A Comparative Study for the Accuracy of Three Molecular Docking Programs Using HIV-1 Protease Inhibitors as a Model
DOI:
https://doi.org/10.31351/vol31iss2pp160-168Abstract
Flexible molecular docking is a computational method of structure-based drug design to evaluate binding interactions between receptor and ligand and identify the ligand conformation within the receptor pocket. Currently, various molecular docking programs are extensively applied; therefore, realizing accuracy and performance of the various docking programs could have a significant value. In this comparative study, the performance and accuracy of three widely used non-commercial docking software (AutoDock Vina, 1-Click Docking, and UCSF DOCK) was evaluated through investigations of the predicted binding affinity and binding conformation of the same set of small molecules (HIV-1 protease inhibitors) and a protein target HIV-1 protease enzyme. The tested sets are composed of eight receptor-ligand complexes with high resolution crystal structures downloaded from Protein Data Bank website. Molecular dockings were applied between approved HIV-1 protease inhibitors and the HIV-1 protease using AutoDock Vina, 1-Click Docking, and DOCK6. Then, docking poses of the top-ranked solution was realized using UCSF Chimera. Furthermore, Pearson correlation coefficient (r) and coefficient of determination (r2) between the experimental results and the top scored docking results of each program were calculated using Graphpad prism V9.2. After comparing saquinavir top scored binding poses of each docking program with the crystal structure, various conformational changes were observed. Moreover, according to the relative comparison between the top ranked calculated ?Gbinding values against the experimental results, r2 value of AutoDock Vina, 1-Click Docking, and DOCK6 were 0.65, 0.41, and 0.005, respectively. The outcome of this study shows that the top scored binding free energy could not produce the best pose prediction. In addition, AutoDock Vina results have the highest correlation with the experimental results.
How to Cite
Publication Dates
References
Sinha S, Vohora D. Chapter 2 - Drug Discovery and Development: An Overview. In: Vohora D, Singh G, editors. Pharmaceutical Medicine and Translational Clinical Research. Boston: Academic Press; 2018. p. 19-32. DOI: https://doi.org/10.1016/B978-0-12-802103-3.00002-X.
Batool M, Ahmad B, Choi S. A Structure-Based Drug Discovery Paradigm. Int J Mol Sci. 2019;20(11):1-18. DOI: 10.3390/ijms20112783.
Fan J, Fu A, Zhang L. Progress in molecular docking. Quantitative Biology. 2019:1-7. DOI: https://doi.org/10.1007/s40484-019-0172-y.
Sulimov VB, Kutov DC, Sulimov AV. Advances in docking. Current medicinal chemistry. 2019;26(42):7555-7580. DOI: https://doi.org/10.2174/0929867325666180904115000.
Dong D, Xu Z, Zhong W, Peng S. Parallelization of Molecular Docking: A Review. Curr Top Med Chem. 2018;18(12):1015-1028. DOI: 10.2174/ 1568026618666180821145215.
Torres PHM, Sodero ACR, Jofily P, Silva-Jr FP. Key Topics in Molecular Docking for Drug Design. Int J Mol Sci. 2019;20(18):1-29. DOI: 10.3390/ijms20184574.
Salman MM, Al-Obaidi Z, Kitchen P, Loreto A, Bill RM, Wade-Martins R. Advances in Applying Computer-Aided Drug Design for Neurodegenerative Diseases. International journal of molecular sciences. 2021;22(9):4688. DOI: 10.3390/ijms22094688.
Kiss R, Sandor M, Szalai FA. http://Mcule.com: a public web service for drug discovery. Journal of Cheminformatics. 2012;4(S1). DOI: 10.1186/1758-2946-4-s1-p17.
Di Filippo JI, Cavasotto CN. Guided structure-based ligand identification and design via artificial intelligence modeling. Expert opinion on drug discovery. 2021:1-8. DOI: 10.1080/17460441.2021.1979514.
Shaker B, Tran MK, Jung C, Na D. Introduction of Advanced Methods for Structure-based Drug Discovery. Current Bioinformatics. 2021;16(3):351-363. DOI: http://dx.doi.org/10.2174/1574893615999200703113200.
Pagadala NS, Syed K, Tuszynski J. Software for molecular docking: a review. Biophys Rev. 2017;9(2):91-102. DOI: 10.1007/s12551-016-0247-1.
Saikia SaB, M. Molecular Docking: Challgenges, Advances and its Use in Drug Discovery Perspective. Current Drug Targets. 2019;20(5):1389-4501. DOI: https:// doi.org/ 10.2174/1389450119666181022153016.
Amaro RE, Baudry J, Chodera J, Demir O, McCammon JA, Miao Y, et al. Ensemble Docking in Drug Discovery. Biophys J. 2018;114(10):2271-2278. DOI: 10.1016/j.bpj.2018.02.038.
Wang Z, Sun H, Yao X, Li D, Xu L, Li Y, et al. Comprehensive evaluation of ten docking programs on a diverse set of protein-ligand complexes: the prediction accuracy of sampling power and scoring power. Physical chemistry chemical physics : PCCP. 2016;18(18):12964-12975. DOI: 10.1039/c6cp01555g.
Maia EHB, Assis LC, de Oliveira TA, da Silva AM, Taranto AG. Structure-Based Virtual Screening: From Classical to Artificial Intelligence. Front Chem. 2020;8:343. DOI: 10.3389/fchem.2020.00343.
Caballero J. The latest automated docking technologies for novel drug discovery. Expert opinion on drug discovery. 2021;16(6):625-645. DOI: 10.1080/17460441.2021.1858793.
K. Hadi M, T. Abduljabbar T. Synthesis, Characterization and Antibacterial Evaluation of Some Coumarin Derivatives. Iraqi Journal of Pharmaceutical Sciences. 2021;30(1):249-257. DOI: 10.31351/vol30iss1pp249-257.
Xu Z, Chen Q, Zhang Y, Liang C. Coumarin-based derivatives with potential anti-HIV activity. Fitoterapia. 2021;150:104863. DOI: https://doi.org/10.1016/j.fitote.2021.104863.
Ghosh AK, Osswald HL, Prato G. Recent Progress in the Development of HIV-1 Protease Inhibitors for the Treatment of HIV/AIDS. J Med Chem. 2016;59(11):5172-5208. DOI: 10.1021/acs.jmedchem.5b01697.
Palese LL. Analysis of the conformations of the HIV-1 protease from a large crystallographic data set. Data Brief. 2017;15:696-700. DOI: 10.1016/j.dib.2017.09.076.
Lv Z, Chu Y, Wang Y. HIV protease inhibitors: a review of molecular selectivity and toxicity. HIV/AIDS (Auckland, NZ). 2015;7:95-104. DOI: 10.2147/HIV.S79956.
Piliero PJ. Atazanavir: a novel HIV-1 protease inhibitor. Expert Opin Investig Drugs. 2002;11(9):1295-1301. DOI: 10.1517/13543784.11.9.1295.
Kozisek M, Lepsik M, Grantz Saskova K, Brynda J, Konvalinka J, Rezacova P. Thermodynamic and structural analysis of HIV protease resistance to darunavir - analysis of heavily mutated patient-derived HIV-1 proteases. FEBS J. 2014;281(7):1834-1847. DOI: 10.1111/febs.12743.
Eberhardt J, Santos-Martins D, Tillack A, Forli S. AutoDock Vina 1.2. 0: new docking methods, expanded force field, and Python bindings. 2021. DOI: 10.26434/ chemrxiv. 14774223.v1.
Allen WJ, Balius TE, Mukherjee S, Brozell SR, Moustakas DT, Lang PT, et al. DOCK 6: Impact of new features and current docking performance. J Comput Chem. 2015 ;36(15):1132-1156. DOI: 10. 1002 /jcc. 23905.
Tie Y, Kovalevsky AY, Boross P, Wang YF, Ghosh AK, Tozser J, et al. Atomic resolution crystal structures of HIV-1 protease and mutants V82A and I84V with saquinavir. Proteins. 2007;67(1):232-242. DOI: 10.1002/prot.21304.
Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, et al. The Protein Data Bank. Nucleic acids research. 2000;28(1):235-242. DOI: https://doi.org/10.1093/nar/28.1.235.
Schrodinger, LLC. The PyMOL Molecular Graphics System, Version 1.3r1. 2010.
ChemAxon M. www.chemaxon.com/products/marvin. Budapest: Jan; 2016.
Butt SS, Badshah Y, Shabbir M, Rafiq M. Molecular Docking Using Chimera and Autodock Vina Software for Nonbioinformaticians. JMIR Bioinformatics Biotechnol. 2020;1(1):e14232. DOI: 10.2196/14232.
Kim S, Thiessen PA, Bolton EE, Chen J, Fu G, Gindulyte A, et al. PubChem Substance and Compound databases. Nucleic acids research. 2016;44(D1):D1202-1213. DOI: 10.1093/nar/gkv951.
Odhar HA, Ahjel SW, Albeer A, Hashim AF, Rayshan AM, Humadi SS. Molecular docking and dynamics simulation of FDA approved drugs with the main protease from 2019 novel coronavirus. Bioinformation. 2020;16(3):236-244. DOI: 10.6026/97320630016236.
Trott O, Olson AJ. AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem. 2010;31(2):455-461. DOI: 10.1002/jcc.21334.
Hornak V, Simmerling C. Targeting structural flexibility in HIV-1 protease inhibitor binding. Drug discovery today. 2007;12(3-4):132-138. DOI: 10.1016/j.drudis.2006.12.011.
Ahsan M, Pindi C, Senapati S. Electrostatics Plays a Crucial Role in HIV-1 Protease Substrate Binding, Drugs Fail to Take Advantage. Biochemistry. 2020;59(36):3316-3331. DOI: 10.1021/acs.biochem.0c00341.
Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC, et al. UCSF chimera - A visualization system for exploratory research and analysis. J Comput Chem. 2004;25(13):1605-1612. DOI: 10.1002/jcc.20084.
Swift ML. GraphPad Prism, Data Analysis, and Scientific Graphing. Journal of Chemical Information and Computer Sciences. 1997;37(2):411-412. DOI: 10.1021/ci960402j.
Kaneria M, Parmar J, Rakholiya K. Molecular docking and drug design of phytoconstituents from Couroupita guianensis – An in silico perspective. Journal of Pharmacognosy and Phytochemistry. 2019;8(6):53-60.
Li J, Fu A, Zhang L. An Overview of Scoring Functions Used for Protein–Ligand Interactions in Molecular Docking. Interdisciplinary Sciences: Computational Life Sciences. 2019;11(2):320-328. DOI: 10.1007/s12539-019-00327-w.
Kozisek M, Bray J, Rezacova P, Saskova K, Brynda J, Pokorna J, et al. Molecular analysis of the HIV-1 resistance development: enzymatic activities, crystal structures, and thermodynamics of nelfinavir-resistant HIV protease mutants. J Mol Biol. 2007;374(4):1005-1016. DOI: 10.1016/j.jmb.2007.09.083.
King NM, Prabu-Jeyabalan M, Bandaranayake RM, Nalam MN, Nalivaika EA, Ozen A, et al. Extreme entropy-enthalpy compensation in a drug-resistant variant of HIV-1 protease. ACS chemical biology. 2012;7(9):1536-1546. DOI: 10.1021/cb300191k.
Dierynck I, De Wit M, Gustin E, Keuleers I, Vandersmissen J, Hallenberger S, et al. Binding kinetics of darunavir to human immunodeficiency virus type 1 protease explain the potent antiviral activity and high genetic barrier. J Virol. 2007;81(24):13845-13851. DOI: 10.1128/JVI.01184-07.
Krohn A, Redshaw S, Ritchie JC, Graves BJ, Hatada MH. Novel binding mode of highly potent HIV-proteinase inhibitors incorporating the (R)-hydroxyethylamine isostere. Journal of Medicinal Chemistry. 1991;34(11):3340-3342. DOI: 10.1021/jm00115a028.
Moore DS, Notz W, Fligner MA. The Basic Practice of Statistics. 2013. W.H. Freeman and Company; [15-24]. Available from: https://books.google.iq/books?id=aw61ygAACAAJ.
Li X, Li Y, Cheng T, Liu Z, Wang R. Evaluation of the performance of four molecular docking programs on a diverse set of protein-ligand complexes. J Comput Chem. 2010;31(11):2109-2125. DOI: 10.1002/jcc.21498
Downloads
Published
Issue
Section
License
Copyright (c) 2022 Iraqi Journal of Pharmaceutical Sciences ( P-ISSN 1683 - 3597 E-ISSN 2521 - 3512)
This work is licensed under a Creative Commons Attribution 4.0 International License.