title: Small molecule shape-fingerprints.
abstract: The optimal overlap between two molecular structures is a useful measure of shape similarity. However, it usually requires significant computation. This work describes the design of shape-fingerprints: binary bit strings that encode molecular shape. Standard measures of similarity between two shape-fingerprints are shown to be an excellent surrogate for similarity based on volume overlap but several orders of magnitude faster to compute. Consequently, shape-fingerprints can be used for clustering of large data sets, evaluating the diversity of compound libraries, as descriptors in SAR and as a prescreen for exact shape comparison against large virtual databases. Our results show that a small set of shapes can be used to build these fingerprints and that this set can be applied universally.
authors.affiliation: Department of Chemistry, The University of Sheffield, Sheffield S3 7HF, England. j.a.haigh@sheffield.ac.uk
authors.forename: James A
authors.initials: JA
authors.lastname: Haigh
authors.forename: Barry T
authors.initials: BT
authors.lastname: Pickup
authors.forename: J Andrew
authors.initials: JA
authors.lastname: Grant
authors.forename: Anthony
authors.initials: A
authors.lastname: Nicholls