title: A prediction model of substrates and non-substrates of breast cancer resistance protein (BCRP) developed by GA-CG-SVM method.
abstract: Breast cancer resistance protein (BCRP) is one of the key multi-drug resistance proteins, which significantly influences the therapeutic effects of many drugs, particularly anti-cancer drugs. Thus, distinguishing between substrates and non-substrates of BCRP is important not only for clinical use but also for drug discovery and development. In this study, a prediction model of the substrates and non-substrates of BCRP was developed using a modified support vector machine (SVM) method, namely GA-CG-SVM. The overall prediction accuracy of the established GA-CG-SVM model is 91.3% for the training set and 85.0% for an independent validation set. For comparison, two other machine learning methods, namely, C4.5 DT and k-NN, were also adopted to build prediction models. The results show that the GA-CG-SVM model is significantly superior to C4.5 DT and k-NN models in terms of the prediction accuracy. To sum up, the prediction model of BCRP substrates and non-substrates generated by the GA-CG-SVM method is sufficiently good and could be used as a screening tool for identifying the substrates and non-substrates of BCRP.
authors.affiliation: State Key Laboratory of Biotherapy, West China Hospital, West China Medical School, Sichuan University, Chengdu, Sichuan 610041, PR China.
authors.forename: Lei
authors.initials: L
authors.lastname: Zhong
authors.forename: Chang-Ying
authors.initials: CY
authors.lastname: Ma
authors.forename: Hui
authors.initials: H
authors.lastname: Zhang
authors.forename: Li-Jun
authors.initials: LJ
authors.lastname: Yang
authors.forename: Hua-Lin
authors.initials: HL
authors.lastname: Wan
authors.forename: Qing-Qing
authors.initials: QQ
authors.lastname: Xie
authors.forename: Lin-Li
authors.initials: LL
authors.lastname: Li
authors.forename: Sheng-Yong
authors.initials: SY
authors.lastname: Yang
mesh_terms: D000070997:ATP Binding Cassette Transporter, Subfamily G, Member 2; D018528:ATP-Binding Cassette Transporters / Q000037:antagonists & inhibitors* / Q000737:chemistry* / Q000378:metabolism; D000818:Animals; D000970:Antineoplastic Agents / Q000737:chemistry* / Q000627:therapeutic use; D001943:Breast Neoplasms / Q000188:drug therapy* / Q000378:metabolism; D019008:Drug Resistance, Neoplasm; D005260:Female; D006801:Humans; D008954:Models, Biological; D009363:Neoplasm Proteins / Q000037:antagonists & inhibitors* / Q000737:chemistry* / Q000378:metabolism; D011237:Predictive Value of Tests; D060388:Support Vector Machine
chemical_list: C116614:ABCG2 protein, human; D000070997:ATP Binding Cassette Transporter, Subfamily G, Member 2; D018528:ATP-Binding Cassette Transporters; D000970:Antineoplastic Agents; D009363:Neoplasm Proteins