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.

中文翻译：

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whichP450：预测化合物主要代谢CYP450亚型的多类分类模型。

在新型药物的开发中，了解化合物的I相代谢中涉及多少种细胞色素P450异构体以及哪些异构体的知识非常重要。如果化合物在药物相互作用或遗传多态性方面主要由单一同工型代谢，则可能引起潜在的问题，这将导致一般人群的暴露水平发生变化。结合每种亚型代谢的区域选择性模型，这种模型也将有助于预测可能由P450介导的代谢形成的代谢产物。我们描述了一个多类随机森林模型的生成，以预测在七种主要的细胞色素P450亚型中，哪些将是新型化合物的主要代谢亚型。