Utilization of integrated Michaelis-Menten equations for enzyme inhibition diagnosis and determination of kinetic constants using Solver supplement of Microsoft Office Excel
Utilization of integrated Michaelis-Menten equations for enzyme inhibition diagnosis and determination of kinetic constants using Solver supplement of Microsoft Office Excel
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DOI：
10.1016/j.cmpb.2012.08.017
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发表时间：
2013-01-01
影响因子：
6.1
通讯作者：
Dias, Albino A.
中科院分区：
文献类型：
--
作者：
Bezerra, Rui M. F.;Fraga, Irene;Dias, Albino A.
酶动力学参数通常由初始速率确定，然而，实验室仪器仅测量底物或产物浓度与反应时间的关系(进度曲线)。为了克服这一问题，我们提出了一种基于Michaelis-Menten方程的集成模型。进程曲线分析最严重的实际限制发生在酶在选定的分析条件下显示出活性丧失时。为了避免这个问题，可以使用用于确定初始速率的相同实验点。这一方法是通过使用由碱性磷酸酶催化的众所周知的反应的积分动力学方程来说明的。在这项工作中，使用Solver附录(Microsoft Office Excel)进行了非线性回归。它很容易处理并以图形方式跟踪SSE(平方误差和)的收敛。根据Akaike信息标准进行酶抑制诊断。(C)2012爱思唯尔爱尔兰有限公司。保留所有权利。
Enzyme kinetic parameters are usually determined from initial rates nevertheless, laboratory instruments only measure substrate or product concentration versus reaction time (progress curves). To overcome this problem we present a methodology which uses integrated models based on Michaelis-menten equation. The most severe practical limitation of progress curve analysis occurs when the enzyme shows a loss of activity under the chosen assay conditions. To avoid this problem it is possible to work with the same experimental points utilized for initial rates determination. This methodology is illustrated by the use of integrated kinetic equations with the well-known reaction catalyzed by alkaline phosphatase enzyme. In this work nonlinear regression was performed with the Solver supplement (Microsoft Office Excel). It is easy to work with and track graphically the convergence of SSE (sum of square errors). The diagnosis of enzyme inhibition was performed according to Akaike information criterion. (C) 2012 Elsevier Ireland Ltd. All rights reserved.