Drug toxicity is frequently caused by electrophilic reactive metabolites that covalently bind to proteins. Epoxides comprise a large class of three-membered cyclic ethers. These molecules are electrophilic and typically highly reactive due to ring tension and polarized carbon–oxygen bonds. Epoxides are metabolites often formed by cytochromes P450 acting on aromatic or double bonds. The specific location on a molecule that undergoes epoxidation is its site of epoxidation (SOE). Identifying a molecule’s SOE can aid in interpreting adverse events related to reactive metabolites and direct modification to prevent epoxidation for safer drugs. The foundation for this model was an algorithm originally designed to model sites of cytochromes P450 metabolism (called XenoSite) that was recently applied to model the intrinsic reactivity of diverse molecules with glutathione. Since publication, our work has continued down this line. The model can identify when structural alerts in drugs are bioactivated. Combining this with metabolite construction and reactivity prediction, we can identify likely pathways to reactivity in drugs. This effort is contributing new insights into how and when drugs are bioactivated into toxic metabolites, and may aid in making safer drugs.

Modeling epoxidation of drug-like molecules with a deep machine learning network

251st National Meeting (2016)

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