Document Detail


Classification of cytochrome P450 inhibitors with respect to binding free energy and pIC50 using common molecular descriptors.
MedLine Citation:
PMID:  19777996     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
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.
Authors:
Onur Dagliyan; I Halil Kavakli; Metin Turkay
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Journal of chemical information and modeling     Volume:  49     ISSN:  1549-960X     ISO Abbreviation:  -     Publication Date:  2009 Oct 
Date Detail:
Created Date:  2009-10-26     Completed Date:  2009-12-24     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101230060     Medline TA:  J Chem Inf Model     Country:  United States    
Other Details:
Languages:  eng     Pagination:  2403-11     Citation Subset:  IM    
Affiliation:
Department of Chemical and Biological Engineering, College of Engineering and Center for Computational Biology and Bioinformatics, Ko?? University, Rumelifeneri yolu, Sariyer, Istanbul, 34450 Turkey.
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MeSH Terms
Descriptor/Qualifier:
Algorithms
Cytochrome P-450 Enzyme System / antagonists & inhibitors*,  chemistry,  metabolism*
Drug Discovery
Enzyme Inhibitors / classification,  metabolism*,  pharmacology*
Humans
Inhibitory Concentration 50
Least-Squares Analysis
Molecular Dynamics Simulation
Protein Binding
Protein Conformation
Thermodynamics*
Chemical
Reg. No./Substance:
0/Enzyme Inhibitors; 9035-51-2/Cytochrome P-450 Enzyme System

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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