title: Analysis and optimization of structure-based virtual screening protocols. 2. Examination of docked ligand orientation sampling methodology: mapping a pharmacophore for success.
abstract: An important element of any structure-based virtual screening (SVS) technique is the method used to orient the ligands in the target active site. This has been a somewhat overlooked issue in recent SVS validation studies, with the assumption being made that the performance of an algorithm for a given set of orientation sampling settings will be representative for the general behavior of said technique. Here, we analyze five different SVS targets using a variety of sampling paradigms within the DOCK, GOLD and PROMETHEUS programs over a data set of approximately 10,000 noise compounds, combined with data sets containing multiple active compounds. These sets have been broken down by chemotype, with chemotype hit rate used to provide a measure of enrichment with a potentially improved relevance to real world SVS experiments. The variability in enrichment results produced by different sampling paradigms is illustrated, as is the utility of using pharmacophores to constrain sampling to regions that reflect known structural biology. The difference in results when comparing chemotype with compound hit rates is also highlighted.
authors.affiliation: Bristol-Myers Squibb, P.O. Box 5100, Wallingford, CT 06492, USA. andrew.good@bms.com
authors.forename: Andrew C
authors.initials: AC
authors.lastname: Good
authors.forename: Daniel L
authors.initials: DL
authors.lastname: Cheney
authors.forename: Doree F
authors.initials: DF
authors.lastname: Sitkoff
authors.forename: John S
authors.initials: JS
authors.lastname: Tokarski
authors.forename: Terry R
authors.initials: TR
authors.lastname: Stouch
authors.forename: Donna A
authors.initials: DA
authors.lastname: Bassolino
authors.forename: Stanley R
authors.initials: SR
authors.lastname: Krystek
authors.forename: Yi
authors.initials: Y
authors.lastname: Li
authors.forename: Jonathan S
authors.initials: JS
authors.lastname: Mason
authors.forename: Timothy D J
authors.initials: TD
authors.lastname: Perkins
mesh_terms: D001665:Binding Sites; D019295:Computational Biology; D003196:Computer Graphics; D003198:Computer Simulation; D030562:Databases, Protein; D015195:Drug Design; D004791:Enzyme Inhibitors / Q000737:chemistry / Q000378:metabolism; D008024:Ligands; D008958:Models, Molecular; D017853:Phosphotransferases (Alcohol Group Acceptor) / Q000378:metabolism / Q000502:physiology; D020794:Receptor Protein-Tyrosine Kinases / Q000378:metabolism / Q000502:physiology; D029701:Saccharomyces cerevisiae Proteins / Q000378:metabolism / Q000502:physiology; D012697:Serine Endopeptidases / Q000378:metabolism / Q000502:physiology; D012984:Software; D013329:Structure-Activity Relationship
chemical_list: D004791:Enzyme Inhibitors; D008024:Ligands; D029701:Saccharomyces cerevisiae Proteins; C095504:FAB1 protein, S cerevisiae; D017853:Phosphotransferases (Alcohol Group Acceptor); D020794:Receptor Protein-Tyrosine Kinases; D012697:Serine Endopeptidases