论估算酶催化反应初始速度的方法误差及其纠正方法:乳酸脱氢酶案例研究

IF 4.033 Q4 Biochemistry, Genetics and Molecular Biology
A. Yu. Lianguzov, N. M. Malygina, T. A. Petrova
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引用次数: 0

摘要

摘要 介绍了一种通用算法,用于在直接测量酶活性的动力学过程中,根据底物消耗或产物积累的动力学曲线,计算酶反应在 "零 "时刻的初始速度。研究以商业乳酸脱氢酶制剂和一套标准生化试剂为例进行。所提出的方法实际上消除了系统测量误差,无论酶活性水平如何,都能以相同的准确度确定初始反应速度,将分析时间缩短到 1 分钟,并扩大了标准试剂盒的应用范围,可用于研究不同来源的酶样本,以解决各种任务。在分析过程中使用共轭酶系统时不能使用该算法,因为在这种情况下,动力学曲线上会有一个较长的初始滞后期。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

On Methodological Errors in Estimating the Initial Velocities of Enzyme-Catalyzed Reactions and Approaches to Their Correction: A Case Study with Lactate Dehydrogenase

On Methodological Errors in Estimating the Initial Velocities of Enzyme-Catalyzed Reactions and Approaches to Their Correction: A Case Study with Lactate Dehydrogenase

A universal algorithm for calculating the initial velocities of enzymatic reactions at the “zero” moment of time according to the kinetic curve of substrate consumption or product accumulation during direct kinetic measurements of enzyme activity is presented. The study was performed using the example of a commercial lactate dehydrogenase preparation and a standard biochemical set of reagents. The proposed approach makes it possible to practically eliminate systematic measurement error, to determine the initial reaction velocity with equal accuracy regardless of the level of enzyme activity, to reduces the analysis time to 1 min, and to expand the scope of application of standard reagent kits for the study of samples of enzymes of different origin in solving a wide range of tasks. The algorithm cannot be applied when using conjugated enzyme systems in an analytical procedure, since in this case there is a long initial lag phase on the kinetic curves.

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来源期刊
Biophysics
Biophysics Biochemistry, Genetics and Molecular Biology-Biophysics
CiteScore
1.20
自引率
0.00%
发文量
67
期刊介绍: Biophysics is a multidisciplinary international peer reviewed journal that covers a wide scope of problems related to the main physical mechanisms of processes taking place at different organization levels in biosystems. It includes structure and dynamics of macromolecules, cells and tissues; the influence of environment; energy transformation and transfer; thermodynamics; biological motility; population dynamics and cell differentiation modeling; biomechanics and tissue rheology; nonlinear phenomena, mathematical and cybernetics modeling of complex systems; and computational biology. The journal publishes short communications devoted and review articles.
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