Discovery Chemistry, Gedeon Richter plc, PO Box 27, 1475 Budapest, Hungary.
J Comput Aided Mol Des. 2010 May;24(5):399-408. doi: 10.1007/s10822-010-9347-3. Epub 2010 Apr 2.
A novel structure-based approach for site of metabolism prediction has been developed. This knowledge-based method consists of three steps: (1) generation of possible metabolites, (2) docking the predicted metabolites to the CYP binding site and (3) selection of the most probable metabolites based on their complementarity to the binding site. As a proof of concept we evaluated our method by using MetabolExpert for metabolite generation and Glide for docking into the binding site of the CYP2C9 crystal structure. Our method could identify the correct metabolite among the three best-ranked compounds in 69% of the cases. The predictive power of our knowledge-based method was compared to that achieved by substrate docking and two alternative literature approaches.
已经开发出一种基于结构的新型代谢部位预测方法。这种基于知识的方法包括三个步骤:(1)生成可能的代谢物,(2)将预测的代谢物对接至 CYP 结合部位,(3)根据与结合部位的互补性选择最可能的代谢物。作为概念验证,我们使用 MetabolExpert 进行代谢物生成,并使用 Glide 对接至 CYP2C9 晶体结构的结合部位,对我们的方法进行了评估。在 69%的情况下,我们的方法可以在三种排名最高的化合物中识别出正确的代谢物。我们的基于知识的方法的预测能力与底物对接和两种替代文献方法的预测能力进行了比较。