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Enzyme kinetic modelling as a tool to analyse the behaviour of cytochrome P450 catalysed reactions: application to amitriptyline N ‐demethylation
Author(s) -
SCHMIDER JÜRGEN,
GREENBLATT DAVID J.,
HARMATZ JEROLD S.,
SHADER RICHARD I.
Publication year - 1996
Publication title -
british journal of clinical pharmacology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.216
H-Index - 146
eISSN - 1365-2125
pISSN - 0306-5251
DOI - 10.1046/j.1365-2125.1996.35717.x
Subject(s) - chemistry , akaike information criterion , demethylation , substrate (aquarium) , hill differential equation , uncompetitive inhibitor , stereochemistry , kinetics , cytochrome p450 , enzyme , nortriptyline , non competitive inhibition , amitriptyline , biochemistry , pharmacology , mathematics , first order partial differential equation , gene expression , partial differential equation , dna methylation , exact differential equation , quantum mechanics , statistics , physics , gene , oceanography , medicine , geology
1 To determine kinetic parameters ( V max , K m ) for cytochrome P450 (CYP) mediated metabolic pathways, nonlinear least squares regression is commonly used to fit a model equation (e.g., Michaelis Menten [MM]) to sets of data points (reaction velocity vs substrate concentration). This method can also be utilized to determine the parameters for more complex mechanisms involving allosteric or multi‐enzyme systems. Akaike's Information Criterion (AIC), or an estimation of improvement of fit as successive parameters are introduced in the model ( F ‐test), can be used to determine whether application of more complex models is helpful. To evaluate these approaches, we have examined the complex enzyme kinetics of amitriptyline (AMI) N‐ demethylation in vitro by human liver microsomes. 2 For a 15‐point nortriptyline (NT) formation rate vs substrate (AMI) concentration curve, a two enzyme model, consisting of one enzyme with MM kinetics ( V max =1.2 nmol min −1 mg −1 , K m =24 μm) together with a sigmoidal component (described by an equation equivalent to the Hill equation for cooperative substrate binding; V max =2.1 nmol min −1 mg −1 , K ′=70 μm; Hill exponent n= 2.34), was favoured according to AIC and the F ‐test. 3 Data generated by incubating AMI under the same conditions but in the presence of 10 μm ketoconazole (KET), a CYP3A3/4 inhibitor, were consistent with a single enzyme model with substrate inhibition ( V max =0.74 nmol min −1 mg −1 , K m =186 μm, K 1 =0.0028 μm −1 ). 4 Sulphaphenazole (SPA), a CYP2C9 inhibitor, decreased the rate of NT formation in a concentration dependent manner, whereas a polyclonal rat liver CYP2C11 antibody, inhibitory for S‐mephenytoin 4′‐hydroxylation in humans, had no important effect on this reaction. 5 Incubation of AMI with 50 μm SPA resulted in a curve consistent with a two enzyme model, one with MM kinetics ( V max =0.72 nmol min −1 mg −1 , K m =54 μm) the other with ‘Hill‐kinetics’ ( V max =2.1 nmol min −1 mg −1 , K ′=195 μm; n= 2.38). 6 A fourth data‐set was generated by incubating AMI with 10 μm KET and 50 μm SPA. The proposed model of best fit describes two activities, one obeying MM‐kinetics ( V max =0.048 nmol min −1 mg −1 , K m =7 μm) and the other obeying MM kinetics but with substrate inhibition ( V max =0.8 nmol min −1 mg −1 , K m =443 μm, K 1 =0.0041 μm −1 ). 7 The combination of kinetic modelling tools and biological data has permitted the discrimination of at least three CYP enzymes involved in AMI N‐ demethylation. Two are identified as CYP3A3/4 and CYP2C9, although further work in several more livers is required to confirm the participation of the latter.