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J Comput Aided Mol Des. 2018 Apr;32(4):537-546. doi: 10.1007/s10822-018-0107-0. Epub 2018 Feb 20.

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

Author information

1
Optibrium Ltd., F5-6 Blenheim House, Cambridge Innovation Park, Denny End Road, Cambridge, CB25 9PB, UK. peter@optibrium.com.
2
Optibrium Ltd., F5-6 Blenheim House, Cambridge Innovation Park, Denny End Road, Cambridge, CB25 9PB, UK.
3
The European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Cambridge, CB10 1SD, UK.

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.

KEYWORDS:

Cytochrome P450; Drug–drug interactions; Metabolism; Multi-class classification; Random forests

PMID:
29464466
DOI:
10.1007/s10822-018-0107-0

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