Machine learning-, rule- and pharmacophore-based classification on the inhibition of P-glycoprotein and NorA.
The efflux pumps P-glycoprotein (P-gp) in humans and NorA in Staphylococcus aureus are of great interest for medicinal chemists because of their important roles in multidrug resistance (MDR). The high polyspecificity as well as the unavailability of high-resolution X-ray crystal structures of these transmembrane proteins lead us to combining ligand-based approaches, which in the case of this study were machine learning, perceptual mapping and pharmacophore modelling. For P-gp inhibitory activity, individual models were developed using different machine learning algorithms and subsequently combined into an ensemble model which showed a good discrimination between inhibitors and noninhibitors (acctrain-diverse = 84%; accinternal-test = 92% and accexternal-test = 100%). For ligand promiscuity between P-gp and NorA, perceptual maps and pharmacophore models were generated for the detection of rules and features. Based on these in silico tools, hit compounds for reversing MDR were discovered from the in-house and DrugBank databases through virtual screening in an attempt to restore drug sensitivity in cancer cells and bacteria.
a Department of Medicinal Chemistry, Faculty of Pharmacy , University of Medicine and Pharmacy at Ho Chi Minh City , Viet Nam.
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Ngo
a Department of Medicinal Chemistry, Faculty of Pharmacy , University of Medicine and Pharmacy at Ho Chi Minh City , Viet Nam.
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Tran
a Department of Medicinal Chemistry, Faculty of Pharmacy , University of Medicine and Pharmacy at Ho Chi Minh City , Viet Nam.
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Le
a Department of Medicinal Chemistry, Faculty of Pharmacy , University of Medicine and Pharmacy at Ho Chi Minh City , Viet Nam.
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Thai
D020168:ATP Binding Cassette Transporter, Subfamily B, Member 1 / Q000037:antagonists & inhibitors* / Q000737:chemistry; D000465:Algorithms; D001426:Bacterial Proteins / Q000037:antagonists & inhibitors* / Q000737:chemistry; D062126:Databases, Chemical; D055808:Drug Discovery; D006801:Humans; D008024:Ligands; D000069550:Machine Learning; D027425:ATP-Binding Cassette, Sub-Family C Proteins / Q000037:antagonists & inhibitors* / Q000737:chemistry; D021281:Quantitative Structure-Activity Relationship; D013211:Staphylococcus aureus
D020168:ATP Binding Cassette Transporter, Subfamily B, Member 1; D001426:Bacterial Proteins; D008024:Ligands; D027425:ATP-Binding Cassette, Sub-Family C Proteins; C075040:NorA protein, Staphylococcus
Machine learning; NorA; P-glycoprotein; classification; pharmacophore; rule