Modelling atypical CYP3A4 kinetics: principles and pragmatism

https://doi.org/10.1016/j.abb.2004.09.010Get rights and content

Abstract

The Michaelis–Menten model, and the existence of a single active site for the interaction of substrate with drug metabolizing enzyme, adequately describes a substantial number of in vitro metabolite kinetic data sets for both clearance and inhibition determination. However, in an increasing number of cases (involving most notably, but not exclusively, CYP3A4), atypical kinetic features are observed, e.g., auto- and heteroactivation; partial, cooperative, and substrate inhibition; concentration-dependent effector responses (activation/inhibition); limited substrate substitution and inhibitory reciprocity necessitating sub-group classification. The phenomena listed above cannot be readily interpreted using single active site models and the literature indicates that three types of approaches have been adopted. First the ‘naı¨ve’ approach of using the Michaelis–Menten model regardless of the kinetic behaviour, second the ‘empirical’ approach (e.g., employing the Hill or uncompetitive inhibition equations to model homotropic phenomena of sigmoidicity and substrate inhibition, respectively) and finally, the ‘mechanistic’ approach. The later includes multisite kinetic models derived using the same rapid equilibrium/steady-state assumptions as the single-site model. These models indicate that 2 or 3 binding sites exist for a given CYP3A4 substrate and/or effector. Multisite kinetic models share common features, depending on the substrate kinetics and the nature of the effector response observed in vitro, which allow a generic model to be proposed. Thus although more complex than the other two approaches, they show more utility and can be comprehensively applied in relatively simple versions that can be readily generated from generic model. Multisite kinetic features, observed in isolated hepatocytes as well as in microsomes from hepatic tissue and heterologous expression systems, may be evident in substrate depletion–time profiles as well as in metabolite formation rates. Failure to adequately account for multisite kinetic phenomena will compromise any attempts to predict human drug clearance and drug–drug interaction potential from in vitro data.

Section snippets

Background and scope

For many years the Michaelis–Menten model, and the existence of a single active site for the interaction of substrate with drug metabolising enzyme, has been used to describe in vitro kinetic data for both clearance and inhibition determination. However, it has become increasingly common that atypical (non-Michaelis–Menten) kinetic features are observed. The phenomena of auto- and heteroactivation; partial, cooperative, and substrate inhibition; concentration-dependent effector responses

Approaches in modelling atypical kinetics

The literature indicates that atypical kinetic in vitro data are generally analysed by three approaches—‘naı¨ve’, empirical, and mechanistic methods. Investigators using the first approach apply the Michaelis–Menten model regardless of the kinetic behaviour observed, ignoring any evidence of sigmoidicity or convexity in the rate-substrate concentration profile. Use of empirical models (e.g., Hill or uncompetitive inhibition equations for the analysis of the two homotropic types described above)

Impact of ‘atypical’ kinetics on the prediction of clearance

A recent FDA report [23] indicates that testosterone is the most commonly used in vitro CYP3A4 probe. It was employed in approximately 50% of reported studies, contrasting with the use of midazolam (15–20%), nifedipine, felodipine, and erythromycin (the later three less than 10% each) for in vitro estimation of CYP3A4 activity. However, the differential effects observed for various CYP3A4 substrates [8] have resulted in the recommendation of employing two or more CYP3A4 substrates [24], [25].

Modelling testosterone interactions: three-site model

Two distinct types of heterotropic interactions have been reported for testosterone where positive cooperativity either remains in the presence of the modifier or is eliminated. The loss of sigmoidicity at high concentrations of modifier (linear Eadie–Hofstee plots as normally seen for hyperbolic kinetics) occurs in the presence of midazolam, nifedipine, and felodipine. An analogous situation is observed for substrates showing substrate inhibition kinetic properties. When γ is comparable to β,

Extending the [I]/Ki approach

The most promising approach to quantitative prediction of drug–drug interactions from in vitro data is based on the ratio between the concentration of the inhibitor in vivo at the enzyme active site (I) and inhibition constant (Ki), assuming reversible single-site inhibition. The major assumptions for this in vitro–in vivo extrapolation are reversible Michaelis–Menten type of inhibition (competitive or non-competitive), applicability of the well-stirred liver model and linear pharmacokinetics

Importance of atypical kinetics in vitro and in vivo

The occurrence of atypical kinetics for CYP3A4 substrates, notably auto- and heteroactivation; partial, cooperative, and substrate inhibition; concentration-dependent effector responses (activation/inhibition); limited substrate substitution and inhibitory reciprocity, is well documented. It is also becoming realised that such atypical behaviour is not unique to CYP3A4 substrates. Cooperativity can occur in multiple steps of CYP-cycle dependent on the enzyme, substrate and the modifier

References (47)

  • M. Shou et al.

    J. Biol. Chem.

    (2001)
  • Y.A. He et al.

    Arch. Biochem. Biophys.

    (2003)
  • J.K. Yano et al.

    J. Biol. Chem.

    (2004)
  • C.A. Lee et al.

    Arch. Biochem. Biophys.

    (1995)
  • W.M. Atkins

    Drug Discov. Today

    (2004)
  • M. Shou et al.

    Biochem. J.

    (1999)
  • Y.-F. Ueng et al.

    Biochemistry

    (1997)
  • Y. Lin et al.

    Drug. Metab. Dispos.

    (2001)
  • A. Galetin et al.

    Drug Metab. Dispos.

    (2002)
  • K.R. Korzekwa et al.

    Biochemistry

    (1998)
  • J.S. Ngui et al.

    Drug Metab. Dispos.

    (2000)
  • K.E. Kenworthy et al.

    Drug Metab. Dispos.

    (2001)
  • K.E. Kenworthy et al.

    Br. J. Clin. Pharmacol.

    (1999)
  • D.M. Stresser et al.

    Drug Metab. Dispos.

    (2000)
  • A. Galetin et al.

    Drug Metab. Dispos.

    (2003)
  • P. Lu et al.

    Drug Metab. Dispos.

    (2001)
  • T.L. Domanski et al.

    Biochemistry

    (2001)
  • P.A. Williams et al.

    Science

    (2004)
  • M.-Y. Yoon et al.

    Drug Metab. Rev.

    (2004)
  • M. Shou et al.

    Curr. Drug Metab.

    (2001)
  • K. Korzekwa
  • J.B. Houston et al.
  • I.H. Segel

    • Cited by (0)

    View full text
    Copyright © 2004 Elsevier Inc. All rights reserved.