COMPARISON OF METHODS FOR THE PREDICTION OF THE METABOLIC SITES FOR CYP3A4-MEDIATED METABOLIC REACTIONS

@article{citeulike:2619656, abstract = {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. 10.1124/dmd.105.008631}, author = {Zhou, Diansong and Afzelius, Lovisa and Grimm, Scott W. and Andersson, Tommy B. and Zauhar, Randy J. and Zamora, Ismael }, citeulike-article-id = {2619656}, doi = {http://dx.doi.org/10.1124/dmd.105.008631}, journal = {Drug Metab Dispos}, keywords = {metasite, p450}, month = {June}, number = {6}, pages = {976--983}, posted-at = {2008-04-01 13:47:05}, priority = {2}, title = {COMPARISON OF METHODS FOR THE PREDICTION OF THE METABOLIC SITES FOR CYP3A4-MEDIATED METABOLIC REACTIONS}, url = {http://dx.doi.org/10.1124/dmd.105.008631}, volume = {34}, year = {2006} }

TY - JOUR ID - citeulike:2619656 L3 - citeulike-article-id:2619656 N2 - 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. 10.1124/dmd.105.008631 IS - 6 JF - Drug Metab Dispos EP - 983 TI - COMPARISON OF METHODS FOR THE PREDICTION OF THE METABOLIC SITES FOR CYP3A4-MEDIATED METABOLIC REACTIONS VL - 34 SP - 976 KW - metasite KW - p450 AU - Zhou, Diansong AU - Afzelius, Lovisa AU - Grimm, Scott AU - Andersson, Tommy AU - Zauhar, Randy AU - Zamora, Ismael PY - 2006/06/01/ UR - http://dx.doi.org/10.1124/dmd.105.008631 ER -