title: Computational predictive models for P-glycoprotein inhibition of in-house chalcone derivatives and drug-bank compounds.
abstract: The human P-glycoprotein (P-gp) efflux pump is of great interest for medicinal chemists because of its important role in multidrug resistance (MDR). Because of the high polyspecificity as well as the unavailability of high-resolution X-ray crystal structures of this transmembrane protein, ligand-based, and structure-based approaches which were machine learning, homology modeling, and molecular docking were combined for this study. In ligand-based approach, individual two-dimensional quantitative structure-activity relationship models were developed using different machine learning algorithms and subsequently combined into the Ensemble model which showed good performance on both the diverse training set and the validation sets. The applicability domain and the prediction quality of the developed models were also judged using the state-of-the-art methods and tools. In our structure-based approach, the P-gp structure and its binding region were predicted for a docking study to determine possible interactions between the ligands and the receptor. Based on these in silico tools, hit compounds for reversing MDR were discovered from the in-house and DrugBank databases through virtual screening using prediction models and molecular docking in an attempt to restore cancer cell sensitivity to cytotoxic drugs.
authors.affiliation: Department of Medicinal Chemistry, Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, 41 Dinh Tien Hoang, Dist. 1, Ho Chi Minh City, 700000, Viet Nam.
authors.forename: Trieu-Du
authors.initials: TD
authors.lastname: Ngo
authors.affiliation: Department of Medicinal Chemistry, Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, 41 Dinh Tien Hoang, Dist. 1, Ho Chi Minh City, 700000, Viet Nam.
authors.forename: Thanh-Dao
authors.initials: TD
authors.lastname: Tran
authors.affiliation: Department of Medicinal Chemistry, Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, 41 Dinh Tien Hoang, Dist. 1, Ho Chi Minh City, 700000, Viet Nam.
authors.forename: Minh-Tri
authors.initials: MT
authors.lastname: Le
authors.affiliation: Department of Medicinal Chemistry, Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, 41 Dinh Tien Hoang, Dist. 1, Ho Chi Minh City, 700000, Viet Nam. thaikhacminh@gmail.com.
authors.forename: Khac-Minh
authors.identifier: http://orcid.org/0000-0002-5279-9614
authors.initials: KM
authors.lastname: Thai
mesh_terms: D018435:ATP Binding Cassette Transporter, Subfamily B / Q000037:antagonists & inhibitors / Q000737:chemistry*; D000465:Algorithms; D002599:Chalcone / Q000031:analogs & derivatives* / Q000737:chemistry* / Q000494:pharmacology; D003198:Computer Simulation; D016208:Databases, Factual; D055808:Drug Discovery; D008024:Ligands; D000069550:Machine Learning; D008958:Models, Molecular; D062105:Molecular Docking Simulation; D056004:Molecular Dynamics Simulation; D021281:Quantitative Structure-Activity Relationship; D015203:Reproducibility of Results; D054852:Small Molecule Libraries
chemical_list: D018435:ATP Binding Cassette Transporter, Subfamily B; D008024:Ligands; D054852:Small Molecule Libraries; D002599:Chalcone
keywords: Chalcone; Docking; Drug bank; Machine learning; P-glycoprotein