title: Guided Iterative Substructure Search (GI-SSS) - A New Trick for an Old Dog.
abstract: Substructure search (SSS) is a fundamental technique supported by various chemical information systems. Many users apply it in an iterative manner: they modify their queries to shape the composition of the retrieved hit sets according to their needs. We propose and evaluate two heuristic extensions of SSS aimed at simplifying these iterative query modifications by collecting additional information during query processing and visualizing this information in an intuitive way. This gives the user a convenient feedback on how certain changes to the query would affect the retrieved hit set and reduces the number of trial-and-error cycles needed to generate an optimal search result. The proposed heuristics are simple, yet surprisingly effective and can be easily added to existing SSS implementations.
authors: Boehringer Ingelheim Pharma GmbH & Co. KG, Discovery Research, Lead Identification and Optimization Support, Computational Chemistry, Birkendorfer Straße 65, 88397, Biberach an der Riss, Germany. nils.weskamp@boehringer-ingelheim.com.
authors: Nils
authors: N
authors: Weskamp
mesh_terms: D000465:Algorithms; D057225:Data Mining; D062126:Databases, Chemical; D008968:Molecular Conformation; D057386:Search Engine; D012984:Software
keywords: Chemoinformatics; Computational Chemistry; Drug Discovery; Fused-ring Systems; Heterocycles; Medicinal Chemistry