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Haptic-Assisted Interactive Molecular Docking Incorporating Receptor Flexibility

Cite this: J. Chem. Inf. Model. 2019, 59, 6, 2900–2912
Publication Date (Web):April 10, 2019
https://doi.org/10.1021/acs.jcim.9b00112
Copyright © 2019 American Chemical Society

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    Abstract

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    Haptic-assisted interactive docking tools immerse the user in an environment where intuition and knowledge can be used to help guide the docking process. Here we present such a tool where the user “holds” a rigid ligand via a haptic device through which they feel interaction forces with a flexible receptor biomolecule. To ensure forces transmitted through the haptic device are smooth and stable, they must be updated at a rate greater than 500 Hz. Due to this time constraint, the majority of haptic docking tools do not attempt to model the conformational changes that would occur when molecules interact during binding. Our haptic-assisted docking tool, “Haptimol FlexiDock”, models a receptor’s conformational response to forces of interaction with a ligand while maintaining the required haptic refresh rate. In order to model receptor flexibility we use the method of linear response for which we determine the variance-covariance matrix of atomic fluctuations from the trajectory of an explicit-solvent molecular dynamics simulation of the ligand-free receptor molecule. The key to satisfying the time constraint is an eigenvector decomposition of the variance–covariance matrix which enables a good approximation to the conformational response of the receptor to be calculated rapidly. This exploits a feature of protein dynamics whereby most fluctuation occurs within a relatively small subspace. The method is demonstrated on glutamine binding protein in interaction with glutamine and maltose binding protein in interaction with maltose. For both proteins the movement that occurs when the ligand is docked near to its binding site matches the experimentally determined movement well. It is thought that this tool will be particularly useful for structure-based drug design.

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    • Video showing Haptimol FlexiDock in use (AVI)

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    Cited By

    This article is cited by 15 publications.

    1. Georgios Iakovou, Stephen D. Laycock, Steven Hayward. Interactive Flexible-Receptor Molecular Docking in Virtual Reality Using DockIT. Journal of Chemical Information and Modeling 2022, 62 (23) , 5855-5861. https://doi.org/10.1021/acs.jcim.2c01274
    2. Lin Liu, Torin Adamson, Lydia Tapia, Bruna Jacobson. Player Exploration Patterns in Interactive Molecular Docking with Electrostatic Visual Cues. 2023, 1-9. https://doi.org/10.1145/3623264.3624463
    3. Emilio Mateev, Maya Georgieva, Alexander Zlatkov. Assessing the Performance of GOLD, Glide and MM-GBSA on a Dataset of Hydrazide-hydrazone-based Tuberculostatics. Letters in Drug Design & Discovery 2023, 20 (10) , 1557-1568. https://doi.org/10.2174/1570180819666220512115015
    4. Steven Hayward. A Retrospective on the Development of Methods for the Analysis of Protein Conformational Ensembles. The Protein Journal 2023, 42 (3) , 181-191. https://doi.org/10.1007/s10930-023-10113-9
    5. Emilio Mateev, Maya Georgieva, Alexandrina Mateeva, Alexander Zlatkov, Shaban Ahmad, Khalid Raza, Vasco Azevedo, Debmalya Barh. Structure-Based Design of Novel MAO-B Inhibitors: A Review. Molecules 2023, 28 (12) , 4814. https://doi.org/10.3390/molecules28124814
    6. André Lanrezac, Nicolas Férey, Marc Baaden. Wielding the power of interactive molecular simulations. WIREs Computational Molecular Science 2022, 12 (4) https://doi.org/10.1002/wcms.1594
    7. Cyprien Plateau-Holleville, Simon Guionnière, Benjamin Boyer, Brian Jiménez-Garcia, Guillaume Levieux, Stéphane Mérillou, Maxime Maria, Matthieu Montes, . UDock2 : interactive real-time multi-body protein–protein docking software. Bioinformatics 2022, 39 (10) https://doi.org/10.1093/bioinformatics/btad609
    8. Emilio Viktorov Mateev, Iva Valkova, Maya Georgieva, Alexander Zlatkov. Suitable Docking Protocol for the Design of Novel Coumarin Derivatives with Selective MAO-B Effects. Journal of Molecular Docking 2021, 1 (1) , 40-47. https://doi.org/10.33084/jmd.v1i1.2357
    9. Georgios Iakovou, Mousa Alhazzazi, Steven Hayward, Stephen D Laycock, . DockIT: a tool for interactive molecular docking and molecular complex construction. Bioinformatics 2021, 36 (24) , 5698-5700. https://doi.org/10.1093/bioinformatics/btaa1059
    10. Shoichi Tanimoto, Koichi Tamura, Shigehiko Hayashi, Norio Yoshida, Haruyuki Nakano. A computational method to simulate global conformational changes of proteins induced by cosolvent. Journal of Computational Chemistry 2021, 42 (8) , 552-563. https://doi.org/10.1002/jcc.26481
    11. Udit J. Chaube, Rakesh Rawal, Abhishek B. Jha, Bhavesh Variya, Hardik G. Bhatt. Design and development of Tetrahydro-Quinoline derivatives as dual mTOR-C1/C2 inhibitors for the treatment of lung cancer. Bioorganic Chemistry 2021, 106 , 104501. https://doi.org/10.1016/j.bioorg.2020.104501
    12. Torin Adamson, Selina Bauernfeind, Bruna Jacobson, Lydia Tapia. Using player generated data to elucidate molecular docking. 2020, 1-1. https://doi.org/10.1145/3388440.3414704
    13. Luciano A. Abriata. Building blocks for commodity augmented reality-based molecular visualization and modeling in web browsers. PeerJ Computer Science 2020, 6 , e260. https://doi.org/10.7717/peerj-cs.260
    14. Torin Adamson, Julian Antolin Camarena, Lydia Tapia, Bruna Jacobson. Optimizing Low Energy Pathways in Receptor-Ligand Binding with Motion Planning. 2019, 2041-2048. https://doi.org/10.1109/BIBM47256.2019.8983169
    15. Anna Chavez, Torin Adamson, Lydia Tapia, Bruna Jacobson. A Mobile Game for Crowdsourced Molecular Docking Pathways. 2019, 1-6. https://doi.org/10.1145/3359566.3360055

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