Literature DB >> 18854379

Prediction of the effect of erythromycin, diltiazem, and their metabolites, alone and in combination, on CYP3A4 inhibition.

Xin Zhang1, David R Jones, Stephen D Hall.   

Abstract

Predictive models of complex drug-drug interactions between multiple inhibitors and their metabolites have not been evaluated. The purpose of this study was to evaluate an interaction model for cytochrome P450 3A4 (CYP3A4) that incorporated the simultaneous reversible and irreversible inhibition by multiple inhibitors. Erythromycin (ERY) and diltiazem (DTZ), and their major metabolites, N-desmethylerythromycin (nd-ERY) and N-desmethyldiltiazem (nd-DTZ), were chosen to evaluate the model. k(inact) (rate constant for maximal inactivation), K(I) (inhibitor concentration at 50% maximal inactivation), and K(i) (reversible inhibition constant) were estimated for ERY, DTZ, nd-ERY, and nd-DTZ, respectively, using cDNA-expressed CYP3A4 and human liver microsomes under optimal experimental conditions. To evaluate the interaction model, combinations of inhibitors and metabolites were incubated at concentrations equal to K(I), (1/2)K(I), and 2K(I) of each inhibitor for specified durations in both enzyme systems. The models were further evaluated by the incubation of combinations of inhibitors with the substrate testosterone for 10 min. CYP3A4 inhibition in the presence of drug mixtures was predicted from the inhibition parameters determined for each drug or metabolite alone. The CYP3A4 activity in the presence of multiple inhibitors was well predicted by the model incorporating additive irreversible inhibition as modified by mutual competitive inhibition (percent mean error and percent mean absolute error ranged from -0.06 to 0.04 and from 0.03 to 0.09, respectively). In conclusion, the additive model predicted the combined effect of multiple inhibitors on CYP3A inhibition in vitro. However, simultaneous reversible and irreversible inhibition effects should be taken into account in a reaction mixture of substrate and multiple inhibitors of CYP3A4.

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Year:  2008        PMID: 18854379     DOI: 10.1124/dmd.108.022178

Source DB:  PubMed          Journal:  Drug Metab Dispos        ISSN: 0090-9556            Impact factor:   3.922


  16 in total

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Authors:  Zhe-Yi Hu; Robert B Parker; S Casey Laizure
Journal:  Drug Metab Dispos       Date:  2012-05-04       Impact factor: 3.922

3.  Inhibition of CYP2C19 and CYP3A4 by omeprazole metabolites and their contribution to drug-drug interactions.

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Journal:  Drug Metab Dispos       Date:  2013-04-25       Impact factor: 3.922

4.  A numerical method for analysis of in vitro time-dependent inhibition data. Part 2. Application to experimental data.

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Journal:  Drug Metab Dispos       Date:  2014-06-17       Impact factor: 3.922

5.  Reversible Mechanisms of Enzyme Inhibition and Resulting Clinical Significance.

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Journal:  Methods Mol Biol       Date:  2021

6.  Irreversible Enzyme Inhibition Kinetics and Drug-Drug Interactions.

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Journal:  Methods Mol Biol       Date:  2021

7.  Multienzyme Kinetics and Sequential Metabolism.

Authors:  Larry C Wienkers; Brooke M Rock
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8.  Are circulating metabolites important in drug-drug interactions?: Quantitative analysis of risk prediction and inhibitory potency.

Authors:  C K Yeung; Y Fujioka; H Hachad; R H Levy; N Isoherranen
Journal:  Clin Pharmacol Ther       Date:  2010-12-01       Impact factor: 6.875

9.  Sequential metabolism of secondary alkyl amines to metabolic-intermediate complexes: opposing roles for the secondary hydroxylamine and primary amine metabolites of desipramine, (s)-fluoxetine, and N-desmethyldiltiazem.

Authors:  Kelsey L Hanson; Brooke M VandenBrink; Kantipudi N Babu; Kyle E Allen; Wendel L Nelson; Kent L Kunze
Journal:  Drug Metab Dispos       Date:  2010-03-03       Impact factor: 3.922

10.  In vitro-in vivo extrapolation of zolpidem as a perpetrator of metabolic interactions involving CYP3A.

Authors:  Thomas M Polasek; Janani S Sadagopal; David J Elliot; John O Miners
Journal:  Eur J Clin Pharmacol       Date:  2009-12-11       Impact factor: 2.953

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