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Predicting reactivity to drug metabolism: beyond P450s—modelling FMOs and UGTs

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Abstract

We present a study based on density functional theory calculations to explore the rate limiting steps of product formation for oxidation by Flavin-containing Monooxygenase (FMO) and glucuronidation by the UDP-glucuronosyltransferase (UGT) family of enzymes. FMOs are responsible for the modification phase of metabolism of a wide diversity of drugs, working in conjunction with Cytochrome P450 (CYP) family of enzymes, and UGTs are the most important class of drug conjugation enzymes. Reactivity calculations are important for prediction of metabolism by CYPs and reactivity alone explains around 70–85% of the experimentally observed sites of metabolism within CYP substrates. In the current work we extend this approach to propose model systems which can be used to calculate the activation energies, i.e. reactivity, for the rate-limiting steps for both FMO oxidation and glucuronidation of potential sites of metabolism. These results are validated by comparison with the experimentally observed reaction rates and sites of metabolism, indicating that the presented models are suitable to provide the basis of a reactivity component within generalizable models to predict either FMO or UGT metabolism.

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Data availability

The data used in the project is available through the referenced publications. The supporting information includes Cartesian coordinates, Z-matrices and total DFT energy values of the presented structures. In addition, the general DFT input files are provided. Code availability: The software used in the project is freely available through the referenced publications.

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The research was funded by Optibrium Ltd. and Lhasa Ltd.

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Correspondence to Mario Öeren.

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MÖ, PAH and MDS are employees of Optibrium Ltd. DJP is an employee of Lhasa Ltd. PJW was an employee of Optibrium Ltd. for the duration of the FMO project.

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Öeren, M., Walton, P.J., Hunt, P.A. et al. Predicting reactivity to drug metabolism: beyond P450s—modelling FMOs and UGTs. J Comput Aided Mol Des 35, 541–555 (2021). https://doi.org/10.1007/s10822-020-00321-1

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