title: Enhancing the effectiveness of similarity-based virtual screening using nearest-neighbor information.
abstract: We test the hypothesis that fusing the outputs of similarity searches based on a single bioactive reference structure and on its nearest neighbors (of unknown activity) is more effective (in terms of numbers of high-ranked active structures) than a similarity search involving just the reference structure. This turbo similarity searching approach provides a simple way to enhance the effectiveness of simulated virtual screening searches of the MDL Drug Data Report database.
authors.affiliation: Krebs Institute for Biomolecular Research and Department of Information Studies, University of Sheffield, Western Bank, Sheffield S10 2TN, U.K.
authors.forename: Jérôme
authors.initials: J
authors.lastname: Hert
authors.forename: Peter
authors.initials: P
authors.lastname: Willett
authors.forename: David J
authors.initials: DJ
authors.lastname: Wilton
authors.forename: Pierre
authors.initials: P
authors.lastname: Acklin
authors.forename: Kamal
authors.initials: K
authors.lastname: Azzaoui
authors.forename: Edgar
authors.initials: E
authors.lastname: Jacoby
authors.forename: Ansgar
authors.initials: A
authors.lastname: Schuffenhauer
mesh_terms: D003205:Computing Methodologies; D016208:Databases, Factual; D004364:Pharmaceutical Preparations / Q000737:chemistry*; D021281:Quantitative Structure-Activity Relationship
chemical_list: D004364:Pharmaceutical Preparations