Zhang Rumin, Wong Kenny
a Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc. , Kenilworth , NJ , USA.
Expert Opin Drug Discov. 2017 Jan;12(1):17-37. doi: 10.1080/17460441.2017.1245721. Epub 2016 Nov 3.
Enzymes are the macromolecular catalysts of many living processes and represent a sizable proportion of all druggable biological targets. Enzymology has been practiced just over a century during which much progress has been made in both the identification of new enzymes and the development of novel methodologies for enzyme kinetics. Areas covered: This review aims to address several key practical aspects in enzyme kinetics in reference to translational drug discovery research. The authors first define what constitutes a high performance enzyme kinetic assay. The authors then review the best practices for turnover, activation and inhibition kinetics to derive critical parameters guiding drug discovery. Notably, the authors recommend global progress curve analysis of dose/time dependence employing an integrated Michaelis-Menten equation and global curve fitting of dose/dose dependence. Expert opinion: The authors believe that in vivo enzyme and substrate abundance and their dynamics, binding modality, drug binding kinetics and enzyme's position in metabolic networks should be assessed to gauge the translational impact on drug efficacy and safety. Integrating these factors in a systems biology and systems pharmacology model should facilitate translational drug discovery.
酶是许多生命过程的大分子催化剂,并且在所有可成药的生物学靶点中占相当大的比例。酶学已经发展了一个多世纪,在此期间,在新酶的鉴定和酶动力学新方法的开发方面都取得了很大进展。涵盖领域:本综述旨在探讨酶动力学中与转化药物发现研究相关的几个关键实际问题。作者首先定义了什么构成高性能酶动力学测定。然后作者回顾了周转率、激活和抑制动力学的最佳实践,以得出指导药物发现的关键参数。值得注意的是,作者推荐采用积分米氏方程对剂量/时间依赖性进行全局进程曲线分析以及对剂量/剂量依赖性进行全局曲线拟合。专家观点:作者认为,应该评估体内酶和底物的丰度及其动态变化、结合方式、药物结合动力学以及酶在代谢网络中的位置,以衡量对药物疗效和安全性的转化影响。将这些因素整合到系统生物学和系统药理学模型中应有助于转化药物发现。