RT Journal Article SR Electronic T1 COMPARISON OF METHODS FOR THE PREDICTION OF THE METABOLIC SITES FOR CYP3A4-MEDIATED METABOLIC REACTIONS JF Drug Metabolism and Disposition JO Drug Metab Dispos FD American Society for Pharmacology and Experimental Therapeutics SP 976 OP 983 DO 10.1124/dmd.105.008631 VO 34 IS 6 A1 Diansong Zhou A1 Lovisa Afzelius A1 Scott W. Grimm A1 Tommy B. Andersson A1 Randy J. Zauhar A1 Ismael Zamora YR 2006 UL http://dmd.aspetjournals.org/content/34/6/976.abstract AB Predictions of the metabolic sites for new chemical entities, synthesized or only virtual, are important in the early phase of drug discovery to guide chemistry efforts in the synthesis of new compounds with reduced metabolic liability. This information can now be obtained from in silico predictions, and therefore, a thorough and unbiased evaluation of the computational techniques available is needed. Several computational methods to predict the metabolic hot spots are emerging. In this study, metabolite identification using MetaSite and a docking methodology, GLUE, were compared. Moreover, the published CYP3A4 crystal structure and computed CYP3A4 homology models were compared for their usefulness in predicting metabolic sites. A total of 227 known CYP3A4 substrates reported to have one or more metabolites adding up to 325 metabolic pathways were analyzed. Distance-based fingerprints and four-point pharmacophore derived from GRID molecular interaction fields were used to characterize the substrate and protein in MetaSite and the docking methodology, respectively. The CYP3A4 crystal structure and homology model with the reactivity factor enabled achieved a similar prediction success (78%) using the MetaSite method. The docking method had a relatively lower prediction success (∼57% for the homology model), although it still may provide useful insights for interactions between ligand and protein, especially for uncommon reactions. The MetaSite methodology is automated, rapid, and has relatively accurate predictions compared with the docking methodology used in this study. The American Society for Pharmacology and Experimental Therapeutics