Abstract
In structure-based virtual screening (SBVS), a scoring function is usually applied to rank a database of docked compounds. Docking programs are often successful in reproducing experimental binding modes; however, the estimation of binding affinity still is the Achilles’ heel of docking. The integration of SB and ligand-based (LB) methods is considered a promising strategy to increase hit rates in VS. Herein, we describe a hybrid protocol that is based on the assessment of binding mode similarity between docked compounds and a bound reference ligand. In this context, both experimental and computationally modeled poses have been successfully used as references for three-dimensional (3D) similarity calculations. In this chapter, the methods applied in recent validation studies are described.
Key words
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Heikamp K, Bajorath J (2013) The future of virtual compound screening. Chem Biol Drug Des 81:33–40. https://doi.org/10.1111/cbdd.12054
Lavecchia A, Di Giovanni C (2013) Virtual screening strategies in drug discovery: a critical review. Curr Med Chem 20:2839–2860. https://doi.org/10.2174/09298673113209990001
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 3:935–949. https://doi.org/10.1038/nrd1549
Irwin JJ, Shoichet BK (2016) Docking screens for novel ligands conferring new biology. J Med Chem 59:4103–4120. https://doi.org/10.1021/acs.jmedchem.5b02008
Gathiaka S, Liu S, Chiu M et al (2016) D3R grand challenge 2015: evaluation of protein–ligand pose and affinity predictions. J Comput Aided Mol Des 30:651–668. https://doi.org/10.1007/s10822-016-9946-8
Ripphausen P, Nisius B, Bajorath J (2011) State-of-the-art in ligand-based virtual screening. Drug Discov Today 16:372–376. https://doi.org/10.1016/j.drudis.2011.02.011
Drwal MN, Griffith R (2013) Combination of ligand- and structure-based methods in virtual screening. Drug Discov Today Technol 10:e395–e401. https://doi.org/10.1016/j.ddtec.2013.02.002
Anighoro A, Bajorath J (2016) Three-dimensional similarity in molecular docking: prioritizing ligand poses on the basis of experimental binding modes. J Chem Inf Model 56:580–587. https://doi.org/10.1021/acs.jcim.5b00745
Anighoro A, Bajorath J (2016) Binding mode similarity measures for ranking of docking poses: a case study on the adenosine A2A receptor. J Comput Aided Mol Des 30:447–456. https://doi.org/10.1007/s10822-016-9918-z
Anighoro A, Bajorath J (2017) Compound ranking on the basis of fuzzy 3D similarity improves the performance of docking into homology models of G-protein coupled receptors. ACS Omega 2:2583–2592. https://doi.org/10.1021/acsomega.7b00330
Peltason L, Bajorath J (2007) Molecular similarity analysis uncovers heterogeneous structure-activity relationships and variable activity landscapes. Chem Biol 14:489–497. https://doi.org/10.1016/j.chembiol.2007.03.011
Molecular Operating Environment (MOE), 2014.09; Chemical Computing Group Inc., 1010 Sherbooke St. West, Suite #910, Montreal, QC, Canada, 2014.
Klon AE, Héroux A, Ross LJ et al (2002) Atomic structures of human dihydrofolate reductase complexed with NADPH and two lipophilic antifolates at 1.09 a and 1.05 a resolution. J Mol Biol 320:677–693. https://doi.org/10.1016/S0022-2836(02)00469-2
Kauppi B, Jakob C, Färnegårdh M et al (2003) The three-dimensional structures of antagonistic and agonistic forms of the glucocorticoid receptor ligand-binding domain: RU-486 induces a transconformation that leads to active antagonism. J Biol Chem 278:22748–22754. https://doi.org/10.1074/jbc.M212711200
Shen C-H, Wang Y-F, Kovalevsky AY et al (2010) Amprenavir complexes with HIV-1 protease and its drug-resistant mutants altering hydrophobic clusters. FEBS J 277:3699–3714. https://doi.org/10.1111/j.1742-4658.2010.07771.x
Miyamoto N, Sakai N, Hirayama T et al (2013) Discovery of N-[5-({2-[(cyclopropylcarbonyl)amino]imidazo[1,2-b]pyridazin-6-yl}oxy)-2-methylphenyl]-1,3-dimethyl-1H-pyrazole-5-carboxamide (TAK-593), a highly potent VEGFR2 kinase inhibitor. Bioorg Med Chem 21:2333–2345. https://doi.org/10.1016/j.bmc.2013.01.074
Liu W, Chun E, Thompson AA et al (2012) Structural basis for allosteric regulation of GPCRs by sodium ions. Science 337:232–236. https://doi.org/10.1126/science.1219218
Cherezov V, Rosenbaum DM, Hanson MA et al (2007) High-resolution crystal structure of an engineered human β2-adrenergic G protein-coupled receptor. Science 318:1258–1265. https://doi.org/10.1126/science.1150577
Berman HM, Westbrook J, Feng Z et al (2000) The protein data bank. Nucleic Acids Res 28:235–242. https://doi.org/10.1093/nar/28.1.235
Bienert S, Waterhouse A, de Beer TAP et al (2017) The SWISS-MODEL repository-new features and functionality. Nucleic Acids Res 45:D313–D319. https://doi.org/10.1093/nar/gkw1132
Isberg V, Mordalski S, Munk C et al (2016) GPCRdb: an information system for G protein-coupled receptors. Nucleic Acids Res 44:D356–D364. https://doi.org/10.1093/nar/gkv1178
Bauer MR, Ibrahim TM, Vogel SM, Boeckler FM (2013) Evaluation and optimization of virtual screening workflows with DEKOIS 2.0--a public library of challenging docking benchmark sets. J Chem Inf Model 53:1447–1462. https://doi.org/10.1021/ci400115b
Huang N, Shoichet BK, Irwin JJ (2006) Benchmarking sets for molecular docking. J Med Chem 49:6789–6801. https://doi.org/10.1021/jm0608356
Mysinger MM, Carchia M, Irwin JJ, Shoichet BK (2012) Directory of useful decoys, enhanced (DUD-E): better ligands and decoys for better benchmarking. J Med Chem 55:6582–6594. https://doi.org/10.1021/jm300687e
Bento AP, Gaulton A, Hersey A et al (2014) The ChEMBL bioactivity database: an update. Nucleic Acids Res 42:D1083–D1090. https://doi.org/10.1093/nar/gkt1031
Liu T, Lin Y, Wen X et al (2007) BindingDB: a web-accessible database of experimentally determined protein–ligand binding affinities. Nucleic Acids Res 35:D198–D201. https://doi.org/10.1093/nar/gkl999
Southan C, Sharman JL, Benson HE et al (2016) The IUPHAR/BPS guide to PHARMACOLOGY in 2016: towards curated quantitative interactions between 1300 protein targets and 6000 ligands. Nucleic Acids Res 44:D1054–D1068. https://doi.org/10.1093/nar/gkv1037
Sali A, Blundell TL (1993) Comparative protein modelling by satisfaction of spatial restraints. J Mol Biol 234:779–815. https://doi.org/10.1006/jmbi.1993.1626
Sievers F, Wilm A, Dineen D et al (2011) Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal omega. Mol Syst Biol 7:539. https://doi.org/10.1038/msb.2011.75
Hu Y, Furtmann N, Gütschow M, Bajorath J (2012) Systematic identification and classification of three-dimensional activity cliffs. J Chem Inf Model 52:1490–1498. https://doi.org/10.1021/ci300158v
Bender A, Glen RC (2005) A discussion of measures of enrichment in virtual screening: comparing the information content of descriptors with increasing levels of sophistication. J Chem Inf Model 45:1369–1375. https://doi.org/10.1021/ci0500177
Lätti S, Niinivehmas S, Pentikäinen OT (2016) Rocker: open source, easy-to-use tool for AUC and enrichment calculations and ROC visualization. J Chem 8:45. https://doi.org/10.1186/s13321-016-0158-y
Acknowledgment
We thank OpenEye Scientific Software, Inc., for a free academic license of the OpenEye Toolkit and Chemical Computing Group, Inc., for academic teaching licenses of the Molecular Operating Environment.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Science+Business Media, LLC, part of Springer Nature
About this protocol
Cite this protocol
Anighoro, A., Bajorath, J. (2018). A Hybrid Virtual Screening Protocol Based on Binding Mode Similarity. In: Mavromoustakos, T., Kellici, T. (eds) Rational Drug Design. Methods in Molecular Biology, vol 1824. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-8630-9_9
Download citation
DOI: https://doi.org/10.1007/978-1-4939-8630-9_9
Published:
Publisher Name: Humana Press, New York, NY
Print ISBN: 978-1-4939-8629-3
Online ISBN: 978-1-4939-8630-9
eBook Packages: Springer Protocols