Literature DB >> 31427434

Kinetic Modeling of Steady-State Situations in Cytochrome P450 Enzyme Reactions.

F Peter Guengerich1.   

Abstract

In the course of investigations of the kinetics of individual reactions of cytochrome P450 (P450) enzymes, a number of points about the complexity of P450 enzyme kinetics have become apparent. Several of these are of particular relevance to work with P450 enzymes in the course of drug development and lead optimization, particularly with regard to estimating in vitro kinetic parameters and dealing with enzyme inhibitors. Modern simulation modeling has been applied to situations involving issues of preincubation time with moderate strength and strong inhibitors, inhibition by tightly bound ligands that have been identified in P450 enzymes, extensive substrate depletion, P450 reactions with a rate-limiting step after product formation, and the consumption of an inhibitor during a reaction by either a P450 enzyme being monitored or another one in a mixture. The results all follow from first principles, and simulations reveal the extent of their significance in various settings. The order of addition of substrate and inhibitors can change the apparent outcome (inhibition constant, K i), and the effect of the order is more pronounced with a stronger inhibitor. Substrate depletion alters parameters (Michaelis constant, K m) and can generate apparently sigmoidal plots. A rate-limiting step after product formation lowers the apparent K m and distorts K i Consumption of an inhibitor during a reaction affects K i and differs depending on which enzyme is involved. The results are relevant with P450 enzymes and other enzymes as well. SIGNIFICANCE STATEMENT: Kinetic simulations have been used to address several potential problems in enzyme kinetic analysis. Although the simulations done here are general for enzyme reactions, several problems addressed here are particularly relevant to cytochrome P450 reactions encountered in drug development work.
Copyright © 2019 by The American Society for Pharmacology and Experimental Therapeutics.

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Year:  2019        PMID: 31427434      PMCID: PMC6815944          DOI: 10.1124/dmd.119.088732

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


  42 in total

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