title: Three- and four-class classification models for P-glycoprotein inhibitors using counter-propagation neural networks.
abstract: P-glycoprotein (P-gp) is an ATP binding cassette (ABC) transporter that helps to protect several certain human organs from xenobiotic exposure. This efflux pump is also responsible for multi-drug resistance (MDR), an issue of the chemotherapy approach in the fight against cancer. Therefore, the discovery of P-gp inhibitors is considered one of the most popular strategies to reverse MDR in tumour cells and to improve therapeutic efficacy of commonly used cytotoxic drugs. Until now, several generations of P-gp inhibitors have been developed but they have largely failed in preclinical and clinical studies due to lack of selectivity, poor solubility and severe pharmacokinetic interactions. In this study, three models (SION, SIO, SIN) to classify specific 'true' P-gp inhibitors as well as three other models (CPBN, CPB1, CPN) to distinguish between P-gp inhibitors, CYP 3A inhibitors and co-inhibitors of these proteins with rather high accuracy values for the test set and the external set were generated based on counter-propagation neural networks (CPG-NN). Such three and four-class classification models helped provide more information about the bioactivities of compounds not only on one target (P-gp), but also on a combination of multiple targets (P-gp, CYP 3A).
authors.affiliation: a Department of Medicinal Chemistry, School of Pharmacy , University of Medicine and Pharmacy at Ho Chi Minh City , Ho Chi Minh City , Viet Nam.
authors.forename: K-M
authors.initials: KM
authors.lastname: Thai
authors.forename: N-T
authors.initials: NT
authors.lastname: Huynh
authors.forename: T-D
authors.initials: TD
authors.lastname: Ngo
authors.forename: T-T
authors.initials: TT
authors.lastname: Mai
authors.forename: T-H
authors.initials: TH
authors.lastname: Nguyen
authors.forename: T-D
authors.initials: TD
authors.lastname: Tran
mesh_terms: D018435:ATP Binding Cassette Transporter, Subfamily B / Q000037:antagonists & inhibitors* / Q000737:chemistry; D003198:Computer Simulation; D065692:Cytochrome P-450 CYP3A Inhibitors / Q000737:chemistry; D062126:Databases, Chemical; D018432:Drug Resistance, Multiple / Q000187:drug effects; D016571:Neural Networks, Computer; D013329:Structure-Activity Relationship
chemical_list: D018435:ATP Binding Cassette Transporter, Subfamily B; D065692:Cytochrome P-450 CYP3A Inhibitors
keywords: CPGNN; CYP 3A; P-glycoprotein; classification; counter-propagation neural networks; four-class classification