Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
2484227 | Journal of Pharmaceutical Sciences | 2016 | 9 Pages |
Abstract
The aim of this study was to develop an in silico prediction system to assess which of 7 categories of drug transporters (organic anion transporting polypeptide [OATP] 1B1/1B3, multidrug resistance-associated protein [MRP] 2/3/4, organic anion transporter [OAT] 1, OAT3, organic cation transporter [OCT] 1/2/multidrug and toxin extrusion [MATE] 1/2-K, multidrug resistance protein 1 [MDR1], and breast cancer resistance protein [BCRP]) can recognize compounds as substrates using its chemical structure alone. We compiled an internal data set consisting of 260 compounds that are substrates for at least 1 of the 7 categories of drug transporters. Four physicochemical parameters (charge, molecular weight, lipophilicity, and plasma unbound fraction) of each compound were used as the basic descriptors. Furthermore, a greedy algorithm was used to select 3 additional physicochemical descriptors from 731 available descriptors. In addition, transporter nonsubstrates tend not to be in the public domain; we, thus, tried to compile an expert-curated data set of putative nonsubstrates for each transporter using personal opinions of 11 researchers in the field of drug transporters. The best prediction was finally achieved by a support vector machine based on 4 basic and 3 additional descriptors. The model correctly judged that 364 of 412 compounds (internal data set) and 111 of 136 compounds (external data set) were substrates, indicating that this model performs well enough to predict the specificity of transporter substrates.
Keywords
ROCFUPITCDDIMRPBcrpOATPAUCOctQSARdrug–drug interactionOatTransportersorganic cation transporterorganic anion transporterslog DIn silico modelingMateHigh-throughput technologiesSVMSupport vector machinecomputational ADMEarea under the curvemultidrug resistance-associated proteinbreast cancer resistance proteinOrganic anion transporting polypeptidemultidrug and toxin extrusionreceiver operating characteristic
Related Topics
Health Sciences
Pharmacology, Toxicology and Pharmaceutical Science
Drug Discovery
Authors
Atsushi Ose, Kota Toshimoto, Kazushi Ikeda, Kazuya Maeda, Shuya Yoshida, Fumiyoshi Yamashita, Mitsuru Hashida, Takashi Ishida, Yutaka Akiyama, Yuichi Sugiyama,