title: Distinguishing between bioactive and modeled compound conformations through mining of emerging chemical patterns.
abstract: To systematically compare bioactive and theoretically derived compound conformations, we have analyzed 18 different sets of active small molecules with experimentally determined binding conformations and modeled conformers using a pattern recognition approach. Compound class-specific descriptor value range patterns that accurately distinguish bioactive conformations from other low-energy conformers were identified for all 18 compound classes. Discriminatory patterns were often chemically intuitive and could be well rationalized on the basis of X-ray structures of the protein-ligand complexes. Target-specific descriptor patterns can be used as filters to screen conformational ensembles for bioactive conformations.
authors.affiliation: Department of Life Science informatics, B-IT, LIMES Program Unit Chemical Biology & Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Dahlmannstrasse 2, D-53113 Bonn, Germany.
authors.forename: Jens
authors.initials: J
authors.lastname: Auer
authors.forename: Jürgen
authors.initials: J
authors.lastname: Bajorath
mesh_terms: D001665:Binding Sites; D004791:Enzyme Inhibitors / Q000737:chemistry*; D004798:Enzymes / Q000737:chemistry*; D008024:Ligands; D008954:Models, Biological; D008968:Molecular Conformation; D013329:Structure-Activity Relationship
chemical_list: D004791:Enzyme Inhibitors; D004798:Enzymes; D008024:Ligands