Gedeon Richter Plc., Discovery Chemistry, 19-21, Gyömroi út, Budapest H-1103, Hungary.
Expert Opin Drug Metab Toxicol. 2011 Mar;7(3):299-312. doi: 10.1517/17425255.2011.553599. Epub 2011 Feb 4.
Preclinical research involves the in vitro monitoring of metabolic stability to deliver compounds with improved ADME profiles. Prediction of the metabolically vulnerable points can substantially help in analyzing CYP-mediated metabolism data and support optimization efforts in drug discovery programs. Moreover, fast and reliable in silico predictions could accelerate the characterization of in vitro/in vivo metabolites.
This paper reviews in silico methods available for CYP-mediated site of metabolism (SOM) prediction. Comprehensive and practical knowledge in this field can guide the identification of best practice and may inspire ideas for the development of novel approaches.
Comparison of the efficacy of SOM prediction methodologies revealed the general dependency on the studied isoform and substrate set. Increasing knowledge on P450 X-ray structures, on biotransformations and on the mechanistic details of the catalytic cycle revolutionized the prediction of SOM. Although no ultimate solution exits, combined methods covering both steric and electronic effects are preferred on most of the pharmaceutically relevant isoforms.
临床前研究涉及体外监测代谢稳定性,以提供具有改善 ADME 特征的化合物。预测代谢脆弱点可以大大帮助分析 CYP 介导的代谢数据,并支持药物发现计划中的优化工作。此外,快速可靠的计算预测可以加速体外/体内代谢物的表征。
本文综述了可用于 CYP 介导的代谢部位(SOM)预测的计算方法。在这一领域的全面和实用知识可以指导确定最佳实践,并可能为开发新方法提供思路。
SOM 预测方法的功效比较表明,其一般依赖于所研究的同工酶和底物集。对 P450 X 射线结构、生物转化以及催化循环的机械细节的了解不断增加,彻底改变了 SOM 的预测。尽管没有最终的解决方案,但在大多数具有药物相关性的同工酶上,涵盖空间和电子效应的组合方法是首选。