title: Assessing an ensemble docking-based virtual screening strategy for kinase targets by considering protein flexibility.
abstract: In this study, to accommodate receptor flexibility, based on multiple receptor conformations, a novel ensemble docking protocol was developed by using the naïve Bayesian classification technique, and it was evaluated in terms of the prediction accuracy of docking-based virtual screening (VS) of three important targets in the kinase family: ALK, CDK2, and VEGFR2. First, for each target, the representative crystal structures were selected by structural clustering, and the capability of molecular docking based on each representative structure to discriminate inhibitors from non-inhibitors was examined. Then, for each target, 50 ns molecular dynamics (MD) simulations were carried out to generate an ensemble of the conformations, and multiple representative structures/snapshots were extracted from each MD trajectory by structural clustering. On average, the representative crystal structures outperform the representative structures extracted from MD simulations in terms of the capabilities to separate inhibitors from non-inhibitors. Finally, by using the naïve Bayesian classification technique, an integrated VS strategy was developed to combine the prediction results of molecular docking based on different representative conformations chosen from crystal structures and MD trajectories. It was encouraging to observe that the integrated VS strategy yields better performance than the docking-based VS based on any single rigid conformation. This novel protocol may provide an improvement over existing strategies to search for more diverse and promising active compounds for a target of interest.
authors.affiliation: Institute of Functional Nano and Soft Materials (FUNSOM), Soochow University , Suzhou, Jiangsu 215123, P. R. China.
authors.forename: Sheng
authors.initials: S
authors.lastname: Tian
authors.forename: Huiyong
authors.initials: H
authors.lastname: Sun
authors.forename: Peichen
authors.initials: P
authors.lastname: Pan
authors.forename: Dan
authors.initials: D
authors.lastname: Li
authors.forename: Xuechu
authors.initials: X
authors.lastname: Zhen
authors.forename: Youyong
authors.initials: Y
authors.lastname: Li
authors.forename: Tingjun
authors.initials: T
authors.lastname: Hou
mesh_terms: D000077548:Anaplastic Lymphoma Kinase; D001499:Bayes Theorem; D001665:Binding Sites; D016000:Cluster Analysis; D018360:Crystallography, X-Ray; D051357:Cyclin-Dependent Kinase 2 / Q000037:antagonists & inhibitors* / Q000737:chemistry; D057166:High-Throughput Screening Assays; D006801:Humans; D008024:Ligands; D062105:Molecular Docking Simulation; D056004:Molecular Dynamics Simulation; D018583:Pliability; D011485:Protein Binding; D011487:Protein Conformation; D047428:Protein Kinase Inhibitors / Q000737:chemistry*; D020794:Receptor Protein-Tyrosine Kinases / Q000037:antagonists & inhibitors* / Q000737:chemistry; D014584:User-Computer Interface; D040301:Vascular Endothelial Growth Factor Receptor-2 / Q000037:antagonists & inhibitors* / Q000737:chemistry
chemical_list: D008024:Ligands; D047428:Protein Kinase Inhibitors; C000626173:ALK protein, human; D000077548:Anaplastic Lymphoma Kinase; C000588866:KDR protein, human; D020794:Receptor Protein-Tyrosine Kinases; D040301:Vascular Endothelial Growth Factor Receptor-2; C495894:CDK2 protein, human; D051357:Cyclin-Dependent Kinase 2