WhichP450: a multi-class categorical model to predict the major metabolising CYP450 isoform for a compound

Journal of Computer-aided Molecular Design
Peter A HuntJonathan D Tyzack

Abstract

In the development of novel pharmaceuticals, the knowledge of how many, and which, Cytochrome P450 isoforms are involved in the phase I metabolism of a compound is important. Potential problems can arise if a compound is metabolised predominantly by a single isoform in terms of drug-drug interactions or genetic polymorphisms that would lead to variations in exposure in the general population. Combined with models of regioselectivities of metabolism by each isoform, such a model would also aid in the prediction of the metabolites likely to be formed by P450-mediated metabolism. We describe the generation of a multi-class random forest model to predict which, out of a list of the seven leading Cytochrome P450 isoforms, would be the major metabolising isoforms for a novel compound. The model has a 76% success rate with a top-1 criterion and an 88% success rate for a top-2 criterion and shows significant enrichment over randomised models.

References

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Citations

Nov 25, 2018·Chemical Biology & Drug Design·Jonathan D Tyzack, Johannes Kirchmair
Apr 5, 2020·Molecules : a Journal of Synthetic Chemistry and Natural Product Chemistry·Rama KaradshehSimon Cocklin
Jan 12, 2021·Computers in Biology and Medicine·Tomaž StepišnikDragi Kocev
Aug 8, 2021·Molecules : a Journal of Synthetic Chemistry and Natural Product Chemistry·Malte HolmerJohannes Kirchmair
Jun 2, 2020·Journal of Chemical Information and Modeling·Benedict W J IrwinGareth J Conduit
Oct 12, 2019·Journal of Chemical Information and Modeling·Xiaoqi ShanDong-Qing Wei

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