title: New molecular shape descriptors: application in database screening.
abstract: Geometric descriptors are becoming popular tools for encoding molecular shape, for use in database screening and clustering calculations. They provide condensed representations of complex objects and, as a consequence, can usually be compared quite rapidly. Here we present a number of new descriptors and methods for the quantification of molecular shape similarity. The techniques are tested using two different biological systems, with particular emphasis on their potential utility as methods for prescreening shape-based database searches. Results are compared with data sets produced using the DOCK program. We find that such similarity evaluations are useful for finding molecules with complementary shape, and that they contain an enriched number of potential DOCK hits when compared to the original databases. Significant limitations in the utility of such DOCK prescreens are discussed, and potential solutions are considered.
authors.affiliation: School of Pharmacy, Department of Pharmaceutical Chemistry, University of California at San Francisco 94143-0446, USA.
authors.forename: A C
authors.initials: AC
authors.lastname: Good
authors.forename: T J
authors.initials: TJ
authors.lastname: Ewing
authors.forename: D A
authors.initials: DA
authors.lastname: Gschwend
authors.forename: I D
authors.initials: ID
authors.lastname: Kuntz
mesh_terms: D001665:Binding Sites; D004247:DNA / Q000737:chemistry*; D016208:Databases, Factual; D015195:Drug Design; D008024:Ligands; D008727:Methotrexate / Q000737:chemistry; D008968:Molecular Conformation; D015394:Molecular Structure; D009429:Netropsin / Q000737:chemistry; D009690:Nucleic Acid Conformation; D012984:Software; D013329:Structure-Activity Relationship
chemical_list: D008024:Ligands; D009429:Netropsin; D004247:DNA; D008727:Methotrexate