Computational methods and tools to predict cytochrome P450 metabolism for drug discovery

Abstract

In this review, we present important, recent developments in the computational prediction of cytochrome P450 (CYP) metabolism in the context of drug discovery. We discuss in silico models for the various aspects of CYP metabolism prediction, including CYP substrate and inhibitor predictors, site of metabolism predictors (i.e., metabolically labile sites within potential substrates) and metabolite structure predictors. We summarize the different approaches taken by these models, such as rule‐based methods, machine learning, data mining, quantum chemical methods, molecular interaction fields, and docking. We highlight the scope and limitations of each method and discuss future implications for the field of metabolism prediction in drug discovery.

Computer-Aided Estimation of Biological Activity Profiles of Drug-Like Compounds Taking into Account Their Metabolism in Human Body

“…Such methods estimate the biological activity profiles with reasonable accuracy based on the structural formula of drug-like compounds. Similarly, computational methods are used to predict drug metabolism (see, e.g., [ 4 , 11 , 12 , 13 , 30 , 31 , 32 ]). These methods predict (a) the interaction of the drug substance with particular biotransformation enzymes, (b) the most probable sites of biotransformation, (c) the most probable metabolites.…”

“…Detailed consideration of the drug’s effects on the organism must include the complex analysis of chemical–biological interactions, which may be performed using up-to-date chemoinformatics approaches [ 6 ]. Machine learning methods allow for estimating drug–target interactions with reasonable accuracy, which produces probable biological activity profiles [ 7 , 8 , 9 , 10 ] and different characteristics of drug metabolism [ 4 , 11 , 12 , 13 ]. However, to the best of our knowledge, an investigation that combine the in silico estimates of drug metabolism and predictions of the biological activity profiles for both the parent drug and its metabolites, has never been conducted.…”

In SilicoInvestigations on Curcuminoids fromCurcuma longaas Positive Regulators of Wnt/β-catenin Signaling Pathway in Wound Healing

“…So, rigorous testing of compound's probability of being metabolized by the CYP450 enzymes is a prerequisite for drug discovery approach. In silico approach for CYP450 utilizes 2D structure of a compound to determine which site in a molecule is more liable to metabolism by CYP450 enzymes [70] [71]. Curcumin I showed better result in P450 site of metabolism prediction ( Table 5) (Figure 7).…”

Prediction of drug metabolites using neural machine translation

“…Traditionally drug metabolism is studied experimentally using analytical techniques, such as mass spectrometry, which are resource demanding. 4 Multiple efforts have been made for developing computational tools for drug metabolism prediction 5,6 to assist experimental evaluation and also facilitate the incorporation of metabolic studies at the early stages of drug development. 7 Most of the existing tools are specically designed for predicting metabolism through CYP450 enzymes that are responsible for metabolizing about 70-80% of existing drugs.…”

“…Methods that have gained popularity, both from a computational and a practical standpoint, are the ones that aim at identifying the atoms within the molecule involved in the metabolic transformation, called sites of metabolism. 5,6 In practice, if the sites of metabolism are known, the structure of a lead compound can be modied in order to manipulate its metabolism. However, the sites of metabolism per se do not give insights on the structure of metabolites that may cause toxicity or other complications.…”