Abstract
Molecular docking refers to computational methods for the prediction of the binding mode and binding affinity between two molecules. Over decades of development, protein–ligand docking methods have been widely used for in silico screening of molecular libraries for drug candidates, serving as a valuable tool in structure-based drug design. MDock is a protein–ligand docking suite originally released from our laboratory in 2007, which incorporates the iteratively derived knowledge-based scoring function and the ensemble docking method. In this chapter, we describe the methodology and usage of MDock for molecular docking and in silico screening. The MDock suite is freely available to academic users through applications at http://zoulab.dalton.missouri.edu/mdock.htm.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Brooijmans N, Kuntz ID (2003) Molecular recognition and docking algorithms. Annu Rev Biophys Biomol Struct 32(1):335–373
Kitchen DB, Decornez H, Furr JR, Bajorath J (2004) Docking and scoring in virtual screening for drug discovery: methods and applications. Nat Rev Drug Discov 3(11):935–949
Huang S-Y, Zou X (2010) Advances and challenges in protein-ligand docking. Int J Mol Sci 11(8):3016–3034
Huang S-Y, Grinter SZ, Zou X (2010) Scoring functions and their evaluation methods for protein–ligand docking: recent advances and future directions. Phys Chem Chem Phys 12(40):12899–12908
Sousa SF, Ribeiro AJM, Coimbra JTS, Neves RPP, Martins SA, Moorthy NSHN, Fernandes PA, Ramos MJ (2013) Protein-ligand docking in the new millennium – a retrospective of 10 years in the field. Curr Med Chem 20(18):2296–2314
Grinter SZ, Zou X (2014) Challenges, applications, and recent advances of protein-ligand docking in structure-based drug design. Molecules 19(7):10150–10176
Huang S-Y, Zou X (2007) Ensemble docking of multiple protein structures: considering protein structural variations in molecular docking. Proteins Struct Funct Bioinf 66(2):399–421
Kuntz ID, Blaney JM, Oatley SJ, Langridge R, Ferrin TE (1982) A geometric approach to macromolecule-ligand interactions. J Mol Biol 161(2):269–288
Ewing TJA, Kuntz ID (1997) Critical evaluation of search algorithms for automated molecular docking and database screening. J Comput Chem 18(9):1175–1189
Huang S-Y, Zou X (2006) An iterative knowledge-based scoring function to predict protein–ligand interactions: I. Derivation of interaction potentials. J Comput Chem 27(15):1866–1875
Huang S-Y, Zou X (2006) An iterative knowledge-based scoring function to predict protein–ligand interactions: II. Validation of the scoring function. J Comput Chem 27(15):1876–1882
Huang S-Y, Zou X (2011) Scoring and lessons learned with the CSAR benchmark using an improved iterative knowledge-based scoring function. J Chem Inf Model 51(9):2097–2106
Huang S-Y, Zou X (2007) Efficient molecular docking of NMR structures: application to HIV-1 protease. Protein Sci 16(1):43–51
Dunbar JB Jr, Smith RD, Yang C-Y, Ung PM-U, Lexa KW, Khazanov NA, Stuckey JA, Wang S, Carlson HA (2011) CSAR benchmark exercise of 2010: selection of the protein–ligand complexes. J Chem Inf Model 51(9):2036–2046
Damm-Ganamet KL, Smith RD, Dunbar JB Jr, Stuckey JA, Carlson HA (2013) CSAR benchmark exercise 2011–2012: evaluation of results from docking and relative ranking of blinded congeneric series. J Chem Inf Model 53(8):1853–1870
Dunbar JB Jr, Smith RD, Damm-Ganamet KL, Ahmed A, Esposito EX, Delproposto J, Chinnaswamy K, Kang Y-N, Kubish G, Gestwicki JE, Stuckey JA, Carlson HA (2013) CSAR data set release 2012: ligands, affinities, complexes, and docking decoys. J Chem Inf Model 53(8):1842–1852
Moustakas DT, Lang PT, Pegg S, Pettersen E, Kuntz ID, Brooijmans N, Rizzo RC (2006) Development and validation of a modular, extensible docking program: Dock 5. J Comput Aided Mol Des 20(10–11):601–619
Wang R, Fang X, Lu Y, Yang C-Y, Wang S (2005) The PDBbind database: methodologies and updates. J Med Chem 48(12):4111–4119
Cheng T, Li X, Li Y, Liu Z, Wang R (2009) Comparative assessment of scoring functions on a diverse test set. J Chem Inf Model 49(4):1079–1093
Yan C, Grinter SZ, Merideth BR, Ma Z, Zou X (2015) Iterative knowledge-based scoring functions derived from rigid and flexible decoy structures: evaluation with the 2013 and 2014 CSAR benchmarks. J Chem Inf Model. doi:10.1021/acs.jcim.5b00504
Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC, Ferrin TE (2004) UCSF chimera—a visualization system for exploratory research and analysis. J Comput Chem 25(13):1605–1612
Hawkins PCD, Skillman AG, Warren GL, Ellingson BA, Stahl MT (2010) Conformer generation with omega: algorithm and validation using high quality structures from the protein databank and Cambridge structural database. J Chem Inf Model 50(4):572–584
Hawkins PCD, Nicholls A (2012) Conformer generation with omega: learning from the data set and the analysis of failures. J Chem Inf Model 52(11):2919–2936
Laurie ATR, Jackson RM (2005) Q-sitefinder: an energy-based method for the prediction of protein–ligand binding sites. Bioinformatics 21(9):1908–1916
Wass MN, Kelley LA, Sternberg MJE (2010) 3DLigandSite: predicting ligand-binding sites using similar structures. Nucleic Acids Res. doi:10.1093/nar/gkq406
Heo L, Shin W-H, Lee MS, Seok C (2014) Galaxysite: ligand-binding-site prediction by using molecular docking. Nucleic Acids Res 42(W1):W210–W214
Atwell S, Adams JM, Badger J, Buchanan MD, Feil IK, Froning KJ, Gao X, Hendle J, Keegan K, Leon BC et al (2004) A novel mode of gleevec binding is revealed by the structure of spleen tyrosine kinase. J Biol Chem 279(53):55827–55832
Grinter SZ, Liang Y, Huang S-Y, Hyder SM, Zou X (2011) An inverse docking approach for identifying new potential anti-cancer targets. J Mol Graph Model 29(6):795–799
Grinter SZ, Yan C, Huang S-Y, Jiang L, Zou X (2013) Automated large-scale file preparation, docking, and scoring: evaluation of ITScore and STScore using the 2012 community structure-activity resource benchmark. J Chem Inf Model 53(8):1905–1914
Acknowledgements
Xiaoqin Zou is supported by NIH grant R01GM088517, NSF CAREER Award DBI0953839, and American Heart Association (Midwest Affiliate) 13GRNT16990076. The computations were performed on the HPC resources at the University of Missouri Bioinformatics Consortium (UMBC).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer Science+Business Media New York
About this protocol
Cite this protocol
Yan, C., Zou, X. (2015). MDock: An Ensemble Docking Suite for Molecular Docking, Scoring and In Silico Screening. In: Zhang, W. (eds) Computer-Aided Drug Discovery. Methods in Pharmacology and Toxicology. Humana Press, New York, NY. https://doi.org/10.1007/7653_2015_62
Download citation
DOI: https://doi.org/10.1007/7653_2015_62
Published:
Publisher Name: Humana Press, New York, NY
Print ISBN: 978-1-4939-3519-2
Online ISBN: 978-1-4939-3521-5
eBook Packages: Springer Protocols