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Correspondence/Rebuttal
Comment on: “Computer Simulations Reveal an Entirely Entropic Activation Barrier for the Chemical Step in a Designer Enzyme”Click to copy article linkArticle link copied!
- Abbie LearAbbie LearCentre for Computational Chemistry, School of Chemistry, University of Bristol, Bristol BS8 1TS, U.K.More by Abbie Lear
- J. L. Ross AndersonJ. L. Ross AndersonSchool of Biochemistry, University of Bristol, University Walk, Bristol BS8 1TD, U.K.More by J. L. Ross Anderson
- Donald HilvertDonald HilvertLaboratory of Organic Chemistry, ETH Zurich, 8093 Zurich, SwitzerlandMore by Donald Hilvert
- Vickery L. ArcusVickery L. ArcusSchool of Science, University of Waikato, Hamilton 3216, New ZealandMore by Vickery L. Arcus
- Marc W. van der KampMarc W. van der KampCentre for Computational Chemistry, School of Chemistry, University of Bristol, Bristol BS8 1TS, U.K.School of Biochemistry, University of Bristol, University Walk, Bristol BS8 1TD, U.K.More by Marc W. van der Kamp
- H. Adrian Bunzel*H. Adrian Bunzel*[email protected]Centre for Computational Chemistry, School of Chemistry, University of Bristol, Bristol BS8 1TS, U.K.Department of Biosystems Science and Engineering, ETH Zurich, CH-4058 Basel, SwitzerlandMore by H. Adrian Bunzel
- Adrian J. Mulholland*Adrian J. Mulholland*[email protected]Centre for Computational Chemistry, School of Chemistry, University of Bristol, Bristol BS8 1TS, U.K.More by Adrian J. Mulholland
Abstract
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Activation heat capacity has been proposed as an important factor in enzyme evolution and thermoadaptation. We previously demonstrated that the emergence of curved activity–temperature profiles during the evolution of a designer enzyme was due to the selective rigidification of its transition state ensemble that induced an activation heat capacity. Åqvist challenged our findings with molecular dynamics simulations suggesting that a change in the rate-limiting step underlies the experimental observations. As we describe here, Åqvist’s model is not consistent with the experimental trends observed for the chemical step of the catalyzed reaction (kcat). We suggest that this discrepancy arises because the simulations performed by Åqvist were limited by restraints and short simulation times, which do not allow sampling of the motions responsible for the observed activation heat capacity.
This publication is licensed for personal use by The American Chemical Society.
Copyright © 2023 American Chemical Society
Introduction
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De novo enzyme design has long been sought after to exploit the selectivity and activity of enzymes in “green” synthesis. (1) However, current design protocols produce only modestly active biocatalysts that require additional optimization by directed evolution. (2) Previously, we improved the de novo designed Kemp eliminase 1A53-2 by 9 rounds of mutagenesis and screening, leading to Kemp eliminase 1A53-2.9. Evolution boosted activity by more than 3 orders of magnitude. Unexpectedly, directed evolution also introduced curvature in the temperature dependence of activity. (3) We used MD simulations to show that this curvature is due to an activation heat capacity (ΔCp‡) rooted in a more rigid transition state (TS) compared to the ground state (GS) ensemble. (4) The observation that evolution selectively rigidifies the TS while improving activity suggests that the negative ΔCp‡ represents an evolutionary trade-off by which efficiency at optimal growth temperatures was improved at the cost of high-temperature activity. (5,6)
In his recent paper (ref (7)), Åqvist questions our conclusion that the curvature in the activity–temperature dependence of 1A53-2.5 is due to a ΔCp‡ effect. He presents empirical valence bond (EVB) simulations of the chemical reaction at a range of temperatures, which suggest that the reaction follows a linear Eyring plot (Figures 1b and 2b in ref (7)). Based on his observation of an unreactive substrate-complex (ES′) during MD, he analyzed the temperature dependence of the active–inactive substrate equilibrium (ES′ ⇌ ES) and likewise observed linear Eyring behavior. Finally, he constructed a three-state model (eq 1) involving substrate binding, reactive complex formation, and the chemical reaction. To analyze the reaction kinetics, this model was fitted to the experimental kcat/KM values, the simulated equilibrium between the reactive and unreactive Michaelis complex (ES′ ⇌ ES), and his calculated reaction barriers (ES → EP). Åqvist’s model indicated a change in the rate-limiting step from substrate binding to the chemical reaction at 308 K (Figure 4c in ref (7)), which he proposed to be the actual cause of the curved Eyring plots of 1A53-2.5. A change in heat capacity on substrate binding (E + S ⇌ ES′) was also suggested as a possible cause for the experimental observation but was discarded based on subsequent work from Åqvist and van der Ent. (8)
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Comments
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Åqvist’s Model in Ref (7) Is Not Consistent with Experimental Data
Åqvist’s analysis focuses on the curved T dependence of kcat/KM, but curvature is also seen for kcat. Åqvist’s model does not reproduce this curvature for kcat (Figure 1A, Figure S6 of ref (3), Extended Data Figure 1 of ref (4)). Åqvist’s conclusion regarding a change in the rate-limiting step arises from fitting MD results to the experimentally determined rates on kcat/KM (Figure 1B). As a mathematical consequence of excluding ΔCp‡ while fitting to kcat/KM values with curvature around 310 K, Åqvist’s model requires curvature in the T dependence of kcat below 250 K (Figure 1). Thus, the Åqvist model cannot simultaneously satisfy the experimentally observed curvature in kcat and kcat/KM around 310 K. We note that Åqvist does not determine substrate-binding rates directly. His analysis only indirectly infers binding rates, which further questions the main finding that a change in the rate-limiting step in favor of substrate-binding causes ΔCp‡.
Figure 1
Figure 1. (A) Åqvist’s model for the Kemp eliminase T dependence disagrees with the experimental kcat values (Figure S6 in ref (3), Extended Data Figure 1 in ref (4)). (B) Åqvist’s model was derived by fitting the data on kcat/KM (Figure 4B in ref (7)). 1A53-2.9 is shown here because T-dependent kcat values are only available for this variant. We note that Kemp eliminase 1A53-2.9 has a similar ΔCp‡ as 1A53-2.5 but a 2-fold higher kcat. The red fit represents Åqvist’s model, and the blue fit reflects our model involving ΔCp‡ from ref (3).
As pointed out by Åqvist, the kcat/KM data suggest that any step up to or including the reaction could cause curvature in the activity–temperature profile (i.e., binding, reactive complex formation, or the chemical reaction; see eq 1). (7) However, the experimental data for kcat also imply that either the chemical step, going from the Michaelis complex to the TS, or a subsequent step causes the curvature. Thus, it is likely that the experimental effect is caused by a ΔCp‡ affecting the chemical reaction and not by a change in the rate-limiting step.
Comparison with the Kemp eliminase HG3 family further questions the possibility of rate-limiting binding causing the apparent ΔCp‡ in the evolved 1A53-2 variants. (9) Substrate binding is not rate-limiting in any HG3 variant, as shown conclusively by kinetic isotope effects (10) and inhibitor-binding experiments. (11) Even HG3.17, one of the most efficient Kemp eliminases engineered to date, is not limited by substrate binding. Coincidentally, Kemp eliminase HG3.7 has a kcat/KM similar to 1A53-2.9 (Figure 2A). For binding (kon) to be rate-limiting in 1A53-2.9 at 55 °C, kon must be ≥2 orders of magnitude slower than for HG3.7 at 25 °C (Figure 2A). This is unlikely because the HG3 and 1A53-2 variants have comparable substrate affinities as indicated by KM and similarly wide substrate-entry channels (Figure 2B). Thus, binding is probably not rate-limiting in the evolved 1A53-2 variants over the studied temperature range.
Figure 2
Figure 2. Substrate binding in Kemp eliminases. (A) Binding would need to be ≥2 orders of magnitude slower in 1A53-2.9 at 55 °C (blue) compared to HG3.7 at 25 °C (red) to be rate limiting (gray). (B) The substrate-entry channel is comparably wide in HG3.7 and 1A53-2.5. (Channels were calculated with CARVER 3.0 (12) from the crystal structures (PDB accession codes: 4BS0, 7K4X, 7K4Q, and 6NW4; hydrogens added with PyMol).
Restraints in the Simulations in Ref (7) Limit Conformational Sampling
Åqvist considerably restrained the protein dynamics by running simulations in a spherical system where the surface solvent atoms are positionally restrained. These restraints even included 4% of the protein, further hindering sampling. Such treatment considerably restricts the protein dynamics, which in turn affects the relatively large conformational changes observed for the solvent-accessible loops, (4) and probably conceals any conformational sampling contributing to ΔCp‡. Moreover, previous work from Åqvist et al. has shown that surface dynamics can substantially affect the temperature dependence of catalysis. (13) Thus, in contrast to our previous simulations, (4,14) which did not significantly restrain the protein dynamics, it is unlikely that the dynamically restrained simulations presented in ref (7) can accurately reproduce the experimentally observed temperature profile and ΔCp‡ effect of 1A532.5.
Short Simulations in Ref (7) Prevent Adequate Sampling
The EVB simulations performed by Åqvist are performed over a relatively short time scale. Each replicate was simulated for ≈1 ns (as concluded from the methods section), whereas we previously ran multiple 500 ns MD simulations to analyze heat capacity changes. (4,14) Simulation length can considerably impact thermodynamic properties, (15) as sufficient time must be allowed for the system to explore all low-energy areas of phase space with reasonable frequency. To result in a meaningful ΔCp‡ in silico, the system requires enough time to equilibrate to the TS or GS. We emphasize that while the actual TS is short-lived, longer-lived reactive conformations akin to the (ES′ ⇌ ES) equilibrium probably provide sufficient time for equilibrating the protein dynamics in vitro.
To illustrate the effect of time scale, we determined the conformational space explored by our previously published (4) GS or TS-bound simulations of 1A53-2.5 using principal component analysis (PCA, Figure 3A and B). PCA of the backbone Cα positions was performed for both the first 1 ns to mimic the simulations from Åqvist and the last 450 ns analogous to our previous work. As expected, PCA clearly shows that the 1 ns simulations sample a much narrower conformational space than the 450 ns set. Since the potential energy depends on atomic positions, restricting the conformational distribution will perturb all thermodynamic parameters calculated from such short simulations. Furthermore, the PCA analysis of the extended time scale simulations shows that for 1A53-2.5, the conformational distribution of the protein is different for the GS and TS. Specifically, the distribution is narrower for the TS state. This observation probably relates to ΔCp‡, where, as the reaction progresses, the width of the sampled conformational space and thus the associated energy distribution decreases. (4,5,14) The sampling issue is likely aggravated by the fact that Åqvist equilibrates all systems bound to the TS, which further diminishes the dynamic differences between the GS and the TS conformational ensemble during EVB simulations. The conformational effects described here suggest that thermodynamic information drawn from short simulations such as those performed by Åqvist is insufficient to detect a ΔCp‡ effect.
Figure 3
Figure 3. Short time scales limit sampling. (A) Kemp eliminase mechanism. (B) Conformational landscape of 1A53-2.5 over 1 ns (black lines) and 450 ns (red and blue shading) of simulation time for both the ground state (GS) and transition state (TS). (C) ΔCp‡ calculated using the variance formula (16) based on either a 1 ns or 50 ns (ref (4)) moving window average over the 450 ns set. Errors are calculated by bootstrapping over ten replicates.
To illustrate the effects of restricted sampling on the thermodynamics of the system, we calculated the heat capacity effect for the 1 ns set from the difference in energy variance between the TS and GS (eq 2, Figure 3C). Within 1 ns, no significant ΔCp‡ effect was observed (−18.0 ± 32.9 kJ mol–1 K–1). To validate that this is not due to insufficient data, we calculated ΔCp‡ using a 1 ns moving window for the 450 ns set. The moving window approach allows for calculating fluctuations over short time scales from longer simulations and likewise provides a close-to-zero ΔCp‡ (1.6 ± 2.4 kJ mol–1 K–1). As published previously, (4) only larger window sizes reflecting the time scale of conformational change result in significant ΔCp‡ values (−19.7 ± 8.6 kJ mol–1 K–1 for a 50 ns window). Given that simulation time scale strongly affects the sampled conformational space, it is unlikely that the 1 ns EVB simulations performed in ref (7) can accurately capture the conformational sampling contributing to ΔCp‡. However, with more extended simulations and sampling, such effects become measurable, as we have demonstrated before. As discussed previously, (4) our simulations overestimate ΔCp‡ because solvent is not included in the calculation of the energetic fluctuations. We stress that─in contrast to Åqvist’s model─our analysis does not rely on generating rate constants by fitting computational results to experimental data. (4,14)
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Conclusion
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The proposal of Åqvist that a change in the rate-limiting step from substrate binding (E + S → ES′) to chemistry (ES → E + P) causes the apparent ΔCp‡ in 1A53-2.5 is questionable. The experimental data (Figure 1) clearly show nonlinearity in kcat and kcat/KM around 310 K, which Åqvist’s model cannot reproduce. Moreover, the substrate-binding rates essential to the proposed change in the catalytic bottleneck have only been indirectly inferred by Åqvist. We propose two possible causes of the discrepancy between the Åqvist model and experiment: constrained dynamics and limited simulation time scales. Both factors severely restrict the amount of conformational sampling and mask the ΔCp‡ effect. Nevertheless, Åqvist’s observation of an unreactive substrate-bound state might be necessary to fully understand the catalytic ramifications of ΔCp‡. A negative ΔCp‡ effect generally results from broader conformational sampling in the GS compared to the TS ensemble. The two-state model (ES′ ⇌ ES) proposed by Åqvist fulfills this requirement, (7) and the observation of an ES′ state might be key to determining the benefit─if any─provided by the evolution of ΔCp‡.
In conclusion, the constrained 1 ns EVB simulations performed by Åqvist cannot capture the catalytically relevant conformational sampling that gives rise to ΔCp‡. Based on the experimental and simulation evidence, the activity–temperature dependence of 1A53-2.5 is most likely caused by a ΔCp‡ and not by a change in the rate-limiting step.
Author Information
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- H. Adrian Bunzel - Centre for Computational Chemistry, School of Chemistry, University of Bristol, Bristol BS8 1TS, U.K.; Department of Biosystems Science and Engineering, ETH Zurich, CH-4058 Basel, Switzerland;
https://orcid.org/0000-0001-6427-368X;
- Adrian J. Mulholland - Centre for Computational Chemistry, School of Chemistry, University of Bristol, Bristol BS8 1TS, U.K.;https://orcid.org/0000-0003-1015-4567;
- Abbie Lear - Centre for Computational Chemistry, School of Chemistry, University of Bristol, Bristol BS8 1TS, U.K.;https://orcid.org/0009-0006-4126-5867
- J. L. Ross Anderson - School of Biochemistry, University of Bristol, University Walk, Bristol BS8 1TD, U.K.;https://orcid.org/0000-0002-6796-0482
- Donald Hilvert - Laboratory of Organic Chemistry, ETH Zurich, 8093 Zurich, Switzerland;https://orcid.org/0000-0002-3941-621X
- Vickery L. Arcus - School of Science, University of Waikato, Hamilton 3216, New Zealand;https://orcid.org/0000-0001-5082-2414
- Marc W. van der Kamp - Centre for Computational Chemistry, School of Chemistry, University of Bristol, Bristol BS8 1TS, U.K.; School of Biochemistry, University of Bristol, University Walk, Bristol BS8 1TD, U.K.;https://orcid.org/0000-0002-8060-3359
AL and HAB wrote the manuscript with input from all coauthors.
Acknowledgments
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HAB and AJM thank EPSRC (EP/M013219/1 and EP/M022609/1) and with JLRA BBSRC (BB/M000354/1) for funding. MWvdK thanks BBSRC for funding (BB/M026280/1). VLA and AJM thank the Marsden Fund of New Zealand (16-UOW-027). This work is part of a project that has received funding from the European Research Council under the European Horizon 2020 research and innovation program (PREDACTED Advanced Grant Agreement no. 101021207) to AL and AJM. HAB thanks the SNSF for funding (P5R5PB_210999). VLA is a James Cook Research Fellow (Royal Society of New Zealand). This work was conducted using the computational facilities of the Advanced Computing Research Centre, University of Bristol.
References
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This article references 16 other publications.
- 1Arnold, F. H. Innovation by Evolution: Bringing New Chemistry to Life (Nobel Lecture). Angew. Chem., Int. Ed. 2019, 58 (41), 14420– 14426, DOI: 10.1002/anie.201907729Google Scholar1https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXhs1aitrjN&md5=7b1e55664b266b22e5c6421eb729ec90Innovation by Evolution: Bringing New Chemistry to Life (Nobel Lecture)Arnold, Frances H.Angewandte Chemie, International Edition (2019), 58 (41), 14420-14426CODEN: ACIEF5; ISSN:1433-7851. (Wiley-VCH Verlag GmbH & Co. KGaA)A review. This article focused on directed evolution strategy suitable for enzymes, exploring the universe of possible proteins, evolution of enzymes for reactions invented by chemists, DNA-encoded protein biocatalysis and bringing new bonds to biol.
- 2Lovelock, S. L.; Crawshaw, R.; Basler, S.; Levy, C.; Baker, D.; Hilvert, D.; Green, A. P. The Road to Fully Programmable Protein Catalysis. Nature 2022, 606 (7912), 49– 58, DOI: 10.1038/s41586-022-04456-zGoogle Scholar2https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB38XhsVant7fM&md5=eb135e789d4558fe2618223340cb5e3cThe road to fully programmable protein catalysisLovelock, Sarah L.; Crawshaw, Rebecca; Basler, Sophie; Levy, Colin; Baker, David; Hilvert, Donald; Green, Anthony P.Nature (London, United Kingdom) (2022), 606 (7912), 49-58CODEN: NATUAS; ISSN:1476-4687. (Nature Portfolio)A review. The ability to design efficient enzymes from scratch would have a profound effect on chem., biotechnol. and medicine. Rapid progress in protein engineering over the past decade makes us optimistic that this ambition is within reach. The development of artificial enzymes contg. metal cofactors and noncanonical organocatalytic groups shows how protein structure can be optimized to harness the reactivity of nonproteinogenic elements. In parallel, computational methods have been used to design protein catalysts for diverse reactions on the basis of fundamental principles of transition state stabilization. Although the activities of designed catalysts have been quite low, extensive lab. evolution has been used to generate efficient enzymes. Structural anal. of these systems has revealed the high degree of precision that will be needed to design catalysts with greater activity. To this end, emerging protein design methods, including deep learning, hold particular promise for improving model accuracy. Here we take stock of key developments in the field and highlight new opportunities for innovation that should allow us to transition beyond the current state of the art and enable the robust design of biocatalysts to address societal needs.
- 3Bunzel, H. A.; Kries, H.; Marchetti, L.; Zeymer, C.; Mittl, P. R. E.; Mulholland, A. J.; Hilvert, D. Emergence of a Negative Activation Heat Capacity during Evolution of a Designed Enzyme. J. Am. Chem. Soc. 2019, 141 (30), 11745– 11748, DOI: 10.1021/jacs.9b02731Google Scholar3https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXhtlamsbzL&md5=fa87c08b1b843903ef26473f4d8042f8Emergence of a Negative Activation Heat Capacity during Evolution of a Designed EnzymeBunzel, H. Adrian; Kries, Hajo; Marchetti, Luca; Zeymer, Cathleen; Mittl, Peer R. E.; Mulholland, Adrian J.; Hilvert, DonaldJournal of the American Chemical Society (2019), 141 (30), 11745-11748CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)Temp. influences the reaction kinetics and evolvability of all enzymes. To understand how evolution shapes the thermodn. drivers of catalysis, we optimized the modest activity of a computationally designed enzyme for an elementary proton-transfer reaction by nearly 4 orders of magnitude over 9 rounds of mutagenesis and screening. As theorized for primordial enzymes, the catalytic effects of the original design were almost entirely enthalpic in origin, as were the rate enhancements achieved by lab. evolution. However, the large redns. in ΔH⧺ were partially offset by a decrease in TΔS⧺ and unexpectedly accompanied by a neg. activation heat capacity, signaling strong adaptation to the operating temp. These findings echo reports of temp.-dependent activation parameters for highly evolved natural enzymes and are relevant to explanations of enzymic catalysis and adaptation to changing thermal environments.
- 4Bunzel, H. A.; Anderson, J. L. R.; Hilvert, D.; Arcus, V. L.; van der Kamp, M. W.; Mulholland, A. J. Evolution of Dynamical Networks Enhances Catalysis in a Designer Enzyme. Nat. Chem. 2021, 13 (10), 1017– 1022, DOI: 10.1038/s41557-021-00763-6Google Scholar4https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3MXhvVCrt77P&md5=7da9f9d8da4e409a091a6edaff256c39Evolution of dynamical networks enhances catalysis in a designer enzymeBunzel, H. Adrian; Anderson, J. L. Ross; Hilvert, Donald; Arcus, Vickery L.; van der Kamp, Marc W.; Mulholland, Adrian J.Nature Chemistry (2021), 13 (10), 1017-1022CODEN: NCAHBB; ISSN:1755-4330. (Nature Portfolio)Activation heat capacity is emerging as a crucial factor in enzyme thermoadaptation, as shown by the non-Arrhenius behavior of many natural enzymes. However, its phys. origin and relation to the evolution of catalytic activity remain uncertain. Directed evolution of a computationally designed Kemp eliminase reshapes protein dynamics, which gives rise to an activation heat capacity absent in the original design. These changes buttress transition-state stabilization. Extensive mol. dynamics simulations show that evolution results in the closure of solvent-exposed loops and a better packing of the active site. Remarkably, this gives rise to a correlated dynamical network that involves the transition state and large parts of the protein. This network tightens the transition-state ensemble, which induces a neg. activation heat capacity and non-linearity in the activity-temp. dependence. The authors' results have implications for understanding enzyme evolution and suggest that selectively targeting the conformational dynamics of the transition-state ensemble by design and evolution will expedite the creation of novel enzymes.
- 5Arcus, V. L.; Prentice, E. J.; Hobbs, J. K.; Mulholland, A. J.; Van der Kamp, M. W.; Pudney, C. R.; Parker, E. J.; Schipper, L. A. On the Temperature Dependence of Enzyme-Catalyzed Rates. Biochemistry 2016, 55 (12), 1681– 1688, DOI: 10.1021/acs.biochem.5b01094Google Scholar5https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XisFKqsbk%253D&md5=24ecee25dcbdffed1012b98edee9a561On the Temperature Dependence of Enzyme-Catalyzed RatesArcus, Vickery L.; Prentice, Erica J.; Hobbs, Joanne K.; Mulholland, Adrian J.; Van der Kamp, Marc W.; Pudney, Christopher R.; Parker, Emily J.; Schipper, Louis A.Biochemistry (2016), 55 (12), 1681-1688CODEN: BICHAW; ISSN:0006-2960. (American Chemical Society)One of the crit. variables that det. the rate of any reaction is temp. For biol. systems, the effects of temp. are convoluted with myriad (and often opposing) contributions from enzyme catalysis, protein stability, and temp.-dependent regulation, for example. We have coined the phrase "macromol. rate theory (MMRT)" to describe the temp. dependence of enzyme-catalyzed rates independent of stability or regulatory processes. Central to MMRT is the observation that enzyme-catalyzed reactions occur with significant values of ΔCp‡ that are in general neg. That is, the heat capacity (Cp) for the enzyme-substrate complex is generally larger than the Cp for the enzyme-transition state complex. Consistent with a classical description of enzyme catalysis, a neg. value for ΔCp‡ is the result of the enzyme binding relatively weakly to the substrate and very tightly to the transition state. This observation of neg. ΔCp‡ has important implications for the temp. dependence of enzyme-catalyzed rates. Here, we lay out the fundamentals of MMRT. We present a no. of hypotheses that arise directly from MMRT including a theor. justification for the large size of enzymes and the basis for their optimum temps. We rationalize the behavior of psychrophilic enzymes and describe a "psychrophilic trap" which places limits on the evolution of enzymes in low temp. environments. One of the defining characteristics of biol. is catalysis of chem. reactions by enzymes, and enzymes drive much of metab. Therefore, we also expect to see characteristics of MMRT at the level of cells, whole organisms, and even ecosystems.
- 6Arcus, V. L.; Mulholland, A. J. Temperature, Dynamics, and Enzyme-Catalyzed Reaction Rates. Annu. Rev. Biophys. 2020, 49 (1), 163– 180, DOI: 10.1146/annurev-biophys-121219-081520Google Scholar6https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXit1Chs7s%253D&md5=9f2034e247a628abff7e178ab402f9b5Temperature, Dynamics, and Enzyme-Catalyzed Reaction RatesArcus, Vickery L.; Mulholland, Adrian J.Annual Review of Biophysics (2020), 49 (), 163-180CODEN: ARBNCV; ISSN:1936-122X. (Annual Reviews)We review the adaptations of enzyme activity to different temps. Psychrophilic (cold-adapted) enzymes show significantly different activation parameters (lower activation enthalpies and entropies) from their mesophilic counterparts. Furthermore, there is increasing evidence that the temp. dependence of many enzyme-catalyzed reactions is more complex than is widely believed. Many enzymes show curvature in plots of activity vs. temp. that is not accounted for by denaturation or unfolding. This is explained by macromol. rate theory: A neg. activation heat capacity for the rate-limiting chem. step leads directly to predictions of temp. optima; both entropy and enthalpy are temp. dependent. Fluctuations in the transition state ensemble are reduced compared to the ground state. We show how investigations combining expt. with mol. simulation are revealing fundamental details of enzyme thermoadaptation that are relevant for understanding aspects of enzyme evolution. Simulations can calc. relevant thermodn. properties (such as activation enthalpies, entropies, and heat capacities) and reveal the mol. mechanisms underlying exptl. obsd. behavior.
- 7Åqvist, J. Computer Simulations Reveal an Entirely Entropic Activation Barrier for the Chemical Step in a Designer Enzyme. ACS Catal. 2022, 12 (2), 1452– 1460, DOI: 10.1021/acscatal.1c05814Google ScholarThere is no corresponding record for this reference.
- 8Åqvist, J.; van der Ent, F. Calculation of Heat Capacity Changes in Enzyme Catalysis and Ligand Binding. J. Chem. Theory Comput. 2022, 18 (10), 6345– 6353, DOI: 10.1021/acs.jctc.2c00646Google ScholarThere is no corresponding record for this reference.
- 9Blomberg, R.; Kries, H.; Pinkas, D. M.; Mittl, P. R. E.; Grütter, M. G.; Privett, H. K.; Mayo, S. L.; Hilvert, D. Precision Is Essential for Efficient Catalysis in an Evolved Kemp Eliminase. Nature 2013, 503 (7476), 418– 421, DOI: 10.1038/nature12623Google Scholar9https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhslSnsb%252FI&md5=882663ec6c0f1e00e3fd7912423bd259Precision is essential for efficient catalysis in an evolved Kemp eliminaseBlomberg, Rebecca; Kries, Hajo; Pinkas, Daniel M.; Mittl, Peer R. E.; Gruetter, Markus G.; Privett, Heidi K.; Mayo, Stephen L.; Hilvert, DonaldNature (London, United Kingdom) (2013), 503 (7476), 418-421CODEN: NATUAS; ISSN:0028-0836. (Nature Publishing Group)Linus Pauling established the conceptual framework for understanding and mimicking enzymes more than six decades ago. The notion that enzymes selectively stabilize the rate-limiting transition state of the catalyzed reaction relative to the bound ground state reduces the problem of design to one of mol. recognition. Nevertheless, past attempts to capitalize on this idea, for example by using transition state analogs to elicit antibodies with catalytic activities, have generally failed to deliver true enzymic rates. The advent of computational design approaches, combined with directed evolution, has provided an opportunity to revisit this problem. Starting from a computationally designed catalyst for the Kemp elimination-a well-studied model system for proton transfer from carbon-we show that an artificial enzyme can be evolved that accelerates an elementary chem. reaction 6 × 108-fold, approaching the exceptional efficiency of highly optimized natural enzymes such as triosephosphate isomerase. A 1.09 Å resoln. crystal structure of the evolved enzyme indicates that familiar catalytic strategies such as shape complementarity and precisely placed catalytic groups can be successfully harnessed to afford such high rate accelerations, making us optimistic about the prospects of designing more sophisticated catalysts.
- 10Kries, H.; Bloch, J. S.; Bunzel, H. A.; Pinkas, D. M.; Hilvert, D. Contribution of Oxyanion Stabilization to Kemp Eliminase Efficiency. ACS Catal. 2020, 10 (8), 4460– 4464, DOI: 10.1021/acscatal.0c00575Google Scholar10https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXlt1Cru7o%253D&md5=ff017d9533da239df9c5ec0df71243c9Contribution of oxyanion stabilization to Kemp eliminase efficiencyKries, Hajo; Bloch, Joel S.; Bunzel, H. Adrian; Pinkas, Daniel M.; Hilvert, DonaldACS Catalysis (2020), 10 (8), 4460-4464CODEN: ACCACS; ISSN:2155-5435. (American Chemical Society)Important reactions in biol. and biocatalysis involve proton abstraction from carbon. When the resulting anionic charge is delocalized from carbon to an oxygen atom, these deprotonations can be catalytically accelerated by oxyanion stabilization. Oxyanion stabilization by a glutamine side chain (Gln50) was thought to accelerate C-H proton abstraction in HG3.17, a computationally designed biocatalyst that had been evolutionarily optimized to enzyme-like efficiency. We present kinetic data and crystal structures at at. resoln. for six Gln50 mutants that indicate a surprisingly small advantage of the hydrogen-bond donor glutamine over "greasy" methionine. However, tightly packed active sites (Gln, Met, Phe)-greasy or not-perform consistently better than water-filled oxyanion holes found with other substitutions (His, Ser, Ala, Lys). Although oxyanion stabilization appears to contribute modestly to HG3.17 efficiency, the role of Gln50 is mechanistically more complex than initially thought, underscoring the importance of multifactorial approaches for the design of enzymic oxyanion holes in the future.
- 11Otten, R.; Pádua, R. A. P.; Bunzel, H. A.; Nguyen, V.; Pitsawong, W.; Patterson, M.; Sui, S.; Perry, S. L.; Cohen, A. E.; Hilvert, D.; Kern, D. How Directed Evolution Reshapes the Energy Landscape in an Enzyme to Boost Catalysis. Science 2020, 370 (6523), 1442– 1446, DOI: 10.1126/science.abd3623Google Scholar11https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXis1KksLzI&md5=7900ea67d0d68d450fa5a4dc54757c65How directed evolution reshapes the energy landscape in an enzyme to boost catalysisOtten, Renee; Padua, Ricardo A. P.; Bunzel, H. Adrian; Nguyen, Vy; Pitsawong, Warintra; Patterson, MacKenzie; Sui, Shuo; Perry, Sarah L.; Cohen, Aina E.; Hilvert, Donald; Kern, DorotheeScience (Washington, DC, United States) (2020), 370 (6523), 1442-1446CODEN: SCIEAS; ISSN:1095-9203. (American Association for the Advancement of Science)The advent of biocatalysts designed computationally and optimized by lab. evolution provides an opportunity to explore mol. strategies for augmenting catalytic function. Applying a suite of NMR, crystallog., and stopped-flow techniques to an enzyme designed for an elementary proton transfer reaction, we show how directed evolution gradually altered the conformational ensemble of the protein scaffold to populate a narrow, highly active conformational ensemble and accelerate this transformation by nearly nine orders of magnitude. Mutations acquired during optimization enabled global conformational changes, including high-energy backbone rearrangements, that cooperatively organized the catalytic base and oxyanion stabilizer, thus perfecting transition-state stabilization. The development of protein catalysts for many chem. transformations could be facilitated by explicitly sampling conformational substates during design and specifically stabilizing productive substates over all unproductive conformations.
- 12Chovancova, E.; Pavelka, A.; Benes, P.; Strnad, O.; Brezovsky, J.; Kozlikova, B.; Gora, A.; Sustr, V.; Klvana, M.; Medek, P.; Biedermannova, L.; Sochor, J.; Damborsky, J. CAVER 3.0: A Tool for the Analysis of Transport Pathways in Dynamic Protein Structures. PLOS Comput. Biol. 2012, 8 (10), e1002708 DOI: 10.1371/journal.pcbi.1002708Google Scholar12https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38Xhs1ansbfI&md5=aff24be751fef33d531b446cf6ab86c5CAVER 3.0: a tool for the analysis of transport pathways in dynamic protein structuresChovancova, Eva; Pavelka, Antonin; Benes, Petr; Strnad, Ondrej; Brezovsky, Jan; Kozlikova, Barbora; Gora, Artur; Sustr, Vilem; Klvana, Martin; Medek, Petr; Biedermannova, Lada; Sochor, Jiri; Damborsky, JiriPLoS Computational Biology (2012), 8 (10), e1002708CODEN: PCBLBG; ISSN:1553-7358. (Public Library of Science)Tunnels and channels facilitate the transport of small mols., ions and water solvent in a large variety of proteins. Characteristics of individual transport pathways, including their geometry, physico-chem. properties and dynamics are instrumental for understanding of structure-function relationships of these proteins, for the design of new inhibitors and construction of improved biocatalysts. CAVER is a software tool widely used for the identification and characterization of transport pathways in static macromol. structures. Herein we present a new version of CAVER enabling automatic anal. of tunnels and channels in large ensembles of protein conformations. CAVER 3.0 implements new algorithms for the calcn. and clustering of pathways. A trajectory from a mol. dynamics simulation serves as the typical input, while detailed characteristics and summary statistics of the time evolution of individual pathways are provided in the outputs. To illustrate the capabilities of CAVER 3.0, the tool was applied for the anal. of mol. dynamics simulation of the microbial enzyme haloalkane dehalogenase DhaA. CAVER 3.0 safely identified and reliably estd. the importance of all previously published DhaA tunnels, including the tunnels closed in DhaA crystal structures. Obtained results clearly demonstrate that anal. of mol. dynamics simulation is essential for the estn. of pathway characteristics and elucidation of the structural basis of the tunnel gating. CAVER 3.0 paves the way for the study of important biochem. phenomena in the area of mol. transport, mol. recognition and enzymic catalysis. The software is freely available as a multiplatform command-line application online.
- 13Isaksen, G. V.; Åqvist, J.; Brandsdal, B. O. Enzyme Surface Rigidity Tunes the Temperature Dependence of Catalytic Rates. Proc. Natl. Acad. Sci. U. S. A. 2016, 113 (28), 7822– 7827, DOI: 10.1073/pnas.1605237113Google Scholar13https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XhtFentrvK&md5=8c0c4323f08439a5707eb0f81449eb08Enzyme surface rigidity tunes the temperature dependence of catalytic ratesIsaksen, Geir Villy; Aaqvist, Johan; Brandsdal, Bjoern OlavProceedings of the National Academy of Sciences of the United States of America (2016), 113 (28), 7822-7827CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)The structural origin of enzyme adaptation to low temp., allowing efficient catalysis of chem. reactions even near the f.p. of water, remains a fundamental puzzle in biocatalysis. A remarkable universal fingerprint shared by all cold-active enzymes is a redn. of the activation enthalpy accompanied by a more neg. entropy, which alleviates the exponential decrease in chem. reaction rates caused by lowering of the temp. Here, the authors explored the role of protein surface mobility in detg. this enthalpy-entropy balance. The effects of modifying surface rigidity in cold- and warm-active trypsins were demonstrated here by calcn. of high-precision Arrhenius plots and thermodn. activation parameters for the peptide hydrolysis reaction, using extensive computer simulations. The protein surface flexibility was systematically varied by applying positional restraints, causing the remarkable effect of turning the cold-active trypsin into a variant with mesophilic characteristics without changing the amino acid sequence. Furthermore, the authors showed that just restraining a key surface loop caused the same effect as a point mutation in that loop between the cold- and warm-active trypsin. Importantly, changes in the activation enthalpy-entropy balance of up to 10 kcal/mol were almost perfectly balanced at room temp., whereas they yielded significantly higher rates at low temps. for the cold-adapted enzyme.
- 14van der Kamp, M. W.; Prentice, E. J.; Kraakman, K. L.; Connolly, M.; Mulholland, A. J.; Arcus, V. L. Dynamical Origins of Heat Capacity Changes in Enzyme-Catalysed Reactions. Nat. Commun. 2018, 9 (1), 1177, DOI: 10.1038/s41467-018-03597-yGoogle Scholar14https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC1MnjsFCksg%253D%253D&md5=5d8a0a11225953507fc64977c47d5126Dynamical origins of heat capacity changes in enzyme-catalysed reactionsvan der Kamp Marc W; van der Kamp Marc W; Connolly Michael; Mulholland Adrian J; Prentice Erica J; Kraakman Kirsty L; Arcus Vickery LNature communications (2018), 9 (1), 1177 ISSN:.Heat capacity changes are emerging as essential for explaining the temperature dependence of enzyme-catalysed reaction rates. This has important implications for enzyme kinetics, thermoadaptation and evolution, but the physical basis of these heat capacity changes is unknown. Here we show by a combination of experiment and simulation, for two quite distinct enzymes (dimeric ketosteroid isomerase and monomeric alpha-glucosidase), that the activation heat capacity change for the catalysed reaction can be predicted through atomistic molecular dynamics simulations. The simulations reveal subtle and surprising underlying dynamical changes: tightening of loops around the active site is observed, along with changes in energetic fluctuations across the whole enzyme including important contributions from oligomeric neighbours and domains distal to the active site. This has general implications for understanding enzyme catalysis and demonstrating a direct connection between functionally important microscopic dynamics and macroscopically measurable quantities.
- 15Mey, A. S. J. S.; Allen, B. K.; Macdonald, H. E. B.; Chodera, J. D.; Hahn, D. F.; Kuhn, M.; Michel, J.; Mobley, D. L.; Naden, L. N.; Prasad, S.; Rizzi, A.; Scheen, J.; Shirts, M. R.; Tresadern, G.; Xu, H. Best Practices for Alchemical Free Energy Calculations [Article v1.0]. Living J. Comput. Mol. Sci. 2020, 2 (1), 18378, DOI: 10.33011/livecoms.2.1.18378Google ScholarThere is no corresponding record for this reference.
- 16Prabhu, N. V.; Sharp, K. A. Heat Capacity in Proteins. Annu. Rev. Phys. Chem. 2005, 56 (1), 521– 548, DOI: 10.1146/annurev.physchem.56.092503.141202Google Scholar16https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2MXps1Grtrs%253D&md5=55b0d3f7c11cbf6606941a28c3404143Heat capacity in proteinsPrabhu, Ninad V.; Sharp, Kim A.Annual Review of Physical Chemistry (2005), 56 (), 521-548CODEN: ARPLAP; ISSN:0066-426X. (Annual Reviews Inc.)A review. Heat capacity (Cp) is one of several major thermodn. quantities commonly measured in proteins. With more than half a dozen definitions, it is the hardest of these quantities to understand in phys. terms, but the richest in insight. There are many ramifications of obsd. Cp changes: The sign distinguishes apolar from polar solvation. It imparts a temp. (T) dependence to entropy and enthalpy that may change their signs and which of them dominate. Protein unfolding usually has a pos. ΔCp, producing a max. in stability and sometimes cold denaturation. There are two heat capacity contributions, from hydration and protein-protein interactions; which dominates in folding and binding is an open question. Theor. work to date has dealt mostly with the hydration term and can account, at least semiquant., for the major Cp-related features: the pos. and neg. Cp of hydration for apolar and polar groups, resp.; the convergence of apolar group hydration entropy at T ≈ 112°C; the decrease in apolar hydration Cp with increasing T; and the T-max. in protein stability and cold denaturation.
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Figure 1
Figure 1. (A) Åqvist’s model for the Kemp eliminase T dependence disagrees with the experimental kcat values (Figure S6 in ref (3), Extended Data Figure 1 in ref (4)). (B) Åqvist’s model was derived by fitting the data on kcat/KM (Figure 4B in ref (7)). 1A53-2.9 is shown here because T-dependent kcat values are only available for this variant. We note that Kemp eliminase 1A53-2.9 has a similar ΔCp‡ as 1A53-2.5 but a 2-fold higher kcat. The red fit represents Åqvist’s model, and the blue fit reflects our model involving ΔCp‡ from ref (3).
Figure 2
Figure 2. Substrate binding in Kemp eliminases. (A) Binding would need to be ≥2 orders of magnitude slower in 1A53-2.9 at 55 °C (blue) compared to HG3.7 at 25 °C (red) to be rate limiting (gray). (B) The substrate-entry channel is comparably wide in HG3.7 and 1A53-2.5. (Channels were calculated with CARVER 3.0 (12) from the crystal structures (PDB accession codes: 4BS0, 7K4X, 7K4Q, and 6NW4; hydrogens added with PyMol).
Figure 3
Figure 3. Short time scales limit sampling. (A) Kemp eliminase mechanism. (B) Conformational landscape of 1A53-2.5 over 1 ns (black lines) and 450 ns (red and blue shading) of simulation time for both the ground state (GS) and transition state (TS). (C) ΔCp‡ calculated using the variance formula (16) based on either a 1 ns or 50 ns (ref (4)) moving window average over the 450 ns set. Errors are calculated by bootstrapping over ten replicates.
References
This article references 16 other publications.
- 1Arnold, F. H. Innovation by Evolution: Bringing New Chemistry to Life (Nobel Lecture). Angew. Chem., Int. Ed. 2019, 58 (41), 14420– 14426, DOI: 10.1002/anie.2019077291https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXhs1aitrjN&md5=7b1e55664b266b22e5c6421eb729ec90Innovation by Evolution: Bringing New Chemistry to Life (Nobel Lecture)Arnold, Frances H.Angewandte Chemie, International Edition (2019), 58 (41), 14420-14426CODEN: ACIEF5; ISSN:1433-7851. (Wiley-VCH Verlag GmbH & Co. KGaA)A review. This article focused on directed evolution strategy suitable for enzymes, exploring the universe of possible proteins, evolution of enzymes for reactions invented by chemists, DNA-encoded protein biocatalysis and bringing new bonds to biol.
- 2Lovelock, S. L.; Crawshaw, R.; Basler, S.; Levy, C.; Baker, D.; Hilvert, D.; Green, A. P. The Road to Fully Programmable Protein Catalysis. Nature 2022, 606 (7912), 49– 58, DOI: 10.1038/s41586-022-04456-z2https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB38XhsVant7fM&md5=eb135e789d4558fe2618223340cb5e3cThe road to fully programmable protein catalysisLovelock, Sarah L.; Crawshaw, Rebecca; Basler, Sophie; Levy, Colin; Baker, David; Hilvert, Donald; Green, Anthony P.Nature (London, United Kingdom) (2022), 606 (7912), 49-58CODEN: NATUAS; ISSN:1476-4687. (Nature Portfolio)A review. The ability to design efficient enzymes from scratch would have a profound effect on chem., biotechnol. and medicine. Rapid progress in protein engineering over the past decade makes us optimistic that this ambition is within reach. The development of artificial enzymes contg. metal cofactors and noncanonical organocatalytic groups shows how protein structure can be optimized to harness the reactivity of nonproteinogenic elements. In parallel, computational methods have been used to design protein catalysts for diverse reactions on the basis of fundamental principles of transition state stabilization. Although the activities of designed catalysts have been quite low, extensive lab. evolution has been used to generate efficient enzymes. Structural anal. of these systems has revealed the high degree of precision that will be needed to design catalysts with greater activity. To this end, emerging protein design methods, including deep learning, hold particular promise for improving model accuracy. Here we take stock of key developments in the field and highlight new opportunities for innovation that should allow us to transition beyond the current state of the art and enable the robust design of biocatalysts to address societal needs.
- 3Bunzel, H. A.; Kries, H.; Marchetti, L.; Zeymer, C.; Mittl, P. R. E.; Mulholland, A. J.; Hilvert, D. Emergence of a Negative Activation Heat Capacity during Evolution of a Designed Enzyme. J. Am. Chem. Soc. 2019, 141 (30), 11745– 11748, DOI: 10.1021/jacs.9b027313https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXhtlamsbzL&md5=fa87c08b1b843903ef26473f4d8042f8Emergence of a Negative Activation Heat Capacity during Evolution of a Designed EnzymeBunzel, H. Adrian; Kries, Hajo; Marchetti, Luca; Zeymer, Cathleen; Mittl, Peer R. E.; Mulholland, Adrian J.; Hilvert, DonaldJournal of the American Chemical Society (2019), 141 (30), 11745-11748CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)Temp. influences the reaction kinetics and evolvability of all enzymes. To understand how evolution shapes the thermodn. drivers of catalysis, we optimized the modest activity of a computationally designed enzyme for an elementary proton-transfer reaction by nearly 4 orders of magnitude over 9 rounds of mutagenesis and screening. As theorized for primordial enzymes, the catalytic effects of the original design were almost entirely enthalpic in origin, as were the rate enhancements achieved by lab. evolution. However, the large redns. in ΔH⧺ were partially offset by a decrease in TΔS⧺ and unexpectedly accompanied by a neg. activation heat capacity, signaling strong adaptation to the operating temp. These findings echo reports of temp.-dependent activation parameters for highly evolved natural enzymes and are relevant to explanations of enzymic catalysis and adaptation to changing thermal environments.
- 4Bunzel, H. A.; Anderson, J. L. R.; Hilvert, D.; Arcus, V. L.; van der Kamp, M. W.; Mulholland, A. J. Evolution of Dynamical Networks Enhances Catalysis in a Designer Enzyme. Nat. Chem. 2021, 13 (10), 1017– 1022, DOI: 10.1038/s41557-021-00763-64https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3MXhvVCrt77P&md5=7da9f9d8da4e409a091a6edaff256c39Evolution of dynamical networks enhances catalysis in a designer enzymeBunzel, H. Adrian; Anderson, J. L. Ross; Hilvert, Donald; Arcus, Vickery L.; van der Kamp, Marc W.; Mulholland, Adrian J.Nature Chemistry (2021), 13 (10), 1017-1022CODEN: NCAHBB; ISSN:1755-4330. (Nature Portfolio)Activation heat capacity is emerging as a crucial factor in enzyme thermoadaptation, as shown by the non-Arrhenius behavior of many natural enzymes. However, its phys. origin and relation to the evolution of catalytic activity remain uncertain. Directed evolution of a computationally designed Kemp eliminase reshapes protein dynamics, which gives rise to an activation heat capacity absent in the original design. These changes buttress transition-state stabilization. Extensive mol. dynamics simulations show that evolution results in the closure of solvent-exposed loops and a better packing of the active site. Remarkably, this gives rise to a correlated dynamical network that involves the transition state and large parts of the protein. This network tightens the transition-state ensemble, which induces a neg. activation heat capacity and non-linearity in the activity-temp. dependence. The authors' results have implications for understanding enzyme evolution and suggest that selectively targeting the conformational dynamics of the transition-state ensemble by design and evolution will expedite the creation of novel enzymes.
- 5Arcus, V. L.; Prentice, E. J.; Hobbs, J. K.; Mulholland, A. J.; Van der Kamp, M. W.; Pudney, C. R.; Parker, E. J.; Schipper, L. A. On the Temperature Dependence of Enzyme-Catalyzed Rates. Biochemistry 2016, 55 (12), 1681– 1688, DOI: 10.1021/acs.biochem.5b010945https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XisFKqsbk%253D&md5=24ecee25dcbdffed1012b98edee9a561On the Temperature Dependence of Enzyme-Catalyzed RatesArcus, Vickery L.; Prentice, Erica J.; Hobbs, Joanne K.; Mulholland, Adrian J.; Van der Kamp, Marc W.; Pudney, Christopher R.; Parker, Emily J.; Schipper, Louis A.Biochemistry (2016), 55 (12), 1681-1688CODEN: BICHAW; ISSN:0006-2960. (American Chemical Society)One of the crit. variables that det. the rate of any reaction is temp. For biol. systems, the effects of temp. are convoluted with myriad (and often opposing) contributions from enzyme catalysis, protein stability, and temp.-dependent regulation, for example. We have coined the phrase "macromol. rate theory (MMRT)" to describe the temp. dependence of enzyme-catalyzed rates independent of stability or regulatory processes. Central to MMRT is the observation that enzyme-catalyzed reactions occur with significant values of ΔCp‡ that are in general neg. That is, the heat capacity (Cp) for the enzyme-substrate complex is generally larger than the Cp for the enzyme-transition state complex. Consistent with a classical description of enzyme catalysis, a neg. value for ΔCp‡ is the result of the enzyme binding relatively weakly to the substrate and very tightly to the transition state. This observation of neg. ΔCp‡ has important implications for the temp. dependence of enzyme-catalyzed rates. Here, we lay out the fundamentals of MMRT. We present a no. of hypotheses that arise directly from MMRT including a theor. justification for the large size of enzymes and the basis for their optimum temps. We rationalize the behavior of psychrophilic enzymes and describe a "psychrophilic trap" which places limits on the evolution of enzymes in low temp. environments. One of the defining characteristics of biol. is catalysis of chem. reactions by enzymes, and enzymes drive much of metab. Therefore, we also expect to see characteristics of MMRT at the level of cells, whole organisms, and even ecosystems.
- 6Arcus, V. L.; Mulholland, A. J. Temperature, Dynamics, and Enzyme-Catalyzed Reaction Rates. Annu. Rev. Biophys. 2020, 49 (1), 163– 180, DOI: 10.1146/annurev-biophys-121219-0815206https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXit1Chs7s%253D&md5=9f2034e247a628abff7e178ab402f9b5Temperature, Dynamics, and Enzyme-Catalyzed Reaction RatesArcus, Vickery L.; Mulholland, Adrian J.Annual Review of Biophysics (2020), 49 (), 163-180CODEN: ARBNCV; ISSN:1936-122X. (Annual Reviews)We review the adaptations of enzyme activity to different temps. Psychrophilic (cold-adapted) enzymes show significantly different activation parameters (lower activation enthalpies and entropies) from their mesophilic counterparts. Furthermore, there is increasing evidence that the temp. dependence of many enzyme-catalyzed reactions is more complex than is widely believed. Many enzymes show curvature in plots of activity vs. temp. that is not accounted for by denaturation or unfolding. This is explained by macromol. rate theory: A neg. activation heat capacity for the rate-limiting chem. step leads directly to predictions of temp. optima; both entropy and enthalpy are temp. dependent. Fluctuations in the transition state ensemble are reduced compared to the ground state. We show how investigations combining expt. with mol. simulation are revealing fundamental details of enzyme thermoadaptation that are relevant for understanding aspects of enzyme evolution. Simulations can calc. relevant thermodn. properties (such as activation enthalpies, entropies, and heat capacities) and reveal the mol. mechanisms underlying exptl. obsd. behavior.
- 7Åqvist, J. Computer Simulations Reveal an Entirely Entropic Activation Barrier for the Chemical Step in a Designer Enzyme. ACS Catal. 2022, 12 (2), 1452– 1460, DOI: 10.1021/acscatal.1c05814There is no corresponding record for this reference.
- 8Åqvist, J.; van der Ent, F. Calculation of Heat Capacity Changes in Enzyme Catalysis and Ligand Binding. J. Chem. Theory Comput. 2022, 18 (10), 6345– 6353, DOI: 10.1021/acs.jctc.2c00646There is no corresponding record for this reference.
- 9Blomberg, R.; Kries, H.; Pinkas, D. M.; Mittl, P. R. E.; Grütter, M. G.; Privett, H. K.; Mayo, S. L.; Hilvert, D. Precision Is Essential for Efficient Catalysis in an Evolved Kemp Eliminase. Nature 2013, 503 (7476), 418– 421, DOI: 10.1038/nature126239https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhslSnsb%252FI&md5=882663ec6c0f1e00e3fd7912423bd259Precision is essential for efficient catalysis in an evolved Kemp eliminaseBlomberg, Rebecca; Kries, Hajo; Pinkas, Daniel M.; Mittl, Peer R. E.; Gruetter, Markus G.; Privett, Heidi K.; Mayo, Stephen L.; Hilvert, DonaldNature (London, United Kingdom) (2013), 503 (7476), 418-421CODEN: NATUAS; ISSN:0028-0836. (Nature Publishing Group)Linus Pauling established the conceptual framework for understanding and mimicking enzymes more than six decades ago. The notion that enzymes selectively stabilize the rate-limiting transition state of the catalyzed reaction relative to the bound ground state reduces the problem of design to one of mol. recognition. Nevertheless, past attempts to capitalize on this idea, for example by using transition state analogs to elicit antibodies with catalytic activities, have generally failed to deliver true enzymic rates. The advent of computational design approaches, combined with directed evolution, has provided an opportunity to revisit this problem. Starting from a computationally designed catalyst for the Kemp elimination-a well-studied model system for proton transfer from carbon-we show that an artificial enzyme can be evolved that accelerates an elementary chem. reaction 6 × 108-fold, approaching the exceptional efficiency of highly optimized natural enzymes such as triosephosphate isomerase. A 1.09 Å resoln. crystal structure of the evolved enzyme indicates that familiar catalytic strategies such as shape complementarity and precisely placed catalytic groups can be successfully harnessed to afford such high rate accelerations, making us optimistic about the prospects of designing more sophisticated catalysts.
- 10Kries, H.; Bloch, J. S.; Bunzel, H. A.; Pinkas, D. M.; Hilvert, D. Contribution of Oxyanion Stabilization to Kemp Eliminase Efficiency. ACS Catal. 2020, 10 (8), 4460– 4464, DOI: 10.1021/acscatal.0c0057510https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXlt1Cru7o%253D&md5=ff017d9533da239df9c5ec0df71243c9Contribution of oxyanion stabilization to Kemp eliminase efficiencyKries, Hajo; Bloch, Joel S.; Bunzel, H. Adrian; Pinkas, Daniel M.; Hilvert, DonaldACS Catalysis (2020), 10 (8), 4460-4464CODEN: ACCACS; ISSN:2155-5435. (American Chemical Society)Important reactions in biol. and biocatalysis involve proton abstraction from carbon. When the resulting anionic charge is delocalized from carbon to an oxygen atom, these deprotonations can be catalytically accelerated by oxyanion stabilization. Oxyanion stabilization by a glutamine side chain (Gln50) was thought to accelerate C-H proton abstraction in HG3.17, a computationally designed biocatalyst that had been evolutionarily optimized to enzyme-like efficiency. We present kinetic data and crystal structures at at. resoln. for six Gln50 mutants that indicate a surprisingly small advantage of the hydrogen-bond donor glutamine over "greasy" methionine. However, tightly packed active sites (Gln, Met, Phe)-greasy or not-perform consistently better than water-filled oxyanion holes found with other substitutions (His, Ser, Ala, Lys). Although oxyanion stabilization appears to contribute modestly to HG3.17 efficiency, the role of Gln50 is mechanistically more complex than initially thought, underscoring the importance of multifactorial approaches for the design of enzymic oxyanion holes in the future.
- 11Otten, R.; Pádua, R. A. P.; Bunzel, H. A.; Nguyen, V.; Pitsawong, W.; Patterson, M.; Sui, S.; Perry, S. L.; Cohen, A. E.; Hilvert, D.; Kern, D. How Directed Evolution Reshapes the Energy Landscape in an Enzyme to Boost Catalysis. Science 2020, 370 (6523), 1442– 1446, DOI: 10.1126/science.abd362311https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXis1KksLzI&md5=7900ea67d0d68d450fa5a4dc54757c65How directed evolution reshapes the energy landscape in an enzyme to boost catalysisOtten, Renee; Padua, Ricardo A. P.; Bunzel, H. Adrian; Nguyen, Vy; Pitsawong, Warintra; Patterson, MacKenzie; Sui, Shuo; Perry, Sarah L.; Cohen, Aina E.; Hilvert, Donald; Kern, DorotheeScience (Washington, DC, United States) (2020), 370 (6523), 1442-1446CODEN: SCIEAS; ISSN:1095-9203. (American Association for the Advancement of Science)The advent of biocatalysts designed computationally and optimized by lab. evolution provides an opportunity to explore mol. strategies for augmenting catalytic function. Applying a suite of NMR, crystallog., and stopped-flow techniques to an enzyme designed for an elementary proton transfer reaction, we show how directed evolution gradually altered the conformational ensemble of the protein scaffold to populate a narrow, highly active conformational ensemble and accelerate this transformation by nearly nine orders of magnitude. Mutations acquired during optimization enabled global conformational changes, including high-energy backbone rearrangements, that cooperatively organized the catalytic base and oxyanion stabilizer, thus perfecting transition-state stabilization. The development of protein catalysts for many chem. transformations could be facilitated by explicitly sampling conformational substates during design and specifically stabilizing productive substates over all unproductive conformations.
- 12Chovancova, E.; Pavelka, A.; Benes, P.; Strnad, O.; Brezovsky, J.; Kozlikova, B.; Gora, A.; Sustr, V.; Klvana, M.; Medek, P.; Biedermannova, L.; Sochor, J.; Damborsky, J. CAVER 3.0: A Tool for the Analysis of Transport Pathways in Dynamic Protein Structures. PLOS Comput. Biol. 2012, 8 (10), e1002708 DOI: 10.1371/journal.pcbi.100270812https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38Xhs1ansbfI&md5=aff24be751fef33d531b446cf6ab86c5CAVER 3.0: a tool for the analysis of transport pathways in dynamic protein structuresChovancova, Eva; Pavelka, Antonin; Benes, Petr; Strnad, Ondrej; Brezovsky, Jan; Kozlikova, Barbora; Gora, Artur; Sustr, Vilem; Klvana, Martin; Medek, Petr; Biedermannova, Lada; Sochor, Jiri; Damborsky, JiriPLoS Computational Biology (2012), 8 (10), e1002708CODEN: PCBLBG; ISSN:1553-7358. (Public Library of Science)Tunnels and channels facilitate the transport of small mols., ions and water solvent in a large variety of proteins. Characteristics of individual transport pathways, including their geometry, physico-chem. properties and dynamics are instrumental for understanding of structure-function relationships of these proteins, for the design of new inhibitors and construction of improved biocatalysts. CAVER is a software tool widely used for the identification and characterization of transport pathways in static macromol. structures. Herein we present a new version of CAVER enabling automatic anal. of tunnels and channels in large ensembles of protein conformations. CAVER 3.0 implements new algorithms for the calcn. and clustering of pathways. A trajectory from a mol. dynamics simulation serves as the typical input, while detailed characteristics and summary statistics of the time evolution of individual pathways are provided in the outputs. To illustrate the capabilities of CAVER 3.0, the tool was applied for the anal. of mol. dynamics simulation of the microbial enzyme haloalkane dehalogenase DhaA. CAVER 3.0 safely identified and reliably estd. the importance of all previously published DhaA tunnels, including the tunnels closed in DhaA crystal structures. Obtained results clearly demonstrate that anal. of mol. dynamics simulation is essential for the estn. of pathway characteristics and elucidation of the structural basis of the tunnel gating. CAVER 3.0 paves the way for the study of important biochem. phenomena in the area of mol. transport, mol. recognition and enzymic catalysis. The software is freely available as a multiplatform command-line application online.
- 13Isaksen, G. V.; Åqvist, J.; Brandsdal, B. O. Enzyme Surface Rigidity Tunes the Temperature Dependence of Catalytic Rates. Proc. Natl. Acad. Sci. U. S. A. 2016, 113 (28), 7822– 7827, DOI: 10.1073/pnas.160523711313https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XhtFentrvK&md5=8c0c4323f08439a5707eb0f81449eb08Enzyme surface rigidity tunes the temperature dependence of catalytic ratesIsaksen, Geir Villy; Aaqvist, Johan; Brandsdal, Bjoern OlavProceedings of the National Academy of Sciences of the United States of America (2016), 113 (28), 7822-7827CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)The structural origin of enzyme adaptation to low temp., allowing efficient catalysis of chem. reactions even near the f.p. of water, remains a fundamental puzzle in biocatalysis. A remarkable universal fingerprint shared by all cold-active enzymes is a redn. of the activation enthalpy accompanied by a more neg. entropy, which alleviates the exponential decrease in chem. reaction rates caused by lowering of the temp. Here, the authors explored the role of protein surface mobility in detg. this enthalpy-entropy balance. The effects of modifying surface rigidity in cold- and warm-active trypsins were demonstrated here by calcn. of high-precision Arrhenius plots and thermodn. activation parameters for the peptide hydrolysis reaction, using extensive computer simulations. The protein surface flexibility was systematically varied by applying positional restraints, causing the remarkable effect of turning the cold-active trypsin into a variant with mesophilic characteristics without changing the amino acid sequence. Furthermore, the authors showed that just restraining a key surface loop caused the same effect as a point mutation in that loop between the cold- and warm-active trypsin. Importantly, changes in the activation enthalpy-entropy balance of up to 10 kcal/mol were almost perfectly balanced at room temp., whereas they yielded significantly higher rates at low temps. for the cold-adapted enzyme.
- 14van der Kamp, M. W.; Prentice, E. J.; Kraakman, K. L.; Connolly, M.; Mulholland, A. J.; Arcus, V. L. Dynamical Origins of Heat Capacity Changes in Enzyme-Catalysed Reactions. Nat. Commun. 2018, 9 (1), 1177, DOI: 10.1038/s41467-018-03597-y14https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC1MnjsFCksg%253D%253D&md5=5d8a0a11225953507fc64977c47d5126Dynamical origins of heat capacity changes in enzyme-catalysed reactionsvan der Kamp Marc W; van der Kamp Marc W; Connolly Michael; Mulholland Adrian J; Prentice Erica J; Kraakman Kirsty L; Arcus Vickery LNature communications (2018), 9 (1), 1177 ISSN:.Heat capacity changes are emerging as essential for explaining the temperature dependence of enzyme-catalysed reaction rates. This has important implications for enzyme kinetics, thermoadaptation and evolution, but the physical basis of these heat capacity changes is unknown. Here we show by a combination of experiment and simulation, for two quite distinct enzymes (dimeric ketosteroid isomerase and monomeric alpha-glucosidase), that the activation heat capacity change for the catalysed reaction can be predicted through atomistic molecular dynamics simulations. The simulations reveal subtle and surprising underlying dynamical changes: tightening of loops around the active site is observed, along with changes in energetic fluctuations across the whole enzyme including important contributions from oligomeric neighbours and domains distal to the active site. This has general implications for understanding enzyme catalysis and demonstrating a direct connection between functionally important microscopic dynamics and macroscopically measurable quantities.
- 15Mey, A. S. J. S.; Allen, B. K.; Macdonald, H. E. B.; Chodera, J. D.; Hahn, D. F.; Kuhn, M.; Michel, J.; Mobley, D. L.; Naden, L. N.; Prasad, S.; Rizzi, A.; Scheen, J.; Shirts, M. R.; Tresadern, G.; Xu, H. Best Practices for Alchemical Free Energy Calculations [Article v1.0]. Living J. Comput. Mol. Sci. 2020, 2 (1), 18378, DOI: 10.33011/livecoms.2.1.18378There is no corresponding record for this reference.
- 16Prabhu, N. V.; Sharp, K. A. Heat Capacity in Proteins. Annu. Rev. Phys. Chem. 2005, 56 (1), 521– 548, DOI: 10.1146/annurev.physchem.56.092503.14120216https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2MXps1Grtrs%253D&md5=55b0d3f7c11cbf6606941a28c3404143Heat capacity in proteinsPrabhu, Ninad V.; Sharp, Kim A.Annual Review of Physical Chemistry (2005), 56 (), 521-548CODEN: ARPLAP; ISSN:0066-426X. (Annual Reviews Inc.)A review. Heat capacity (Cp) is one of several major thermodn. quantities commonly measured in proteins. With more than half a dozen definitions, it is the hardest of these quantities to understand in phys. terms, but the richest in insight. There are many ramifications of obsd. Cp changes: The sign distinguishes apolar from polar solvation. It imparts a temp. (T) dependence to entropy and enthalpy that may change their signs and which of them dominate. Protein unfolding usually has a pos. ΔCp, producing a max. in stability and sometimes cold denaturation. There are two heat capacity contributions, from hydration and protein-protein interactions; which dominates in folding and binding is an open question. Theor. work to date has dealt mostly with the hydration term and can account, at least semiquant., for the major Cp-related features: the pos. and neg. Cp of hydration for apolar and polar groups, resp.; the convergence of apolar group hydration entropy at T ≈ 112°C; the decrease in apolar hydration Cp with increasing T; and the T-max. in protein stability and cold denaturation.