Bäuerle Felix, Zotter Agnes, Schreiber Gideon
Department of Biomolecular Sciences, Weizmann Institute of Science, 234 Herzel St, Rehovot 76100, Israel.
Max Planck Institute for Dynamics and Self-Organization, Am Faßberg 17, D-37077 Goettingen, Germany.
Protein Eng Des Sel. 2017 Mar 1;30(3):149-156. doi: 10.1093/protein/gzw053.
With computer-based data-fitting methods becoming a standard tool in biochemistry, progress curve analysis of enzyme kinetics is a feasible, yet seldom used tool. Here we present a versatile Matlab-based tool (PCAT) to analyze catalysis progress curves with three complementary model approaches. The first two models are based on the known closed-form solution for this problem: the first describes the required Lambert W function with an analytical approximation and the second provides a numerical solution of the Lambert W function. The third model is a direct simulation of the enzyme kinetics. Depending on the chosen model, the tools excel in speed, accuracy or initial value requirements. Using simulated and experimental data, we show the strengths and pitfalls of the different fitting models. Direct simulation proves to have the highest level of accuracy, but it also requires reasonable initial values to converge. Finally, we propose a standard procedure to obtain optimized enzyme kinetic parameters from single progress curves.
随着基于计算机的数据拟合方法成为生物化学中的标准工具,酶动力学的进展曲线分析是一种可行但很少使用的工具。在这里,我们展示了一种基于Matlab的通用工具(PCAT),用于通过三种互补模型方法分析催化进展曲线。前两个模型基于该问题的已知封闭形式解:第一个用解析近似描述所需的兰伯特W函数,第二个提供兰伯特W函数的数值解。第三个模型是酶动力学的直接模拟。根据所选模型,这些工具在速度、准确性或初始值要求方面表现出色。使用模拟和实验数据,我们展示了不同拟合模型的优点和缺陷。直接模拟证明具有最高的准确性水平,但它也需要合理的初始值才能收敛。最后,我们提出了一种从单个进展曲线获得优化酶动力学参数的标准程序。