Structure-Based Methods for the Prediction of the Dominant P450 Enzyme in Human Drug Biotransformation: Consideration of CYP3A4, CYP2C9, CYP2D6

Abstract

Metabolic drug–drug interactions are receiving more and more attention from the in silico community. Early prediction of such interactions would not only improve drug safety but also contribute to make drug design more predictable and rational. The aim of this study was to build a simple and interpretable model for the determination of the P450 enzyme predominantly responsible for a drug's metabolism. The P450 enzymes taken into consideration were CYP3A4, CYP2D6 and CYP2C9. Physico-chemical descriptors and structural descriptors for 96 currently marketed drugs were submitted to statistical analysis using the formal inference-based recursive modelling (FIRM) method, a form of recursive partitioning. Generally accepted knowledge on metabolism by these enzymes was also used to construct a hierarchical decision tree. Robust methods of variable selection using recursive partitioning were utilised. The descriptive ability of the resulting hierarchical model is very satisfactory, with 94% of the compounds correctly classified.

Keywords:

• Drug interactions
• QSPKR
• Metabolism
• Recursive partitioning
• WHIM descriptors
• Hydrogen bond factors

Notes

Presented at the 11th International Workshop on Quantitative Structure-Activity Relationships in the Human Health and Environmental Sciences (QSAR2004), 9–13 May 2004, Liverpool, England.

Additional information

Notes on contributors

M.T.D. Cronin

Presented at the 11th International Workshop on Quantitative Structure-Activity Relationships in the Human Health and Environmental Sciences (QSAR2004), 9–13 May 2004, Liverpool, England.