State-of-the-art tools for computational site of metabolism predictions: comparative analysis, mechanistical insights, and future applications

Drug Metab Rev. 2007;39(1):61-86. doi: 10.1080/03602530600969374.

Abstract

In drug design, it is crucial to have reliable information on how a chemical entity behaves in the presence of metabolizing enzymes. This requires substantial experimental efforts. Consequently, being able to predict the likely site/s of metabolism in any compound, synthesized or virtual, would be highly beneficial and time efficient. In this work, six different methodologies for predictions of the site of metabolism (SOM) have been compared and validated using structurally diverse data sets of drug-like molecules with well-established metabolic pattern in CYP3A4, CYP2C9, or both. Three of the methods predict the SOM based on the ligand's chemical structure, two additional methods use structural information of the enzymes, and the sixth method combines structure and ligand similarity and reactivity. The SOM is correctly predicted in 50 to 90% of the cases, depending on method and enzyme, which is an encouraging rate. We also discuss the underlying mechanisms of cytochrome P450 metabolism in the light of the results from this comparison.

Publication types

  • Comparative Study
  • Evaluation Study

MeSH terms

  • Algorithms
  • Aryl Hydrocarbon Hydroxylases / metabolism
  • Binding Sites
  • Computational Biology / methods*
  • Computational Biology / trends
  • Cytochrome P-450 CYP2C9
  • Cytochrome P-450 CYP3A
  • Cytochrome P-450 Enzyme System / metabolism
  • Humans
  • Hydrophobic and Hydrophilic Interactions
  • Molecular Structure
  • Pharmaceutical Preparations / chemistry*
  • Pharmaceutical Preparations / metabolism*
  • Principal Component Analysis

Substances

  • Pharmaceutical Preparations
  • Cytochrome P-450 Enzyme System
  • CYP2C9 protein, human
  • Cytochrome P-450 CYP2C9
  • Aryl Hydrocarbon Hydroxylases
  • Cytochrome P-450 CYP3A
  • CYP3A4 protein, human