AlteQ: a new complementarity principle-centered method for the evaluation of docking poses

Reference

• Allen, W. J., Balius, T. E., Mukherjee, S., Brozell, S. R., Moustakas, D. T., Lang, P. T., Case, D. A., Kuntz, I. D., & Rizzo, R. C. (2015). DOCK 6: Impact of new features and current docking performance. Journal of Computational Chemistry, 36(15), 1132–1156. https://doi.org/10.1002/jcc.23905
   PubMed Web of Science ®Google Scholar
• Berman, H. M., Battistuz, T., Bhat, T. N., Bluhm, W. F., Bourne, P. E., Burkhardt, K., Feng, Z., Gilliland, G. L., Iype, L., Jain, S., Fagan, P., Marvin, J., Padilla, D., Ravichandran, V., Schneider, B., Thanki, N., Weissig, H., Westbrook, J. D., & Zardecki, C. (2002). The protein data bank. Acta Crystallographica. Section D, Biological Crystallography, 58(Pt 6 No 1), 899–907. https://doi.org/10.1107/S0907444902003451
   PubMedGoogle Scholar
• Brenk, R., Vetter, S. W., Boyce, S. E., Goodin, D. B., & Shoichet, B. K. (2006). Probing molecular docking in a charged model binding site. Journal of Molecular Biology, 357(5), 1449–1470. https://doi.org/10.1016/j.jmb.2006.01.034
   PubMed Web of Science ®Google Scholar
• Cheng, T., Li, Q., Zhou, Z., Wang, Y., & Bryant, S. H. (2012). Structure-based virtual screening for drug discovery: A problem-centric review. The AAPS Journal, 14(1), 133–141. https://doi.org/10.1208/s12248-012-9322-0
   PubMed Web of Science ®Google Scholar
• Cole, J. C., Murray, C. W., Nissink, J. W. M., Taylor, R. D., & Taylor, R. (2005). Comparing protein-ligand docking programs is difficult. In Proteins: Structure, Function and Genetics, 60(3), 325–332. https://doi.org/10.1002/prot.20497
   PubMed Web of Science ®Google Scholar
• Corbeil, C. R., Williams, C. I., & Labute, P. (2012). Variability in docking success rates due to dataset preparation. Journal of Computer-Aided Molecular Design, 26(6), 775–786. https://doi.org/10.1007/s10822-012-9570-1
   PubMed Web of Science ®Google Scholar
• Friesner, R. A., Banks, J. L., Murphy, R. B., Halgren, T. A., Klicic, J. J., Mainz, D. T., Repasky, M. P., Knoll, E. H., Shelley, M., Perry, J. K., Shaw, D. E., Francis, P., & Shenkin, P. S. (2004). Glide: A new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. Journal of Medicinal Chemistry, 47(7), 1739–1749. https://doi.org/10.1021/jm0306430
   PubMed Web of Science ®Google Scholar
• Gilpin, W. (2015). PyPDB: A Python API for the protein data bank. Bioinformatics, 32(1), btv543. https://doi.org/10.1093/bioinformatics/btv543
   Web of Science ®Google Scholar
• Gohlke, H., Hendlich, M., & Klebe, G. (2000). Knowledge-based scoring function to predict protein-ligand interactions. Journal of Molecular Biology, 295(2), 337–356. https://doi.org/10.1006/jmbi.1999.3371
   PubMed Web of Science ®Google Scholar
• Grishina, M. A., & Potemkin, V. A. (2019). Topological analysis of electron density in large biomolecular systems. Current Drug Discovery Technologies, 16(4), 437–448. https://doi.org/10.2174/1570163815666180821165330
   PubMedGoogle Scholar
• Hawkins, P. C. D., Warren, G. L., Skillman, A. G., & Nicholls, A. (2008). How to do an evaluation: Pitfalls and traps. Journal of Computer-Aided Molecular Design, 22(3-4), 179–190. https://doi.org/10.1007/s10822-007-9166-3
   PubMed Web of Science ®Google Scholar
• Huang, S. Y., Grinter, S. Z., & Zou, X. (2010). Scoring functions and their evaluation methods for protein-ligand docking: Recent advances and future directions. Physical Chemistry Chemical Physics, 12(40), 12899–12908. https://doi.org/10.1039/c0cp00151a
   PubMed Web of Science ®Google Scholar
• Huang, S. Y., & Zou, X. (2010). Advances and challenges in Protein-ligand docking. International Journal of Molecular Sciences, 11(8), 3016–3034. https://doi.org/10.3390/ijms11083016
   PubMed Web of Science ®Google Scholar
• Hunter, J. D. (2007). Matplotlib: A 2D graphics environment. Computing in Science and Engineering, 9(3), 99–104. https://doi.org/10.1109/MCSE.2007.55
   Web of Science ®Google Scholar
• Jones, G., Willett, P., Glen, R. C., Leach, A. R., & Taylor, R. (1997). Development and validation of a genetic algorithm for flexible docking. Journal of Molecular Biology, 267(3), 727–748. https://doi.org/10.1006/jmbi.1996.0897
   PubMed Web of Science ®Google Scholar
• Jonsson, B.-H., & Brenk, R. (2009). Validation of docking performance in the context of a structural water molecule using model system [Master Thesis in Chemical Biology]. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-19525
   Google Scholar
• Kandagalla, S., Rimac, H., Potemkin, V. A., & Grishina, M. A. (2021). Complementarity principle in terms of electron density for the study of EGFR complexes. Future Medicinal Chemistry, 13(10), 863–875. https://doi.org/10.4155/FMC-2020-0265
   PubMed Web of Science ®Google Scholar
• Kitchen, D. B., Decornez, H., Furr, J. R., & Bajorath, J. (2004). Docking and scoring in virtual screening for drug discovery: Methods and applications. Nature Reviews Drug Discovery, 3(11), 935–949. https://doi.org/10.1038/nrd1549
   PubMed Web of Science ®Google Scholar
• Kramer, B., Rarey, M., & Lengauer, T. (1999). Evaluation of the FlexX incremental construction algorithm for protein-ligand docking. Proteins: Structure, Function, and Genetics, 37(2), 228–241. https://doi.org/10.1002/(SICI)1097-0134(19991101)37:2 < 228::AID-PROT8 > 3.0.CO;2-8
   PubMed Web of Science ®Google Scholar
• Kroemer, R. T., Vulpetti, A., McDonald, J. J., Rohrer, D. C., Trosset, J. Y., Giordanetto, F., Cotesta, S., McMartin, C., Kihlén, M., & Stouten, P. F. W. (2004). Assessment of docking poses: Interactions-based accuracy classification (IBAC) versus crystal structure deviations. Journal of Chemical Information and Computer Sciences, 44(3), 871–881. https://doi.org/10.1021/ci049970m
   PubMedGoogle Scholar
• Kufareva, I., & Abagyan, R. (2012). Methods of protein structure comparison. Methods in Molecular Biology (Clifton, N.J.), 857, 231–257. https://doi.org/10.1007/978-1-61779-588-6_10
   PubMedGoogle Scholar
• Li, J., Fu, A., & Zhang, L. (2019). An overview of scoring functions used for protein–ligand interactions in molecular docking. Interdisciplinary Sciences, Computational Life Sciences, 11(2), 320–328. https://doi.org/10.1007/S12539-019-00327-W
   PubMed Web of Science ®Google Scholar
• Morris, G. M., Ruth, H., Lindstrom, W., Sanner, M. F., Belew, R. K., Goodsell, D. S., & Olson, A. J. (2009). Software news and updates AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. Journal of Computational Chemistry, 30(16), 2785–2791. https://doi.org/10.1002/jcc.21256
   PubMed Web of Science ®Google Scholar
• Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., & Duchesnay, E. (2011). Scikit-learn: Machine learning in Python. Journal of Machine Learning Research, 12(2011), 2825-2830. http://scikit-learn.sourceforge.net.
   Google Scholar
• Pettersen, E. F., Goddard, T. D., Huang, C. C., Couch, G. S., Greenblatt, D. M., Meng, E. C., & Ferrin, T. E. (2004). UCSF Chimera—A visualization system for exploratory research and analysis. Journal of Computational Chemistry, 25(13), 1605–1612. https://doi.org/10.1002/jcc.20084
   PubMed Web of Science ®Google Scholar
• Potemkin, V. A., & Grishina, M. A. (2008). A new paradigm for pattern recognition of drugs. Journal of Computer-Aided Molecular Design, 22(6-7), 489–505. https://doi.org/10.1007/s10822-008-9203-x
   PubMed Web of Science ®Google Scholar
• Potemkin, A. V., Grishina, M. A., & Potemkin, V. A. (2017). Grid-based continual analysis of molecular interior for drug discovery, QSAR and QSPR. Current Drug Discovery Technologies, 14(3), 181-205. https://doi.org/10.2174/1570163814666170207144018
   PubMedGoogle Scholar
• Rimac, H., Grishina, M. A., & Potemkin, V. A. (2020). Electron density analysis of CDK complexes using the AlteQ method. Future Medicinal Chemistry, 12(15), 1387–1397. https://doi.org/10.4155/fmc-2020-0076
   PubMed Web of Science ®Google Scholar
• Rimac, H., Grishina, M., & Potemkin, V. (2021). Use of the complementarity principle in docking procedures: A new approach for evaluating the correctness of binding poses. Journal of Chemical Information and Modeling, 16(4), 181-205. https://doi.org/10.1021/acs.jcim.0c01382
   Google Scholar
• Rueda, M., Katritch, V., Raush, E., & Abagyan, R. (2010). SimiCon: A web tool for protein-ligand model comparison through calculation of equivalent atomic contacts. Bioinformatics (Oxford, England), 26(21), 2784–2785. https://doi.org/10.1093/bioinformatics/btq504
   PubMed Web of Science ®Google Scholar
• Ruiz-Carmona, S., Alvarez-Garcia, D., Foloppe, N., Garmendia-Doval, A. B., Juhos, S., Schmidtke, P., Barril, X., Hubbard, R. E., & Morley, S. D. (2014). rDock: A fast, versatile and open source program for docking ligands to proteins and nucleic acids. PLoS Computational Biology, 10(4), e1003571. https://doi.org/10.1371/journal.pcbi.1003571
   PubMed Web of Science ®Google Scholar
• Schulz-Gasch, T., & Stahl, M. (2004). Scoring functions for protein-ligand interactions: A critical perspective. Drug Discovery Today. Technologies, 1(3), 231–239. https://doi.org/10.1016/j.ddtec.2004.08.004
   PubMedGoogle Scholar
• Trott, O., & Olson, A. J. (2009). AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. Journal of Computational Chemistry, 31(2), NA–NA. https://doi.org/10.1002/jcc.21334
   Web of Science ®Google Scholar
• Trott, O., & Olson, A. J. (2010). AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. Journal of Computational Chemistry, 31(2), 455–461. https://doi.org/10.1002/jcc.21334
   PubMed Web of Science ®Google Scholar
• Venkatachalam, C. M., Jiang, X., Oldfield, T., & Waldman, M. (2003). LigandFit: A novel method for the shape-directed rapid docking of ligands to protein active sites. Journal of Molecular Graphics & Modelling, 21(4), 289–307. https://doi.org/10.1016/S1093-3263(02)00164-X
   PubMed Web of Science ®Google Scholar
• Vieira, T. F., & Sousa, S. F. (2019). Comparing AutoDock and Vina in ligand/decoy discrimination for virtual screening. Applied Sciences, 9(21), 4538. https://doi.org/10.3390/app9214538
   Google Scholar