title: Exploiting structure-activity relationships in docking.
abstract: From the perspective of 2D chemical descriptors, error in docking activity predictions is separated into noise and systematic components. This error framework explains how fitting docking scores to a 2D-QSAR equation often improves accuracy as well as its logical limits. Intriguingly, in examined cases where multiple docking models (e.g., multiple crystal structures or multiple scoring functions) are available for an enzyme, the noise component of error dominates the difference between the more accurate and less accurate docking models. When this is true, the QSAR equation fit statistics can rank each docking-score set's accuracy in the absence of experimental activity data.
authors.affiliation: Department of Computer Aided Drug Discovery, Global Discovery Chemistry, Novartis Institutes for Biomedical Research, 4560 Horton Street, Emeryville, California 94608, USA. davidxyz1972@yahoo.com
authors.forename: David C
authors.initials: DC
authors.lastname: Sullivan
authors.forename: Eric J
authors.initials: EJ
authors.lastname: Martin
mesh_terms: D015195:Drug Design; D016333:HIV Protease / Q000378:metabolism; D015394:Molecular Structure; D010770:Phosphotransferases / Q000378:metabolism; D021281:Quantitative Structure-Activity Relationship
chemical_list: D010770:Phosphotransferases; D016333:HIV Protease