We will describe a method for predicting P450 metabolism that combines quantum mechanical simulations to estimate the reactivity of potential sites of metabolism on a compound  with a ligand-based approach to accounting for the effects of orientation and steric constraints due to the binding pockets of different P450 isoforms. We will present validation results for this method for prediction of regioselectivity by the major drug metabolising isforms of P450.
However, while valuable, predicting the relative proportion of metabolite formation at different sites on a compound is only a partial solution to designing more stable compounds in drug discovery. The advantage of a quantum mechanical approach is that it provides a quantitative estimate of the reactivity of each site, from which additional information can be derived regarding the vulnerability of each site to metabolism in absolute terms. One such measurement is the site lability, as calculated by StarDrop™, which is a measure of the efficiency of the product formation step by comparison of the rate of product formation with that of decoupling to form water and inactivation of the oxidative enzyme species. This is an important factor in determining the overall rate of metabolism and we will illustrate how this provides valuable guidance regarding the potential to redesign compounds to overcome issues due to rapid metabolism by P450s.
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