title: Computer evaluation of drug interactions with P-glycoprotein.
abstract: The (Q)SAR models for evaluating the structure-property relationships, fit for prediction of drug interactions with P-glycoprotein as inhibitors or substrates, were constructed using PASS and GUSAR software. The models were constructed and validated on the basis of information on the structure and characteristics of 256 and 94 compounds used as P-glycoprotein substrates and inhibitors, respectively. The initial samples were divided 80:20 into training and test samples. The best prediction accuracy for the test samples was 78% for P-glycoprotein substrate prediction (PASS) and 89% for inhibitor prediction (GUSAR).
authors.affiliation: V. N. Orekhovich Institute of Biomedical Chemistry, the Russian Academy of Medical Sciences, Moscow, Russia. alexey.lagunin@ibmc.msk.ru
authors.forename: A A
authors.initials: AA
authors.lastname: Lagunin
authors.forename: T A
authors.initials: TA
authors.lastname: Gloriozova
authors.forename: A V
authors.initials: AV
authors.lastname: Dmitriev
authors.forename: N E
authors.initials: NE
authors.lastname: Volgina
authors.forename: V V
authors.initials: VV
authors.lastname: Poroikov
mesh_terms: D020168:ATP Binding Cassette Transporter, Subfamily B, Member 1 / Q000737:chemistry*; D003198:Computer Simulation; D004347:Drug Interactions; D008962:Models, Theoretical; D021281:Quantitative Structure-Activity Relationship; D012984:Software
chemical_list: D020168:ATP Binding Cassette Transporter, Subfamily B, Member 1