State-of-the-art Tools for Computational Site of Metabolism Predictions: Comparative Analysis, Mechanistical Insights, and Future Applications

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.

Key Words :

• Cytochrome P450 (CYP450)
• Metabolism
• Heme
• Computational prediction
• Structure-based design
• Ligand-based design
• Reactivity
• DFT
• Docking
• Data mining