title: Self-organizing maps for identification of new inhibitors of P-glycoprotein.
abstract: Self-organizing maps were trained to separate high- and low-active propafenone-type inhibitors of P-glycoprotein. The trained maps were subsequently used to identify highly active compounds in a virtual screen of the SPECS compound library.
authors.affiliation: Emerging Focus Pharmacoinformatics, Department of Medicinal Chemistry, University of Vienna, Althanstrasse 14, 1090 Wien, Austria.
authors.forename: Dominik
authors.initials: D
authors.lastname: Kaiser
authors.forename: Lothar
authors.initials: L
authors.lastname: Terfloth
authors.forename: Stephan
authors.initials: S
authors.lastname: Kopp
authors.forename: Jan
authors.initials: J
authors.lastname: Schulz
authors.forename: Randolf
authors.initials: R
authors.lastname: de Laet
authors.forename: Peter
authors.initials: P
authors.lastname: Chiba
authors.forename: Gerhard F
authors.initials: GF
authors.lastname: Ecker
authors.forename: Johann
authors.initials: J
authors.lastname: Gasteiger
mesh_terms: D020168:ATP Binding Cassette Transporter, Subfamily B, Member 1 / Q000037:antagonists & inhibitors* / Q000737:chemistry*; D016208:Databases, Factual; D004351:Drug Resistance; D011405:Propafenone / Q000031:analogs & derivatives / Q000737:chemistry; D021281:Quantitative Structure-Activity Relationship
chemical_list: D020168:ATP Binding Cassette Transporter, Subfamily B, Member 1; D011405:Propafenone