Computational Models for Cytochrome P450: A Predictive Electronic Model for Aromatic Oxidation and Hydrogen Atom Abstraction

Abstract

This paper is available online at http://dmd.aspetjournals.org ABSTRACT:Experimental observations suggest that electronic characteristics play a role in the rates of substrate oxidation for cytochrome P450 enzymes. For example, the tendency for oxidation of a certain functional group generally follows the relative stability of the radicals that are formed (e.g., N-dealkylation > O-dealkylation > 2°c arbon oxidation > 1°carbon oxidation). In addition, results show that useful correlations between the rates of product formation can be developed using electronic models. In this article, we attempt to determine whether a combined computational model for aromatic and aliphatic hydroxylation can be developed. Toward this goal, we used a combination of experimental data and semiempirical molecular orbital calculations to predicted activation energies for aromatic and aliphatic hydroxylation. The resulting model extends the predictive capacity of our previous aliphatic hydroxylation model to include the second most important group of oxidations, aromatic hydroxylation. The combined model can account for about 83% of the variance in the data for the 20 compounds in the training set and has an error of about 0.7 kcal/mol. The P4501 enzymes are a superfamily of monooxygenases involved in the metabolism of both exogenous and endogenous compounds. Ironically, these enzymes play a central role in both the prevention and induction of chemical toxicities and carcinogenicity. Although most P450 oxidations of xenobiotics result in detoxification, occasionally a more toxic intermediate is formed. In fact, many ultimate toxins and carcinogens are formed by the bioactivation of less reactive compounds, and many bioactivation reactions are mediated by the P450 enzymes. Often bioactivation reactions are in competition with detoxification pathways for the same substrate. Since these enzymes play such a central role in both detoxification and bioactivation, predictive models for cytochrome P450 catalysis will be useful tools for evaluating of the potential risks of environmental exposures. One of the most pertinent but difficult problems in risk assessment is translating bench results and mechanistic information into a form that can be used. This article outlines steps toward the development of computational models from laboratory data into a form that can be used for risk assessments that accurately reflect experimental results. For example, these models now more completely describe all positions of metabolism for nitriles and should be more complete in predicting the toxicity related to nitrile metabolism. These semiempirical computational models blend experimental data and computational chemistry in such a way as to provide a consistent prediction of the bioactivation rates for a broad spectrum of compounds. In particular, these models can be used to predict xenobiotic metabolism by the P450 enzyme family, including the bioactivation of compounds to toxins and carcinogens.Models such as those presented here for P450-mediated reaction...

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