title: Analysis and use of fragment-occurrence data in similarity-based virtual screening.
abstract: Current systems for similarity-based virtual screening use similarity measures in which all the fragments in a fingerprint contribute equally to the calculation of structural similarity. This paper discusses the weighting of fragments on the basis of their frequencies of occurrence in molecules. Extensive experiments with sets of active molecules from the MDL Drug Data Report and the World of Molecular Bioactivity databases, using fingerprints encoding Tripos holograms, Pipeline Pilot ECFC_4 circular substructures and Sunset Molecular keys, demonstrate clearly that frequency-based screening is generally more effective than conventional, unweighted screening. The results suggest that standardising the raw occurrence frequencies by taking the square root of the frequencies will maximise the effectiveness of virtual screening. An upper-bound analysis shows the complex interactions that can take place between representations, weighting schemes and similarity coefficients when similarity measures are computed, and provides a rationalisation of the relative performance of the various weighting schemes.
authors.affiliation: Krebs Institute for Biomolecular Research and Department of Information Studies, University of Sheffield, 211 Portobello Street, Sheffield, S1 4DP, UK.
authors.forename: Shereena M
authors.initials: SM
authors.lastname: Arif
authors.forename: John D
authors.initials: JD
authors.lastname: Holliday
authors.forename: Peter
authors.initials: P
authors.lastname: Willett
mesh_terms: D000465:Algorithms; D016208:Databases, Factual; D055808:Drug Discovery / Q000379:methods*; D006696:Holography / Q000379:methods; D015394:Molecular Structure; D004364:Pharmaceutical Preparations / Q000737:chemistry / Q000145:classification; D021281:Quantitative Structure-Activity Relationship
chemical_list: D004364:Pharmaceutical Preparations