Classification of cytochrome P450 inhibitors with respect to binding free energy and pIC50 using common molecular descriptors.
Virtual screening of chemical libraries following experimental assays of drug candidates is a common procedure in structure based drug discovery. However, the relationship between binding free energies and biological activities (pIC50) of drug candidates is still an unsolved issue that limits the efficiency and speed of drug development processes. In this study, the relationship between them is investigated based on a common molecular descriptor set for human cytochrome P450 enzymes (CYPs). CYPs play an important role in drug-drug interactions, drug metabolism, and toxicity. Therefore, in silico prediction of CYP inhibition by drug candidates is one of the major considerations in drug discovery. The combination of partial least-squares regression (PLSR) and a variety of classification algorithms were employed by considering this relationship as a classification problem. Our results indicate that PLSR with classification is a powerful tool to predict more than one output such as binding free energy and pIC50 simultaneously. PLSR with mixed-integer linear programming based hyperboxes predicts the binding free energy and pIC50 with a mean accuracy of 87.18% (min: 81.67% max: 97.05%) and 88.09% (min: 79.83% max: 92.90%), respectively, for the cytochrome p450 superfamily using the common 6 molecular descriptors with a 10-fold cross-validation.
Dagliyan
Onur
O
Department of Chemical and Biological Engineering, College of Engineering and Center for Computational Biology and Bioinformatics, Koç University, Rumelifeneri yolu, Sariyer, Istanbul, 34450 Turkey.
Kavakli
I Halil
IH
Turkay
Metin
M
D000465:Algorithms; D065607:Cytochrome P-450 Enzyme Inhibitors; D003577:Cytochrome P-450 Enzyme System / Q000737:chemistry / Q000378:metabolism*; D055808:Drug Discovery; D004791:Enzyme Inhibitors / Q000145:classification / Q000378:metabolism* / Q000494:pharmacology*; D006801:Humans; D020128:Inhibitory Concentration 50; D016018:Least-Squares Analysis; D056004:Molecular Dynamics Simulation; D011485:Protein Binding; D011487:Protein Conformation; D013816:Thermodynamics
D065607:Cytochrome P-450 Enzyme Inhibitors; D004791:Enzyme Inhibitors; D003577:Cytochrome P-450 Enzyme System