title: The ensemble performance index: an improved measure for assessing ensemble pose prediction performance.
abstract: We present a theoretical study on the performance of ensemble docking methodologies considering multiple protein structures. We perform a theoretical analysis of pose prediction experiments which is completely unbiased, as we make no assumptions about specific scoring functions, search paradigms, protein structures, or ligand data sets. We introduce a novel interpretable measure, the ensemble performance index (EPI), for the assessment of scoring performance in ensemble docking, which will be applied to simulated and real data sets.
authors.affiliation: Cambridge Crystallographic Data Centre, 12 Union Road, Cambridge CB2 1EZ, United Kingdom. korb@ccdc.cam.ac.uk
authors.forename: Oliver
authors.initials: O
authors.lastname: Korb
authors.forename: Patrick
authors.initials: P
authors.lastname: McCabe
authors.forename: Jason
authors.initials: J
authors.lastname: Cole
mesh_terms: D001665:Binding Sites; D019295:Computational Biology / Q000379:methods*; D051357:Cyclin-Dependent Kinase 2 / Q000037:antagonists & inhibitors / Q000737:chemistry* / Q000378:metabolism; D055808:Drug Discovery / Q000379:methods*; D006801:Humans; D008024:Ligands; D008958:Models, Molecular; D011485:Protein Binding; D047428:Protein Kinase Inhibitors / Q000737:chemistry / Q000378:metabolism* / Q000494:pharmacology; D012107:Research Design; D012984:Software; D013329:Structure-Activity Relationship; D014584:User-Computer Interface
chemical_list: D008024:Ligands; D047428:Protein Kinase Inhibitors; D051357:Cyclin-Dependent Kinase 2