, processed, peptide antigens bound in the context of a highly diverse family of cell-surface major histocompatibility complexes (pMHCs). Despite the extensive TCR-MHC interaction surface, peptide-independent cross-reactivity of native TCRs is generally avoided through cell-mediated selection of mols. with low inherent affinity for MHC. Here we show that, contrary to expectations, the germ line-encoded complementarity detg. regions (CDRs) of human TCRs, namely the CDR2s, which appear to contact only the MHC surface and not the bound peptide, can be engineered to yield sol. low nanomolar affinity ligands that retain a surprisingly high degree of specificity for the cognate pMHC target. Structural investigation of one such CDR2 mutant implicates shape complementarity of the mutant CDR2 contact interfaces as being a key determinant of the increased affinity. Our results suggest that manipulation of germ line CDR2 loops may provide a useful route to the prodn. of high-affinity TCRs with therapeutic and diagnostic potential.
- 47Wan, S.; Knapp, B.; Wright, D. W.; Deane, C. M.; Coveney, P. V. Rapid, Precise, and Reproducible Prediction of Peptide-MHC Binding Affinities from Molecular Dynamics That Correlate Well with Experiment. J. Chem. Theory Comput. 2015, 11, 3346– 3356, DOI: 10.1021/acs.jctc.5b0017947https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhtVaksLjN&md5=860aa35a6e8e4013e2b0c7f0ae99170fRapid, precise, and reproducible prediction of peptide-MHC binding affinities from molecular dynamics that correlate well with experimentWan, Shunzhou; Knapp, Bernhard; Wright, David W.; Deane, Charlotte M.; Coveney, Peter V.Journal of Chemical Theory and Computation (2015), 11 (7), 3346-3356CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The presentation of potentially pathogenic peptides by major histocompatibility complex (MHC) mols. is one of the most important processes in adaptive immune defense. Prediction of peptide-MHC (pMHC) binding affinities is therefore a principal objective of theor. immunol. Machine learning techniques achieve good results if substantial exptl. training data are available. Approaches based on structural information become necessary if sufficiently similar training data are unavailable for a specific MHC allele, although they have often been deemed to lack accuracy. In this study, we use a free energy method to rank the binding affinities of 12 diverse peptides bound by a class I MHC mol. HLA-A*02:01. The method is based on enhanced sampling of mol. dynamics calcns. in combination with a continuum solvent approxn. and includes ests. of the configurational entropy based on either a one or a three trajectory protocol. It produces precise and reproducible free energy ests. which correlate well with exptl. measurements. If the results are combined with an amino acid hydrophobicity scale, then an extremely good ranking of peptide binding affinities emerges. Our approach is rapid, robust, and applicable to a wide range of ligand-receptor interactions without further adjustment.
- 48Wright, D. W.; Hall, B. A.; Kenway, O. A.; Jha, S.; Coveney, P. V. Computing Clinically Relevant Binding Free Energies of HIV-1 Protease Inhibitors. J. Chem. Theory Comput. 2014, 10, 1228– 1241, DOI: 10.1021/ct400703748https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXht12ltrk%253D&md5=56bc7e7c8f6bbdd694bfc76c20dcec63Computing Clinically Relevant Binding Free Energies of HIV-1 Protease InhibitorsWright, David W.; Hall, Benjamin A.; Kenway, Owain A.; Jha, Shantenu; Coveney, Peter V.Journal of Chemical Theory and Computation (2014), 10 (3), 1228-1241CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The use of mol. simulation to est. the strength of macromol. binding free energies is becoming increasingly widespread, with goals ranging from lead optimization and enrichment in drug discovery to personalizing or stratifying treatment regimes. To realize the potential of such approaches to predict new results, not merely to explain previous exptl. findings, it is necessary that the methods used are reliable and accurate, and that their limitations are thoroughly understood. However, the computational cost of atomistic simulation techniques such as mol. dynamics (MD) has meant that until recently little work has focused on validating and verifying the available free energy methodologies, with the consequence that many of the results published in the literature are not reproducible. Here, we present a detailed anal. of two of the most popular approx. methods for calcg. binding free energies from mol. simulations, mol. mechanics Poisson-Boltzmann surface area (MMPBSA) and mol. mechanics generalized Born surface area (MMGBSA), applied to the nine FDA-approved HIV-1 protease inhibitors. Our results show that the values obtained from replica simulations of the same protease-drug complex, differing only in initially assigned atom velocities, can vary by as much as 10 kcal mol-1, which is greater than the difference between the best and worst binding inhibitors under investigation. Despite this, anal. of ensembles of simulations producing 50 trajectories of 4 ns duration leads to well converged free energy ests. For seven inhibitors, we find that with correctly converged normal mode ests. of the configurational entropy, we can correctly distinguish inhibitors in agreement with exptl. data for both the MMPBSA and MMGBSA methods and thus have the ability to rank the efficacy of binding of this selection of drugs to the protease (no account is made for free energy penalties assocd. with protein distortion leading to the over estn. of the binding strength of the two largest inhibitors ritonavir and atazanavir). We obtain improved rankings and ests. of the relative binding strengths of the drugs by using a novel combination of MMPBSA/MMGBSA with normal mode entropy ests. and the free energy of assocn. calcd. directly from simulation trajectories. Our work provides a thorough assessment of what is required to produce converged and hence reliable free energies for protein-ligand binding.
- 49Genheden, S.; Ryde, U. How to Obtain Statistically Converged MM/GBSA Results. J. Comput. Chem. 2009, 31, 837– 846, DOI: 10.1002/jcc.21366There is no corresponding record for this reference.
- 50Wan, S.; Bhati, A. P.; Zasada, S. J.; Wall, I.; Green, D.; Bamborough, P.; Coveney, P. V. Rapid and Reliable Binding Affinity Prediction of Bromodomain Inhibitors: A Computational Study. J. Chem. Theory Comput. 2017, 13, 784– 795, DOI: 10.1021/acs.jctc.6b0079450https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XitFektLnF&md5=713436084662420482684fb50db0832eRapid and Reliable Binding Affinity Prediction of Bromodomain Inhibitors: A Computational StudyWan, Shunzhou; Bhati, Agastya P.; Zasada, Stefan J.; Wall, Ian; Green, Darren; Bamborough, Paul; Coveney, Peter V.Journal of Chemical Theory and Computation (2017), 13 (2), 784-795CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)Binding free energies of bromodomain inhibitors are calcd. with recently formulated approaches, namely ESMACS (enhanced sampling of mol. dynamics with approxn. of continuum solvent) and TIES (thermodn. integration with enhanced sampling). A set of compds. is provided by GlaxoSmithKline, which represents a range of chem. functionality and binding affinities. The predicted binding free energies exhibit a good Spearman correlation of 0.78 with the exptl. data from the 3-trajectory ESMACS, and an excellent correlation of 0.92 from the TIES approach where applicable. Given access to suitable high end computing resources and a high degree of automation, the authors can compute individual binding affinities in a few hours with precisions no greater than 0.2 kcal/mol for TIES, and no larger than 0.34 kcal/mol and 1.71 kcal/mol for the 1- and 3-trajectory ESMACS approaches.
- 51Chen, F.; Liu, H.; Sun, H.; Pan, P.; Li, Y.; Li, D.; Hou, T. Assessing the Performance of the MM/PBSA and MM/GBSA Methods. 6. Capability to Predict Protein–Protein Binding Free Energies and Re-Rank Binding Poses Generated by Protein–Protein Docking. Phys. Chem. Chem. Phys. 2016, 18, 22129– 22139, DOI: 10.1039/C6CP03670H51https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XhtFKktbvP&md5=ad3658a355db86f1e7cd46f196e7f76eAssessing the performance of the MM/PBSA and MM/GBSA methods. 6. Capability to predict protein-protein binding free energies and re-rank binding poses generated by protein-protein dockingChen, Fu; Liu, Hui; Sun, Huiyong; Pan, Peichen; Li, Youyong; Li, Dan; Hou, TingjunPhysical Chemistry Chemical Physics (2016), 18 (32), 22129-22139CODEN: PPCPFQ; ISSN:1463-9076. (Royal Society of Chemistry)Understanding protein-protein interactions (PPIs) is quite important to elucidate crucial biol. processes and even design compds. that interfere with PPIs with pharmaceutical significance. Protein-protein docking can afford the at. structural details of protein-protein complexes, but the accurate prediction of the three-dimensional structures for protein-protein systems is still notoriously difficult due in part to the lack of an ideal scoring function for protein-protein docking. Compared with most scoring functions used in protein-protein docking, the Mol. Mechanics/Generalized Born Surface Area (MM/GBSA) and Mol. Mechanics/Poisson Boltzmann Surface Area (MM/PBSA) methodologies are more theor. rigorous, but their overall performance for the predictions of binding affinities and binding poses for protein-protein systems has not been systematically evaluated. In this study, we first evaluated the performance of MM/PBSA and MM/GBSA to predict the binding affinities for 46 protein-protein complexes. On the whole, different force fields, solvation models, and interior dielec. consts. have obvious impacts on the prediction accuracy of MM/GBSA and MM/PBSA. The MM/GBSA calcns. based on the ff02 force field, the GB model developed by Onufriev et al. and a low interior dielec. const. (εin = 1) yield the best correlation between the predicted binding affinities and the exptl. data (rp = -0.647), which is better than MM/PBSA (rp = -0.523) and a no. of empirical scoring functions used in protein-protein docking (rp = -0.141 to -0.529). Then, we examd. the capability of MM/GBSA to identify the possible near-native binding structures from the decoys generated by ZDOCK for 43 protein-protein systems. The results illustrate that the MM/GBSA rescoring has better capability to distinguish the correct binding structures from the decoys than the ZDOCK scoring. Besides, the optimal interior dielec. const. of MM/GBSA for re-ranking docking poses may be detd. by analyzing the characteristics of protein-protein binding interfaces. Considering the relatively high prediction accuracy and low computational cost, MM/GBSA may be a good choice for predicting the binding affinities and identifying correct binding structures for protein-protein systems.
- 52Sun, H.; Li, Y.; Shen, M.; Tian, S.; Xu, L.; Pan, P.; Guan, Y.; Hou, T. Assessing the Performance of MM/PBSA and MM/GBSA Methods. 5. Improved Docking Performance Using High Solute Dielectric Constant MM/GBSA and MM/PBSA Rescoring. Phys. Chem. Chem. Phys. 2014, 16, 22035– 22045, DOI: 10.1039/C4CP03179B52https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhtlOjsbfJ&md5=3cf9751ee3c05dd7aa6fa27f591fba9eAssessing the performance of MM/PBSA and MM/GBSA methods. 5. Improved docking performance using high solute dielectric constant MM/GBSA and MM/PBSA rescoringSun, Huiyong; Li, Youyong; Shen, Mingyun; Tian, Sheng; Xu, Lei; Pan, Peichen; Guan, Yan; Hou, TingjunPhysical Chemistry Chemical Physics (2014), 16 (40), 22035-22045CODEN: PPCPFQ; ISSN:1463-9076. (Royal Society of Chemistry)With the rapid development of computational techniques and hardware, more rigorous and precise theor. models have been used to predict the binding affinities of a large no. of small mols. to biomols. By employing continuum solvation models, the MM/GBSA and MM/PBSA methodologies achieve a good balance between low computational cost and reasonable prediction accuracy. The authors have thoroughly studied the effects of interior dielec. const., mol. dynamics (MD) simulations, and the no. of top-scored docking poses on the performance of the MM/GBSA and MM/PBSA rescoring of docking poses for three tyrosine kinases, including ABL, ALK, and BRAF. Overall, the MM/PBSA and MM/GBSA rescoring achieved comparative accuracies based on a relatively higher solute (or interior) dielec. const. (i.e. ε = 2, or 4), and could markedly improve the screening power and ranking power given by Autodock. Moreover, with a relatively higher solute dielec. const., the MM/PBSA or MM/GBSA rescoring based on the best scored docking poses and the multiple top-scored docking poses gave similar predictions, implying that much computational cost can be saved by considering the best scored docking poses only. Besides, compared with the rescoring based on the minimized structures, the rescoring based on the MD simulations might not be completely necessary due to its negligible impact on the docking performance. Considering the much higher computational demand of MM/PBSA, MM/GBSA with a high solute dielec. const. (ε = 2 or 4) is recommended for the virtual screening of tyrosine kinases.
- 53Wang, C.; Nguyen, P. H.; Pham, K.; Huynh, D.; Le, T. B. N.; Wang, H.; Ren, P.; Luo, R. Calculating Protein–Ligand Binding Affinities with MMPBSA: Method and Error Analysis. J. Comput. Chem. 2016, 2436– 2446, DOI: 10.1002/jcc.2446753https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28Xhtlalsb3L&md5=a8131b248b24f7f8d1285c4867c39b07Calculating protein-ligand binding affinities with MMPBSA: Method and error analysisWang, Changhao; Nguyen, Peter H.; Pham, Kevin; Huynh, Danielle; Le, Thanh-Binh Nancy; Wang, Hongli; Ren, Pengyu; Luo, RayJournal of Computational Chemistry (2016), 37 (27), 2436-2446CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)Mol. Mechanics Poisson-Boltzmann Surface Area (MMPBSA) methods have become widely adopted in estg. protein-ligand binding affinities due to their efficiency and high correlation with expt. Here different computational alternatives were studied to assess their impact to the agreement of MMPBSA calcns. with expt. Seven receptor families with both high-quality crystal structures and binding affinities were selected. First the performance of nonpolar solvation models was studied and the modern approach that sep. models hydrophobic and dispersion interactions dramatically reduces RMSD's of computed relative binding affinities. The numerical setup of the Poisson-Boltzmann methods was analyzed next. The impact of grid spacing to the quality of MMPBSA calcns. is small: the numerical error at the grid spacing of 0.5 Å is already small enough to be negligible. The impact of different at. radius sets and different mol. surface definitions was further analyzed and weak influences were found on the agreement with expt. The influence of solute dielec. const. was also analyzed: a higher dielec. const. generally improves the overall agreement with expt., esp. for highly charged binding pockets. Also the converged simulations caused slight redn. in the agreement with expt. Finally the direction of estg. abs. binding free energies was briefly explored. Upon correction of the binding-induced rearrangement free energy and the binding entropy lost, the errors in abs. binding affinities were also reduced dramatically when the modern nonpolar solvent model was used, although further developments were apparently necessary to further improve the MMPBSA methods. © 2016 Wiley Periodicals, Inc.
- 54Liu, X.; Peng, L.; Zhou, Y.; Zhang, Y.; Zhang, J. Z. H. Computational Alanine Scanning with Interaction Entropy for Protein–Ligand Binding Free Energies. J. Chem. Theory Comput. 2018, 14, 1772– 1780, DOI: 10.1021/acs.jctc.7b0129554https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXit1ykur8%253D&md5=c808e0f9bf3d32fc8ce9ddade1300048Computational Alanine Scanning with Interaction Entropy for Protein-Ligand Binding Free EnergiesLiu, Xiao; Peng, Long; Zhou, Yifan; Zhang, Youzhi; Zhang, John Z. H.Journal of Chemical Theory and Computation (2018), 14 (3), 1772-1780CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)In protein-ligand binding, only a few residues contribute significantly to the ligand binding. Quant. characterization of binding free energies of specific residues in protein-ligand binding is extremely useful in our understanding of drug resistance and rational drug design. Here, we present an alanine scanning approach combined with an efficient interaction entropy method to compute residue-specific protein-ligand binding free energies in protein-drug binding. In the current approach, the entropic components in the free energies of all residues binding to the ligand are explicitly computed from just a single trajectory mol. dynamics (MD) simulation by using the interaction entropy method. In this approach the entropic contribution to binding free energy is detd. from fluctuations of individual residue-ligand interaction energies contained in the MD trajectory. The calcd. residue-specific binding free energies give relative values between those for ligand binding to the wild-type protein and those to the mutants when specific results mutated to alanine. Computational study for the binding of 2 classes of drugs (1st and 2nd generation drugs) to the target protein, anaplastic leukemia kinase (ALK) and its mutants was performed. Important or hot spot residues with large contributions to the total binding energy were quant. characterized and the mutational effect for the loss of binding affinity for the 1st-generation drug was explained. Finally, it is very interesting to note that the sum of those individual residue-specific binding free energies were in quite good agreement with the exptl. measured total binding free energies for this protein-ligand system.
- 55Vangone, A.; Spinelli, R.; Scarano, V.; Cavallo, L.; Oliva, R. COCOMAPS: A Web Application to Analyze and Visualize Contacts at the Interface of Biomolecular Complexes. Bioinformatics 2011, 27, 2915– 2916, DOI: 10.1093/bioinformatics/btr48455https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXht12qsLvL&md5=67683342e85e9f5ae9637ac55bbe7dcbCOCOMAPS: a web application to analyze and visualize contacts at the interface of biomolecular complexesVangone, Anna; Spinelli, Raffaele; Scarano, Vittorio; Cavallo, Luigi; Oliva, RominaBioinformatics (2011), 27 (20), 2915-2916CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)Summary: Herein we present COCOMAPS, a novel tool for analyzing, visualizing and comparing the interface in protein-protein and protein-nucleic acids complexes. COCOMAPS combines traditional analyses and 3D visualization of the interface with the effectiveness of intermol. contact maps. Availability: COCOMAPS is accessible as a public web tool at http://www.molnac.unisa.it/BioTools/cocomaps Contact: [email protected]; [email protected].
- 56Ramos, R. M.; Moreira, I. S. Computational Alanine Scanning Mutagenesis─An Improved Methodological Approach for Protein–DNA Complexes. J. Chem. Theory Comput. 2013, 9, 4243– 4256, DOI: 10.1021/ct400387r56https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXht1Wis73K&md5=8b15ee28b995791e18447c2005d2ce8bComputational Alanine Scanning Mutagenesis-An Improved Methodological Approach for Protein-DNA ComplexesRamos, Rui M.; Moreira, Irina S.Journal of Chemical Theory and Computation (2013), 9 (9), 4243-4256CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)Proteins and protein-based complexes are the basis of many key systems in nature and have been the subject of intense research in the last decades, in an attempt to acquire comprehensive knowledge of reactions that take place in nature. Computational Alanine Scanning Mutagenesis approaches have been extensively used in the study of protein interfaces and in the detn. of the most important residues for complex formation, the Hot-spots. However, as it is usually applied to the study of protein-protein interfaces, the authors tried to modify and apply it to the study of protein-DNA interfaces, which are also crucial in nature but have not been the subject of as much research. The authors carry out MD simulations of seven protein-DNA complexes and tested the influence of the variation of different parameters on the detn. of the binding free energy terms (ΔΔGbinding) of 78 mutations: solvent representation, internal dielec. const., Linear and Nonlinear Poisson-Boltzmann equation, Generalized Born model, simulation time, no. of structures analyzed, no. of MD trajectories, force field used, and energetic terms involved. Overall, this new approach gave an av. error of 1.55 kcal/mol, and P, R, F1, accuracy, and specificity values of 0.78, 0.50, 0.61, 0.77, and 0.92, resp. This improved computational alanine scanning mutagenesis approach may serve as a tool to explore the behavior of this important class of complexes.
- 57Moreira, I. S.; Fernandes, P. A.; Ramos, M. J. Computational Alanine Scanning Mutagenesis─An Improved Methodological Approach. J. Comput. Chem. 2007, 28, 644– 654, DOI: 10.1002/jcc.2056657https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXhsVWntb8%253D&md5=54074b0d0d9b0a28744f3d27697a266cComputational alanine scanning mutagenesis - an improved methodological approachMoreira, Irina S.; Fernandes, Pedro A.; Ramos, Maria J.Journal of Computational Chemistry (2007), 28 (3), 644-654CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)Alanine scanning mutagenesis of protein-protein interfacial residues can be applied to a wide variety of protein complexes to understand the structural and energetic characteristics of the hot-spots. Binding free energies have been estd. with reasonable accuracy with empirical methods, such as Mol. Mechanics/Poisson-Boltzmann surface area (MM-PBSA), and with more rigorous computational approaches like Free Energy Perturbation (FEP) and Thermodn. Integration (TI). The main objective of this work is the development of an improved methodol. approach, with less computational cost, that predicts accurately differences in binding free energies between the wild-type and alanine mutated complexes (ΔΔGbinding). The method was applied to three complexes, and a mean unsigned error of 0.80 kcal/mol was obtained in a set of 46 mutations. The computational method presented here achieved an overall success rate of 80% and an 82% success rate in residues for which alanine mutation causes an increase in the binding free energy > 2.0 kcal/mol (warm- and hot-spots). This fully atomistic computational methodol. approach consists in a computational Mol. Dynamics simulation protocol performed in a continuum medium using the Generalized Born model. A set of three different internal dielec. consts., to mimic the different degree of relaxation of the interface when different types of amino acids are mutated for alanine, have to be used for the proteins, depending on the type of amino acid that is mutated. This method permits a systematic scanning mutagenesis of protein-protein interfaces and it is capable of anticipating the exptl. results of mutagenesis, thus guiding new exptl. investigations.
- 58Martins, S. A.; Perez, M. A. S.; Moreira, I. S.; Sousa, S. F.; Ramos, M. J.; Fernandes, P. A. Computational Alanine Scanning Mutagenesis: MM-PBSA vs TI. J. Chem. Theory Comput. 2013, 9, 1311– 1319, DOI: 10.1021/ct400037258https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXitlCiurs%253D&md5=8a790e3a8bce51eeb33993d7c84c2112Computational Alanine Scanning Mutagenesis: MM-PBSA vs TIMartins, Silvia A.; Perez, Marta A. S.; Moreira, Irina S.; Sousa, Sergio F.; Ramos, M. J.; Fernandes, P. A.Journal of Chemical Theory and Computation (2013), 9 (3), 1311-1319CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)Understanding protein-protein assocn. and being able to det. the crucial residues responsible for their assocn. (hot-spots) is a key issue with huge practical applications such as rational drug design and protein engineering. A variety of computational methods exist to detect hot-spots residues, but the development of a fast and accurate quant. alanine scanning mutagenesis (ASM) continues to be crucial. Using four protein-protein complexes, we have compared a variation of the std. computational ASM protocol developed at our group, based on the Mol. Mechanics/Poisson-Boltzmann Surface Area (MM-PBSA) approach, against Thermodn. Integration (TI), a well-known and accurate but computationally expensive method. To compare the efficiency and the accuracy of the two methods, we have calcd. the protein-protein binding free energy differences upon alanine mutation of interfacial residues (ΔΔGbind). In relation to the exptl. ΔΔGbind values, the av. error obtained with TI was 1.53 kcal/mol, while the ASM protocol resulted in an av. error of 1.18 kcal/mol. The results demonstrate that the much faster ASM protocol gives results at the same level of accuracy as the TI method but at a fraction of the computational time required to run TI. This ASM protocol is therefore a strong and efficient alternative to the systematic evaluation of protein-protein interfaces, involving hundreds of amino acid residues in search of hot-spots.
- 59Simões, I. C. M.; Costa, I. P. D.; Coimbra, J. T. S.; Ramos, M. J.; Fernandes, P. A. New Parameters for Higher Accuracy in the Computation of Binding Free Energy Differences upon Alanine Scanning Mutagenesis on Protein-Protein Interfaces. J. Chem. Inf. Model. 2017, 57, 60– 72, DOI: 10.1021/acs.jcim.6b0037859https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XitVKqtLzM&md5=5faedefbb4899a041a0c3e7a350709ddNew Parameters for Higher Accuracy in the Computation of Binding Free Energy Differences upon Alanine Scanning Mutagenesis on Protein-Protein InterfacesSimoes, Ines C. M.; Costa, Ines P. D.; Coimbra, Joao T. S.; Ramos, Maria J.; Fernandes, Pedro A.Journal of Chemical Information and Modeling (2017), 57 (1), 60-72CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)Knowing how proteins make stable complexes enables the development of inhibitors to preclude protein-protein (P:P) binding. The identification of the specific interfacial residues that contribute the most for protein binding, denominated as hot-spots, is thus crit. Here the authors refine a computational alanine scanning mutagenesis protocol, based on a residue-dependent dielec. const. version of the Mol. Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) method. The authors used a large data set of structurally diverse P:P complexes to re-define the residue-dependent dielec. consts. used in the calcn. of binding free energies. The accuracy of the method was validated through comparison with exptl. data, considering the per-residue P:P binding free energy (ΔΔGbinding) differences upon alanine mutation. Different protocols were tested, i.e. a geometry optimization protocol and three mol. dynamics (MD) protocols: (1) one using explicit water mols., (2) another with an implicit solvation model, and (3) a third where the authors have carried out an accelerated MD with explicit water mols. Using a set of protein dielec. consts. (within the range of 1 to 20) the dielec. consts. of 7 for non-polar and polar residues and 11 for charged residues (and histidine) provide optimal ΔΔGbinding predictions. An overall mean unsigned error (MUE) of 1.4 kcal.mol-1 relative to expt. was achieved in 210 mutations only with geometry optimization, which was further reduced with MD simulations (MUE of 1.1 kcal.mol-1 for the explicit solvent MD). This recalibrated method allows for a better computational identification of hot-spots, avoiding expensive and time-consuming expts. or thermodn. integration/ free energy perturbation/ uBAR calcns., and will hopefully help new drug discovery campaigns in their quest of searching spots of interest for binding small drug-like mols. at P:P interfaces.
- 60Sheng, Y.; Yin, Y.; Ma, Y.; Ding, H. Improving the Performance of MM/PBSA in Protein–Protein Interactions via the Screening Electrostatic Energy. J. Chem. Inf. Model. 2021, 61, 2454– 2462, DOI: 10.1021/acs.jcim.1c0041060https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3MXpvFKnsrs%253D&md5=7532ed49ab5f2d8cf8b03aac1f73b199Improving the Performance of MM/PBSA in Protein-Protein Interactions via the Screening Electrostatic EnergySheng, Yan-jing; Yin, Yue-wen; Ma, Yu-qiang; Ding, Hong-mingJournal of Chemical Information and Modeling (2021), 61 (5), 2454-2462CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)Accurate calcn. of protein-protein binding free energy is of great importance in biol. and medical science, yet it remains a hugely challenging problem. In this work, we develop a new strategy in which a screened electrostatic energy (i.e., adding an exponential damping factor to the Coulombic interaction energy) is used within the framework of the mol. mechanics/Poisson-Boltzmann surface area (MM/PBSA) method. Our results show that the Pearson correlation coeff. in the modified MM/PBSA is over 0.70, which is much better than that in the std. MM/PBSA, esp. in the Amber14SB force field. In particular, the performance of the std. MM/PBSA is very poor in a system where the proteins carry like charges. Moreover, we also calcd. the mean abs. error (MAE) between the calcd. and exptl. ΔG values and found that the MAE in the modified MM/PBSA was indeed much smaller than that in the std. MM/PBSA. Furthermore, the effect of the dielec. const. of the proteins and the salt conditions on the results was also investigated. The present study highlights the potential power of the modified MM/PBSA for accurately predicting the binding energy in highly charged biosystems.
- 61Pierce, B. G.; Weng, Z. A Flexible Docking Approach for Prediction of T Cell Receptor-Peptide-MHC Complexes. Protein Sci. 2013, 22, 35– 46, DOI: 10.1002/pro.218161https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhvVeksrjE&md5=300f9098326bcc6d5e1e8a660f5160ddA flexible docking approach for prediction of T cell receptor-peptide-MHC complexesPierce, Brian G.; Weng, ZhipingProtein Science (2013), 22 (1), 35-46CODEN: PRCIEI; ISSN:1469-896X. (Wiley-Blackwell)T cell receptors (TCRs) are immune proteins that specifically bind to antigenic mols., which are often foreign peptides presented by major histocompatibility complex proteins (pMHCs), playing a key role in the cellular immune response. To advance our understanding and modeling of this dynamic immunol. event, we assembled a protein-protein docking benchmark consisting of 20 structures of crystd. TCR/pMHC complexes for which unbound structures exist for both TCR and pMHC. We used our benchmark to compare predictive performance using several flexible and rigid backbone TCR/pMHC docking protocols. Our flexible TCR docking algorithm, TCRFlexDock, improved predictive success over the fixed backbone protocol, leading to near-native predictions for 80% of the TCR/pMHC cases among the top 10 models, and 100% of the cases in the top 30 models. We then applied TCRFlexDock to predict the two distinct docking modes recently described for a single TCR bound to two different antigens, and tested several protein modeling scoring functions for prediction of TCR/pMHC binding affinities. This algorithm and benchmark should enable future efforts to predict, and design of uncharacterized TCR/pMHC complexes.
- 62Jensen, K. K.; Rantos, V.; Jappe, E. C.; Olsen, T. H.; Jespersen, M. C.; Jurtz, V.; Jessen, L. E.; Lanzarotti, E.; Mahajan, S.; Peters, B.; Nielsen, M.; Marcatili, P. TCRpMHCmodels: Structural Modelling of TCR-PMHC Class I Complexes. Sci. Rep. 2019, 9, 14530 DOI: 10.1038/s41598-019-50932-462https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BB3MnmvVSktA%253D%253D&md5=3d29620d5f2b1aeec26f26b940d4df18TCRpMHCmodels: Structural modelling of TCR-pMHC class I complexesJensen Kamilla Kjaergaard; Rantos Vasileios; Jappe Emma Christine; Olsen Tobias Hegelund; Jespersen Martin Closter; Jessen Leon Eyrich; Nielsen Morten; Marcatili Paolo; Rantos Vasileios; Jappe Emma Christine; Jurtz Vanessa; Lanzarotti Esteban; Nielsen Morten; Mahajan Swapnil; Peters Bjoern; Peters BjoernScientific reports (2019), 9 (1), 14530 ISSN:.The interaction between the class I major histocompatibility complex (MHC), the peptide presented by the MHC and the T-cell receptor (TCR) is a key determinant of the cellular immune response. Here, we present TCRpMHCmodels, a method for accurate structural modelling of the TCR-peptide-MHC (TCR-pMHC) complex. This TCR-pMHC modelling pipeline takes as input the amino acid sequence and generates models of the TCR-pMHC complex, with a median Cα RMSD of 2.31 ÅA. TCRpMHCmodels significantly outperforms TCRFlexDock, a specialised method for docking pMHC and TCR structures. TCRpMHCmodels is simple to use and the modelling pipeline takes, on average, only two minutes. Thanks to its ease of use and high modelling accuracy, we expect TCRpMHCmodels to provide insights into the underlying mechanisms of TCR and pMHC interactions and aid in the development of advanced T-cell-based immunotherapies and rational design of vaccines. The TCRpMHCmodels tool is available at http://www.cbs.dtu.dk/services/TCRpMHCmodels/ .
- 63Wright, D. W.; Wan, S.; Meyer, C.; van Vlijmen, H.; Tresadern, G.; Coveney, P. V. Application of ESMACS Binding Free Energy Protocols to Diverse Datasets: Bromodomain-Containing Protein 4. Sci. Rep. 2019, 9, 6017 DOI: 10.1038/s41598-019-41758-163https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BB3M%252FkvFaqsQ%253D%253D&md5=b62c5a234b09797af7f8e21846c7815fApplication of ESMACS binding free energy protocols to diverse datasets: Bromodomain-containing protein 4Wright David W; Wan Shunzhou; Coveney Peter V; Meyer Christophe; van Vlijmen Herman; Tresadern GaryScientific reports (2019), 9 (1), 6017 ISSN:.As the application of computational methods in drug discovery pipelines becomes more widespread it is increasingly important to understand how reproducible their results are and how sensitive they are to choices made in simulation setup and analysis. Here we use ensemble simulation protocols, termed ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent), to investigate the sensitivity of the popular molecular mechanics Poisson-Boltzmann surface area (MMPBSA) methodology. Using the bromodomain-containing protein 4 (BRD4) system bound to a diverse set of ligands as our target, we show that robust rankings can be produced only through combining ensemble sampling with multiple trajectories and enhanced solvation via an explicit ligand hydration shell.
- 64Mikulskis, P.; Genheden, S.; Ryde, U. Effect of Explicit Water Molecules on Ligand-Binding Affinities Calculated with the MM/GBSA Approach. J. Mol. Model. 2014, 20, 2273 DOI: 10.1007/s00894-014-2273-x64https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC2cjmvFSltQ%253D%253D&md5=9dca49d75be826f8dd37eca977d68fdaEffect of explicit water molecules on ligand-binding affinities calculated with the MM/GBSA approachMikulskis Paulius; Genheden Samuel; Ryde UlfJournal of molecular modeling (2014), 20 (6), 2273 ISSN:.We tested different approaches to including the effect of binding-site water molecules for ligand-binding affinities within the MM/GBSA approach (molecular mechanics combined with generalised Born and surface-area solvation). As a test case, we studied the binding of nine phenol analogues to ferritin. The effect of water molecules mediating the interaction between the receptor and the ligand can be studied by considering a few water molecules as a part of the receptor. We extended previous methods by allowing for a variable number of water molecules in the binding site. The effect of displaced water molecules can also be considered within the MM/GBSA philosophy by calculating the affinities of binding-site water molecules, both before and after binding of the ligand. To obtain proper energies, both the water molecules and the ligand need then to be converted to non-interacting ghost molecules and a single-average approach (i.e., the same structures are used for bound and unbound states) based on the simulations of both the complex and the free receptor can be used to improve the precision. The only problem is to estimate the free energy of an unbound water molecule. With an experimental estimate of this parameter, promising results were obtained for our test case.
- 65Maffucci, I.; Hu, X.; Fumagalli, V.; Contini, A. An Efficient Implementation of the Nwat-MMGBSA Method to Rescore Docking Results in Medium-Throughput Virtual Screenings. Front. Chem. 2018, 6, 43 DOI: 10.3389/fchem.2018.0004365https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXit1egsbrN&md5=b2925a1d0f9323f99cb4c93af53ced04An efficient implementation of the nwat-mmgbsa method to rescore docking results in medium-throughput virtual screeningsMaffucci, Irene; Hu, Xiao; Fumagalli, Valentina; Contini, AlessandroFrontiers in Chemistry (Lausanne, Switzerland) (2018), 6 (), 43/1-43/14CODEN: FCLSAA; ISSN:2296-2646. (Frontiers Media S.A.)Nwat-MMGBSA is a variant of MM-PB/GBSA based on the inclusion of a no. of explicit water mols. that are the closest to the ligand in each frame of a mol. dynamics trajectory. This method demonstrated improved correlations between calcd. and exptl. binding energies in both protein-protein interactions and ligand-receptor complexes, in comparison to the std. MM-GBSA. A protocol optimization, aimed to maximize efficacy and efficiency, is discussed here considering penicillopepsin, HIV1-protease, and BCL-XL as test cases. Calcns. were performed in triplicates on both classic HPC environments and on std. workstations equipped by a GPU card, evidencing no statistical differences in the results. No relevant differences in correlation to expts. were also obsd. when performing Nwat-MMGBSA calcns. on 4 or 1 ns long trajectories. A fully automatic workflow for structure-based virtual screening, performing from library set-up to docking and Nwat-MMGBSA rescoring, has then been developed. The protocol has been tested against no rescoring or std. MM-GBSA rescoring within a retrospective virtual screening of inhibitors of AmpC β-lactamase and of the Rac1-Tiam1 protein-protein interaction. In both cases, Nwat-MMGBSA rescoring provided a statistically significant increase in the ROC AUCs of between 20 and 30%, compared to docking scoring or to std. MM-GBSA rescoring.
- 66Peccati, F.; Jiménez-Osés, G. Enthalpy–Entropy Compensation in Biomolecular Recognition: A Computational Perspective. ACS Omega 2021, 6, 11122– 11130, DOI: 10.1021/acsomega.1c0048566https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3MXptVCnsbc%253D&md5=6dc6836f79c336f41671dd615e119a81Enthalpy-Entropy Compensation in Biomolecular Recognition: A Computational PerspectivePeccati, Francesca; Jimenez-Oses, GonzaloACS Omega (2021), 6 (17), 11122-11130CODEN: ACSODF; ISSN:2470-1343. (American Chemical Society)A review. This mini-review provides an overview of the enthalpy-entropy compensation phenomenon in the simulation of biomacromol. recognition, with particular emphasis on ligand binding. We approach this complex phenomenon from the point of view of practical computational chem. Without providing a detailed description of the plethora of existing methodologies already reviewed in depth elsewhere, we present a series of examples to illustrate different approaches to interpret and predict compensation phenomena at an atomistic level, which is far from trivial to predict using canonical, classic textbook assumptions.
- 67Sun, H.; Duan, L.; Chen, F.; Liu, H.; Wang, Z.; Pan, P.; Zhu, F.; Zhang, J. Z. H.; Hou, T. Assessing the Performance of MM/PBSA and MM/GBSA Methods. 7. Entropy Effects on the Performance of End-Point Binding Free Energy Calculation Approaches. Phys. Chem. Chem. Phys. 2018, 20, 14450– 14460, DOI: 10.1039/C7CP07623A67https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXos1Omsrg%253D&md5=04109321f5c9c739a408d439fed21bdaAssessing the performance of MM/PBSA and MM/GBSA methods. 7. Entropy effects on the performance of end-point binding free energy calculation approachesSun, Huiyong; Duan, Lili; Chen, Fu; Liu, Hui; Wang, Zhe; Pan, Peichen; Zhu, Feng; Zhang, John Z. H.; Hou, TingjunPhysical Chemistry Chemical Physics (2018), 20 (21), 14450-14460CODEN: PPCPFQ; ISSN:1463-9076. (Royal Society of Chemistry)Entropy effects play an important role in drug-target interactions, but the entropic contribution to ligand-binding affinity is often neglected by end-point binding free energy calcn. methods, such as MM/GBSA and MM/PBSA, due to the expensive computational cost of normal mode anal. (NMA). Here, the authors systematically investigated entropy effects on the prediction power of MM/GBSA and MM/PBSA using >1500 protein-ligand systems and six representative AMBER force fields. Two computationally efficient methods, including NMA based on truncated structures and the interaction entropy approach, were used to est. the entropic contributions to ligand-target binding free energies. In terms of the overall accuracy, the authors found that, for the minimized structures, in most cases the inclusion of the conformational entropies predicted by truncated NMA (enthalpynmode_min_9Å) compromises the overall accuracy of MM/GBSA and MM/PBSA compared with the enthalpies calcd. based on the minimized structures (enthalpymin). However, for the MD trajectories, the binding free energies can be improved by the inclusion of the conformation entropies predicted by either truncated-NMA for a relatively high dielec. const. (εin = 4) or the interaction entropy method for εin = 1-4. In terms of reproducing the abs. binding free energies, the binding free energies estd. by including the truncated-NMA entropies based on the MD trajectories (ΔGnmode_md_9Å) give the lowest av. abs. deviations against the exptl. data among all the tested strategies for both MM/GBSA and MM/PBSA. Although the inclusion of the truncated NMA based on the MD trajectories (ΔGnmode_md_9Å) for a relatively high dielec. const. gave the overall best result and the lowest av. abs. deviations against the exptl. data (for the ff03 force field), it needs too much computational time. Alternatively, considering that the interaction entropy method does not incur any addnl. computational cost and can give comparable (at high dielec. const., εin = 4) or even better (at low dielec. const., εin = 1-2) results than the truncated-NMA entropy (ΔGnmode_md_9Å), the interaction entropy approach is recommended to est. the entropic component for MM/GBSA and MM/PBSA based on MD trajectories, esp. for a diverse dataset. Furthermore, the authors compared the predictions of MM/GBSA with six different AMBER force fields. The results show that the ff03 force field (ff03 for proteins and gaff with AM1-BCC charges for ligands) performs the best, but the predictions given by the tested force fields are comparable, implying that the MM/GBSA predictions are not very sensitive to force fields.
- 68Genheden, S.; Kuhn, O.; Mikulskis, P.; Hoffmann, D.; Ryde, U. The Normal-Mode Entropy in the MM/GBSA Method: Effect of System Truncation, Buffer Region, and Dielectric Constant. J. Chem. Inf. Model. 2012, 52, 2079– 2088, DOI: 10.1021/ci300191968https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhtVKlt7%252FP&md5=a82e8b710c3231bfcfc09f25fe6b235dThe Normal-Mode Entropy in the MM/GBSA Method: Effect of System Truncation, Buffer Region, and Dielectric ConstantGenheden, Samuel; Kuhn, Oliver; Mikulskis, Paulius; Hoffmann, Daniel; Ryde, UlfJournal of Chemical Information and Modeling (2012), 52 (8), 2079-2088CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)We have performed a systematic study of the entropy term in the MM/GBSA (mol. mechanics combined with generalized Born and surface-area solvation) approach to calc. ligand-binding affinities. The entropies are calcd. by a normal-mode anal. of harmonic frequencies from minimized snapshots of mol. dynamics simulations. For computational reasons, these calcns. have normally been performed on truncated systems. We have studied the binding of eight inhibitors of blood clotting factor Xa, nine ligands of ferritin, and two ligands of HIV-1 protease and show that removing protein residues with distances larger than 8-16 Å to the ligand, including a 4 Å shell of fixed protein residues and water mols., change the abs. entropies by 1-5 kJ/mol on av. However, the change is systematic, so relative entropies for different ligands change by only 0.7-1.6 kJ/mol on av. Consequently, entropies from truncated systems give relative binding affinities that are identical to those obtained for the whole protein within statistical uncertainty (1-2 kJ/mol). We have also tested to use a distance-dependent dielec. const. in the minimization and frequency calcn. (ε = 4r), but it typically gives slightly different entropies and poorer binding affinities. Therefore, we recommend entropies calcd. with the smallest truncation radius (8 Å) and ε =1. Such an approach also gives an improved precision for the calcd. binding free energies.
- 69Suárez, D.; Díaz, N. Ligand Strain and Entropic Effects on the Binding of Macrocyclic and Linear Inhibitors: Molecular Modeling of Penicillopepsin Complexes. J. Chem. Inf. Model. 2017, 57, 2045– 2055, DOI: 10.1021/acs.jcim.7b0035569https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXht1WgsLfL&md5=c83605b794ab1615e50948f18f15e558Ligand Strain and Entropic Effects on the Binding of Macrocyclic and Linear Inhibitors: Molecular Modeling of Penicillopepsin ComplexesSuarez, Dimas; Diaz, NataliaJournal of Chemical Information and Modeling (2017), 57 (8), 2045-2055CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)Using extensive mol. dynamics simulations, we investigate the structure and dynamics of the complexes formed between penicillopepsin and 2 peptidomimetic inhibitors: a linear compd., isovaleryl(P4)-valine(P3)-asparagine(P2)-leucine(P1)-phosphonate-phenylalanine(P1'), and its macrocyclic analog that includes a methylene bridge between the Asn(P2) and Phe(P1') side-chains. The macrocyclic inhibitor, which has a 420-fold larger affinity than that of the acyclic inhibitor, has been considered to lower the entropic penalty for binding. To better understand this binding preference, the soln. structure of the inhibitors was studied by mol. dynamics simulations. Subsequently, we assessed the influence of the enzyme/inhibitor contacts, the enzyme-induced inhibitor strain, the variation of the ligand configurational entropy, and the enzyme reorganization by combining mol.-mechanics Poisson-Boltzmann surface area and normal mode calcns. with the estn. of the conformational entropy of the inhibitors. We found that there was no relevant entropic stabilization on the binding of the cyclic inhibitor with respect to the acyclic analog because the methylene bridge did not reduce appreciably the conformational flexibility of the free inhibitor. The most important factors explaining the larger affinity of the macrocyclic inhibitor were the conformational filtering and the lower ligand strain induced by the methylene bridge.
- 70Yan, Y.; Yang, M.; Ji, C. G.; Zhang, J. Z. H. Interaction Entropy for Computational Alanine Scanning. J. Chem. Inf. Model. 2017, 57, 1112– 1122, DOI: 10.1021/acs.jcim.6b0073470https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXlvFOqsr8%253D&md5=ae06608eeaa594d31cc2ac9d1b66487fInteraction Entropy for Computational Alanine ScanningYan, Yuna; Yang, Maoyou; Ji, Chang G.; Zhang, John Z. H.Journal of Chemical Information and Modeling (2017), 57 (5), 1112-1122CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)The theor. calcn. of protein-protein binding free energy is a grand challenge in computational biol. Accurate prediction of crit. residues along with their specific and quant. contributions to protein-protein binding free energy is extremely helpful to reveal binding mechanisms and identify drug-like mols. that alter protein-protein interactions. In this paper, we propose an interaction entropy approach combined with the MM/GBSA method for solvation to compute residue-specific protein-protein binding free energy. In the current approach, the entropic loss in binding free energy of individual residues is explicitly computed from MD simulation by using the interaction entropy method. In this approach the entropic contribution to binding free energy is detd. from fluctuation of the interaction in MD simulation. Studies for an extensive set of realistic protein-protein interaction systems showed that by including the entropic contribution, the computed residue-specific binding free energies are in better agreement with the corresponding exptl. data.
- 71Chen, J.; Wang, X.; Zhang, J. Z. H. H.; Zhu, T. Effect of Substituents in Different Positions of Aminothiazole Hinge-Binding Scaffolds on Inhibitor-CDK2 Association Probed by Interaction Entropy Method. ACS Omega 2018, 3, 18052– 18064, DOI: 10.1021/acsomega.8b0235471https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXisFOmt7bO&md5=45bc29bf0a9b77e74bf198ec3ddb905eEffect of Substituents in Different Positions of Aminothiazole Hinge-Binding Scaffolds on Inhibitor-CDK2 Association Probed by Interaction Entropy MethodChen, Jianzhong; Wang, Xingyu; Zhang, John Z. H.; Zhu, TongACS Omega (2018), 3 (12), 18052-18064CODEN: ACSODF; ISSN:2470-1343. (American Chemical Society)Recently, CDK2 has been a promising target of drug development for treatment of the myriad of various human diseases. Mol. dynamics (MD) simulations are integrated with efficient interaction entropy (IE) method to probe effect of substitutions at S1 and S2 positions of the aminothiazole hinge-binding scaffold (1-{4-amino-2-(alkyl(o aryl)amino)thiazol-5-yl}arylmethanones) on bindings of inhibitors to CDK2. The results suggest that a para-sulfonamide moiety or a meta-amino group of a Ph ring introduced into S1 and S2 of the aminothiazole hinge-binding scaffold could not only improve van der Waals interactions of inhibitors with CDK2, but also strengthen their electrostatic interactions. The hot interaction spots of inhibitors with residues of CDK2 were identified by performing scanning of hydrophobic contacts and hydrogen bond contacts of inhibitors with CDK2 on MD trajectories. The results show that the aminothiazole hinge-binding scaffold not only generates stable hydrophobic contacts with conserved residues V18 and L134, but also form stable hydrogen bond contacts with conserved resides E81 and L83. Among the current substitutions, a para-sulfonamide moiety or a meta-amino group of a Ph ring at S1 and S2 of the aminothiazole hinge-binding scaffold display potential to improve binding ability of inhibitors to CDK2. The authors expect that this study can contribute significant guidance to design of potent inhibitors targeting CDK2.
- 72Sun, Z.; Yan, Y. N.; Yang, M.; Zhang, J. Z. H. Interaction Entropy for Protein-Protein Binding. J. Chem. Phys. 2017, 146, 124124 DOI: 10.1063/1.497889372https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXlsVagtrw%253D&md5=13171a7573f2cf571471c4bd9b749f15Interaction entropy for protein-protein bindingSun, Zhaoxi; Yan, Yu N.; Yang, Maoyou; Zhang, John Z. H.Journal of Chemical Physics (2017), 146 (12), 124124/1-124124/8CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)Protein-protein interactions are at the heart of signal transduction and are central to the function of protein machine in biol. The highly specific protein-protein binding is quant. characterized by the binding free energy whose accurate calcn. from the first principle is a grand challenge in computational biol. In this paper, the authors show how the interaction entropy approach, which was recently proposed for protein-ligand binding free energy calcn., can be applied to computing the entropic contribution to the protein-protein binding free energy. Explicit theor. derivation of the interaction entropy approach for protein-protein interaction system is given in detail from the basic definition. Extensive computational studies for a dozen realistic protein-protein interaction systems are carried out using the present approach and comparisons of the results for these protein-protein systems with those from the std. normal mode method are presented. Anal. of the present method for application in protein-protein binding as well as the limitation of the method in numerical computation is discussed. The study and anal. of the results provided useful information for extg. correct entropic contribution in protein-protein binding from mol. dynamics simulations. (c) 2017 American Institute of Physics.
- 73Ekberg, V.; Ryde, U. On the Use of Interaction Entropy and Related Methods to Estimate Binding Entropies. J. Chem. Theory Comput. 2021, 17, 5379– 5391, DOI: 10.1021/acs.jctc.1c0037473https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3MXhsFaku77I&md5=5f29641ac4bb30b94d28fad15faf4ecbOn the Use of Interaction Entropy and Related Methods to Estimate Binding EntropiesEkberg, Vilhelm; Ryde, UlfJournal of Chemical Theory and Computation (2021), 17 (8), 5379-5391CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)Mol. mechanics combined with Poisson-Boltzmann or generalized Born and solvent-accessible area solvation energies (MM/PBSA and MM/GBSA) are popular methods to est. the free energy for the binding of small mols. to biomacromols. However, the estn. of the entropy was problematic and time-consuming. Traditionally, normal-mode anal. was used to est. the entropy, but more recently, alternative approaches were suggested. In particular, it was suggested that exponential averaging of the electrostatic and Lennard-Jones interaction energies may provide much faster and more accurate entropies, the interaction entropy (IE) approach. This exponential averaging is extremely poorly conditioned. Using stochastic simulations, assuming that the interaction energies follow a Gaussian distribution, if the std. deviation of the interaction energies (σIE) is larger than 15 kJ/mol, it becomes practically impossible to converge the interaction entropies (more than 10 million energies are needed, and the no. increases exponentially). A cumulant approxn. to the second order of the exponential av. shows a better convergence, but for σIE > 25 kJ/mol, it gives entropies that are unrealistically large. Moreover, in practical applications, both methods show a steady increase in the entropy with the no. of energies considered.
Supporting Information
Supporting Information
The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jcim.1c00765.
Details of simulation setup and equilibration, truncated-normal mode calculations, and explicit water selection; (additional) plots of computational vs experimental ΔΔG values, residuals, number of water-bridged and solute–solute hydrogen bonds, histograms of gas-phase interaction energies, effect of entropy corrections on Spearman’s rank and Pearson’s r, and bootstrapping analysis of Pearson’s r; tables of histidine tautomers, experimental TCR–pHLA affinities from literature, CDR loop sequences, and mean absolute deviations (MADs) for linear fits (PDF)
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