Skip to main content


  • Oral presentation
  • Open Access

A novel method for predicting ligand regioselectivity to metabolism by the CYP3A4 enzyme

  • 1,
  • 1,
  • 1 and
  • 1
Chemistry Central Journal20093 (Suppl 1) :O8

  • Published:


  • Molecular Docking
  • Drug Discovery Process
  • QSAR Analysis
  • Rapid Dynamic
  • Metabolic Site

The CYP-P450 3A4 enzyme is responsible for metabolizing 50% of marketed drugs, covering a wide space of structural diversity [1]. From a drug discovery standpoint, knowledge of ligand regional propensity to metabolism is essential.

Experimental metabolite characterization is done using liquid chromatography/tandem mass spectrometry [2]. While accurate, this technique is time consuming and labor intensive. This is unfeasible for high throughput testing of molecules under development early in the drug discovery process. What is needed is a quick, accurate, interpretable technique for identifying ligand regioselectivity to metabolism by the 3A4 isozyme. A number of in silico methods have been reported upon CYP 3A4 site of metabolism prediction. These methods revolve around one of two metrics: a ligand based QSAR analysis [3], or fingerprint based molecular docking and scoring [4].

In the present method, topologically distinct regions of a ligand are identified and ranked as putative metabolic sites. Ranking is performed on the basis of 1) easily calculable electronic properties of each unique region and 2) spacial and steric scoring based upon a constrained rapid dynamics simulation. The electronic property based component of this methodology has already been reported and was found to be 71% accurate in the absence of the rapid simulation component [5]. The final combined method can be used as a reliable metric for evaluating metabolic liability of lead compounds.

Authors’ Affiliations

120 Cogswell 110 8th street, 12180 Troy, NY, USA


  1. Singh S: A Model for Predicting Likely Sites of CYP3A4-mediated Metabolism on Drug-like Molecules. J Med Chem. 2003, 46: 1330-10.1021/jm020400s.View ArticleGoogle Scholar
  2. Afzelius L: State-of-the-art Tools for Computational Site of Metabolism Predictions: Comparative Analysis, Mechanistical insights, and Future Applications. Drug Metabolism Reviews. 2007, 39: 61-10.1080/03602530600969374.View ArticleGoogle Scholar
  3. Sheridan R: Emperical Regioselectivity Models for Human Cytochromes P450 3A4, 2D6, and 2C9. J Med Chem. 2007, 50: 3173-10.1021/jm0613471.View ArticleGoogle Scholar
  4. Cruciani G: MetaSite: Understanding Metabolism in Human Cytochromes from the Perspective of the Chemist. J Med Chem. 2005, 44: 6970-10.1021/jm050529c.View ArticleGoogle Scholar
  5. Bergeron C: Multiple Instance Ranking. ICML. 2008, []Google Scholar


© Zaretzki et al; licensee BioMed Central Ltd. 2009

This article is published under license to BioMed Central Ltd.