Wharton C W, Szawelski R J
Biochem J. 1982 May 1;203(2):351-60. doi: 10.1042/bj2030351.
Substitution of half-time parameters in the integrated form of the Michaelis-Menten equation for any enzyme-catalysed reaction yields an equation that gives a linear relationship between the half-time of the reaction and the substrate concentration at that point of the reaction. The logarithmic term of the integrated equation becomes a constant as a result of the substitution, which means that the use of the half-time plot of the equation requires calculation only of half-time and substrate-concentration values at various stages of the reaction. The half-time method is both simple and exact, being analogous to an [S(0)]/v(i) against [S(0)] plot. A direct linear form of the half-time plot has been devised that allows very simple estimation of Michaelis parameters and/or initial velocities from progress-curve data. This method involves no approximation and is statistically valid. Simulation studies have shown that linear-regression analysis of half-time plots provides unbiased estimates of the Michaelis parameters. Simulation of the effect of error in estimation of the product concentration at infinite time [P(infinity)] reveals that this is always a cause for concern, such errors being magnified approximately an order of magnitude in the estimate of the Michaelis constant. Both the half-time plot and the direct linear form have been applied to the analysis of a variety of experimental data. The method has been shown to produce excellent results provided certain simple rules are followed regarding criteria of experimental design. A set of rules has been formulated that, if followed, allows progress-curve data to be acquired and analysed in a reliable fashion. It is apparent that the use of modern spectrophotometers in carefully designed experiments allows the collection of data characterized by low noise and accurate [P(infinity)] estimates. [P(infinity)] values have been found, in the present work, to be precise to within +/-0.2% and noise levels have always been below 0.1% (signal-to-noise ratio approximately 1000). As a result of the considerations above, it is concluded that there is little to be feared with regard to the analysis of enzyme kinetics using complete progress curves, despite the generally lukewarm recommendations to be found in the literature. The saving in time, materials and experimental effort amply justify analysis of enzyme kinetics by progress-curve methods. Half-time plots linear to >/=90% of reaction have been obtained for some alpha-chymotrypsin-, papain- and fumarase-catalysed reactions.
对于任何酶催化反应,在米氏方程的积分形式中代入半衰期参数,会得到一个方程,该方程给出了反应半衰期与反应该时刻底物浓度之间的线性关系。由于代入操作,积分方程的对数项变为常数,这意味着使用该方程的半衰期图仅需计算反应各个阶段的半衰期和底物浓度值。半衰期法既简单又准确,类似于[S(0)]/v(i)对[S(0)]的作图。已设计出半衰期图的直接线性形式,可根据进程曲线数据非常简单地估算米氏参数和/或初始速度。该方法无需近似,且在统计学上有效。模拟研究表明,半衰期图的线性回归分析可提供米氏参数的无偏估计。对无限时间[P(∞)]时产物浓度估计误差的影响进行模拟,结果表明这始终是一个值得关注的问题,此类误差在米氏常数估计中会放大约一个数量级。半衰期图和直接线性形式均已应用于各种实验数据的分析。结果表明,只要遵循关于实验设计标准的某些简单规则,该方法就能产生出色的结果。已制定了一套规则,若遵循这些规则,就能以可靠的方式获取和分析进程曲线数据。显然,在精心设计的实验中使用现代分光光度计,能够收集具有低噪声和准确[P(∞)]估计值的数据。在本研究中发现,[P(∞)]值精确到±0.2%以内,噪声水平始终低于0.1%(信噪比约为1000)。基于上述考虑,得出结论:尽管文献中对此的推荐通常不温不火,但使用完整的进程曲线分析酶动力学无需担忧太多。在时间、材料和实验工作量方面的节省,充分证明了通过进程曲线法分析酶动力学是合理的。对于一些α-胰凝乳蛋白酶、木瓜蛋白酶和延胡索酸酶催化的反应,已获得反应至≥90%时呈线性的半衰期图。