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Inhibition of Recombinant Cytochrome P450 Isoforms 2D6 and 2C9 by Diverse Drug-like Molecules

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Department of Molecular Systems and Department of Applied Computer Science and Mathematics, Merck Research Laboratories, Rahway, New Jersey, and Department of Drug Metabolism, Merck Research Laboratories, West Point, Pennsylvania
Cite this: J. Med. Chem. 2007, 50, 14, 3205–3213
Publication Date (Web):June 9, 2007
Copyright © 2007 American Chemical Society

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    The affinities of a diverse set of 500 drug-like molecules to cytochrome P450 isoforms 2C9 and 2D6 were measured using recombinant expressed enzyme. The dose−response curve of each compound was fitted with a series of equations representing typical or various types of atypical kinetics. Atypical kinetics was identified where the Akaike Information Criterion, plus other criteria, suggested the kinetics was more complex than expected for a Michaelis−Menten model. Approximately 20% of the compounds were excluded due to poor solubility, and approximately 15% were excluded due to fluorescence interference. Of the remaining compounds, roughly half were observed to bind with an affinity of 200 μM or lower for each of the two isoforms. Atypical kinetics was observed in 18% of the compounds that bind to cytochrome 2C9, but less than 2% for 2D6. The resulting collection of competitive inhibitors and inactive compounds were analyzed for trends in binding affinity. For CYP2D6, a clear relationship between polar surface area and charge was observed, with the most potent inhibitors having a formal positive charge and a low percent polar surface area. For CYP2C9, no clear trend between activity and physicochemical properties could be seen for the group as a whole; however, certain classes of compounds have altered frequencies of activity and atypical kinetics.

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     To whom correspondence should be addressed. Tel.:  (732) 594-6812. Fax:  (732) 594-4224. E-mail:  [email protected].

     Department of Molecular Systems.

     Visiting scientist from Washington State University, Pullman, Washington.


     Department of Drug Metabolism.

     Department of Applied Computer Science and Mathematics.

    Abbreviations:  AIC, Akaike Information Criterion; AICc, corrected Akaike Information Criterion; DDI, drug−drug interactions; ESI, enzyme−substrate−inhibitor; QSAR, quantitative structure−activity relationship; RSS, residual sum of squares.

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