RT Journal Article
SR Electronic
T1 PREDICTION OF CYTOCHROME P450 3A INHIBITION BY VERAPAMIL ENANTIOMERS AND THEIR METABOLITES
JF Drug Metabolism and Disposition
JO Drug Metab Dispos
FD American Society for Pharmacology and Experimental Therapeutics
SP 259
OP 266
DO 10.1124/dmd.32.2.259
VO 32
IS 2
A1 Ying-Hong Wang
A1 David R. Jones
A1 Stephen D. Hall
YR 2004
UL http://dmd.aspetjournals.org/content/32/2/259.abstract
AB Verapamil inhibition of CYP3A activity results in many drug-drug interactions with CYP3A substrates, but the mechanism of inhibition is unclear. The present study showed that verapamil enantiomers and their major metabolites [norverapamil and N-desalkylverapamil (D617)] inhibited CYP3A in a time- and concentration-dependent manner by using pooled human liver microsomes and the cDNA-expressed CYP3A4 (+b5). The values of the inactivation kinetic parameters kinact and KI obtained with the cDNA-expressed CYP3A4 (+b5) were 0.39 min-1 and 6.46 μM for R-verapamil, 0.64 min-1 and 2.97 μM for S-verapamil, 1.12 min-1 and 5.89 μM for (±)-norverapamil, and 0.07 min-1 and 7.93 μM for D617. Based on the ratio of kinact and KI, the inactivation potency of verapamil enantiomers and their metabolites was in the following order: S-norverapamil > S-verapamil > R-norverapamil > R-verapamil > D617. Using dual beam spectrophotometry, we confirmed that metabolic intermediate complex formation with CYP3A was the mechanism of inactivation for all compounds. The in vitro unbound fraction was 0.84 for S-verapamil, 0.68 for R-verapamil, and 0.84 for (±)-norverapamil. A mechanism-based pharmacokinetic model predicted that the oral area under the curve (AUC) of a CYP3A substrate that is eliminated completely (fm = 1) by the hepatic CYP3A increased 1.6- to 2.2-fold after repeated oral administration of verapamil. For midazolam (fm = 0.9), a drug that undergoes extensive intestinal wall metabolism, the predicted increase in oral AUC was 3.2- to 4.5-fold. The predicted results correlate well with the in vivo drug interaction data, suggesting that the model is suitable for predicting drug interactions by mechanism-based inhibitors. The American Society for Pharmacology and Experimental Therapeutics