title: Multipose binding in molecular docking.
abstract: Molecular docking has been extensively applied in virtual screening of small molecule libraries for lead identification and optimization. A necessary prerequisite for successful differentiation between active and non-active ligands is the accurate prediction of their binding affinities in the complex by use of docking scoring functions. However, many studies have shown rather poor correlations between docking scores and experimental binding affinities. Our work aimed to improve this correlation by implementing a multipose binding concept in the docking scoring scheme. Multipose binding, i.e., the property of certain protein-ligand complexes to exhibit different ligand binding modes, has been shown to occur in nature for a variety of molecules. We conducted a high-throughput docking study and implemented multipose binding in the scoring procedure by considering multiple docking solutions in binding affinity prediction. In general, improvement of the agreement between docking scores and experimental data was observed, and this was most pronounced in complexes with large and flexible ligands and high binding affinities. Further developments of the selection criteria for docking solutions for each individual complex are still necessary for a general utilization of the multipose binding concept for accurate binding affinity prediction by molecular docking.
authors.affiliation: Structural Bioinformatics, BIOTEC TU Dresden, Tatzberg 47-51, Dresden 01307, Germany. katkovs@gwdg.de.
authors.forename: Kalina
authors.initials: K
authors.lastname: Atkovska
authors.affiliation: Structural Bioinformatics, BIOTEC TU Dresden, Tatzberg 47-51, Dresden 01307, Germany. sergeys@biotec.tu-dresden.de.
authors.forename: Sergey A
authors.initials: SA
authors.lastname: Samsonov
authors.affiliation: Department of Medical Systems Biology, TU Dresden, Medical Faculty, University Hospital Carl Gustav Carus, Dresden 01307, Germany. maciej.paszkowski-rogacz@tu-dresden.de.
authors.forename: Maciej
authors.initials: M
authors.lastname: Paszkowski-Rogacz
authors.affiliation: Structural Bioinformatics, BIOTEC TU Dresden, Tatzberg 47-51, Dresden 01307, Germany. mayte@biotec.tu-dresden.de.
authors.forename: M Teresa
authors.initials: MT
authors.lastname: Pisabarro
mesh_terms: D016333:HIV Protease / Q000737:chemistry / Q000378:metabolism; D017320:HIV Protease Inhibitors / Q000737:chemistry / Q000378:metabolism; D008024:Ligands; D062105:Molecular Docking Simulation; D010455:Peptides / Q000737:chemistry / Q000378:metabolism; D025341:Principal Component Analysis; D011485:Protein Binding; D011506:Proteins / Q000737:chemistry / Q000378:metabolism; D054852:Small Molecule Libraries / Q000737:chemistry / Q000378:metabolism; D012984:Software; D018909:src Homology Domains
chemical_list: D017320:HIV Protease Inhibitors; D008024:Ligands; D010455:Peptides; D011506:Proteins; D054852:Small Molecule Libraries; D016333:HIV Protease