Department of Chemistry, McGill University, 801 Sherbrooke St W, Montreal, QC H3A 0B8, Canada.
J Chem Inf Model. 2012 Sep 24;52(9):2471-83. doi: 10.1021/ci3003073. Epub 2012 Sep 4.
The metabolism of xenobiotics--and more specifically drugs--in the liver is a critical process controlling their half-life. Although there exist experimental methods, which measure the metabolic stability of xenobiotics and identify their metabolites, developing higher throughput predictive methods is an avenue of research. It is expected that predicting the chemical nature of the metabolites would be an asset for designing safer drugs and/or drugs with modulated half-lives. We have developed IMPACTS (In-silico Metabolism Prediction by Activated Cytochromes and Transition States), a computational tool combining docking to metabolic enzymes, transition state modeling, and rule-based substrate reactivity prediction to predict the site of metabolism (SoM) of xenobiotics. Its application to sets of CYP1A2, CYP2C9, CYP2D6, and CYP3A4 substrates and comparison to experts' predictions demonstrates its accuracy and significance. IMPACTS identified an experimentally observed SoM in the top 2 predicted sites for 77% of the substrates, while the accuracy of biotransformation experts' prediction was 65%. Application of IMPACTS to external sets and comparison of its accuracy to those of eleven other methods further validated the method implemented in IMPACTS.
外源物质（尤其是药物）在肝脏中的代谢是控制其半衰期的关键过程。尽管存在测量外源物质代谢稳定性和鉴定其代谢物的实验方法，但开发更高通量的预测方法是一个研究方向。预计预测代谢物的化学性质将有助于设计更安全的药物和/或半衰期可调节的药物。我们开发了 IMPACTS（通过激活细胞色素和过渡态的体内代谢预测），这是一种计算工具，结合了对代谢酶的对接、过渡态建模和基于规则的底物反应性预测，以预测外源物质的代谢部位（SoM）。将其应用于一组 CYP1A2、CYP2C9、CYP2D6 和 CYP3A4 底物，并与专家预测进行比较，证明了其准确性和意义。IMPACTS 在外源物质的代谢部位（SoM）的预测中，对于 77%的底物，其预测结果在前两个预测位点中得到了验证，而生物转化专家预测的准确性为 65%。将 IMPACTS 应用于外部数据集，并将其准确性与其他 11 种方法进行比较，进一步验证了 IMPACTS 中实现的方法。
