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First published on January 13, 2006; DOI: 10.1124/dmd.105.007625


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Received for publication September 29, 2005.
Revised January 6, 2006.
Accepted for publication January 9, 2006.

In silico and in vitro screening for inhibition of cytochrome P450 CYP3A4 by co-medications commonly used by patients with cancer

Jean-Didier Marechal 1, Jinglei Yu 2, Simon Brown 2, Iouri Kapelioukh 2, Elaine M Rankin 2, C Roland Wolf 2, Gordon CK Roberts 3, Mark JI Paine 2, Michael J Sutcliffe 1*

1 University of Manchester 2 University of Dundee 3 University of Leicester

* Address correspondence to: E-mail: michael.sutcliffe{at}manchester.ac.uk

Abstract

Cytochrome P450 3A4 (CYP3A4) is the major enzyme responsible for phase I drug metabolism of many anti-cancer agents. It is also a major route for metabolism of many drugs used by patients to treat the symptoms caused by cancer and its treatment as well as their other illnesses, for example cardiovascular disease. To assess the ability to inhibit CYP3A4 of drugs most commonly used by our patients during cancer therapy, we have made in silico predictions based on the crystal structures of CYP3A4. From this set of 33 common co-medicated drugs, ten were predicted to be inhibitors of CYP3A4, with the anti-diarrhoeal drug loperamide predicted to be the most potent. There was significant correlation (r2 = 0.75 - 0.66) between predicted affinity and measured IC50 values, and loperamide was confirmed as a potent inhibitor (IC50 of 0.050 ± 0.006 µM). Active site docking studies predicted an orientation of loperamide consistent with formation of the major (N-demethylated) metabolite, where it interacts with the phenylalanine cluster, Arg-212 and Glu-374; experimental evidence for the latter interaction comes from the ~12-fold increase in KM for loperamide observed for the Glu-374-Gln mutant. The commonly prescribed drugs loperamide, amitryptyline, diltiazem, domperidone, lanzoprazole, omeprazole and simvastatin were identified by our in silico and in vitro screens as relatively potent inhibitors of CYP3A4 which have the potential to interact with cytotoxic agents to cause adverse effects, highlighting the likelihood of drug-drug interactions affecting chemotherapy treatment.


Key words: computer modeling and simulation, CYP3A, drug development, drug-drug interactions, human CYP enzymes


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