朗伯W函数
米氏-门汀动力学
酶动力学
化学
动力学
功能(生物学)
常量(计算机编程)
基质(水族馆)
反应速率常数
分析化学(期刊)
酶
数学
计算机科学
色谱法
物理
有机化学
数学分析
酶分析
地质学
海洋学
生物
进化生物学
程序设计语言
量子力学
活动站点
作者
Cheenou Her,Aaron P. Alonzo,Justin Y. Vang,Ernesto Lopez Torres,V. V. Krishnan
标识
DOI:10.1021/acs.jchemed.5b00136
摘要
Enzyme kinetics is an essential part of a chemistry curriculum, especially for students interested in biomedical research or in health care fields. Though the concept is routinely performed in undergraduate chemistry/biochemistry classrooms using other spectroscopic methods, we provide an optimized approach that uses a real-time monitoring of the kinetics by quantitative NMR (qNMR) spectroscopy and a direct analysis of the time course data using Lambert-W function. The century old Michaelis–Menten equation, one of the fundamental concepts in biochemistry, relates the time derivative of the substrate to two kinetic parameters (the Michaelis constant KM and the maximum rate Vmax) and to the concentration of the substrate. The exact solution to the Michaelis–Menten equation, in terms of the Lambert-W function, is not available in standard curve-fitting tools. The high-quality of the real-time qNMR data on the enzyme kinetics enables a revisit of the concept of applying the progress curve analysis. This is particularly made feasible with the advent of analytical approximations of the Lambert-W function. Thus, the combination of NMR experimental time-course data with progress curve analysis is demonstrated in the case of enzyme (invertase) catalyzed hydrolysis reaction (conversion of sucrose to fructose and glucose) to provide students with direct and simple estimations of kinetic parameters of Michaelis–Menten. Complete details on how to implement the experiment and perform data analysis are provided in the Supporting Information.
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