How graphical analysis helps interpreting optimal experimental designs for nonlinear enzyme kinetic models
How graphical analysis helps interpreting optimal experimental designs for nonlinear enzyme kinetic models
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DOI：
10.1002/aic.15814
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发表时间：
2017-11
期刊：
影响因子：
3.7
通讯作者：
Rüdiger Ohs;Jan Wendlandt;A. Spiess
中科院分区：
文献类型：
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作者：
Rüdiger Ohs;Jan Wendlandt;A. Spiess
进度曲线实验与最佳实验设计 (OED) 相结合是确定酶动力学的有效方法。然而，很难验证为什么建议进行特定实验来识别非线性酶动力学模型。因此，我们系统地研究了灵敏度以及基于灵敏度的 OED 标准的曲面图和等高线图。模型反应是酶催化醛与手性 2-羟基酮的自连接。可视化提高了对 OED 的理解，并允许推导和确认动力学识别的五个建议：1. 避免靠近反应平衡的实验，2. 选择尽可能大的设计空间，3. 优先选择 D（终止符）- 和 E（igenvalue）- 标准而不是 A（平均值）-标准，4. 应用酶浓度，使反应不会完成得太快，5. 很少有最佳实验可以显着改进参数估计。图形分析还提供有关选择适当优化算法的信息。本文受版权保护。版权所有。
Progress curve experiments combined with optimal experimental design (OED) are an efficient approach to determine enzyme kinetics. However, it is hardly possible to verify why specific experiments are suggested for nonlinear enzyme kinetic model identification. Therefore, we systematically investigated the surface and contour plots of the sensitivities and of the OED criteria which are based on sensitivities. The model reaction was an enzyme catalyzed self-ligation of aldehydes to chiral 2-hydroxyketones. The visualization improved the understanding of OED and allowed for deducing and confirming five suggestions for kinetic identification: 1. Avoid experiments vicinal to the reaction equilibrium, 2. Choose the design space as large as possible, 3. Prefer D(eterminant)- and E(igenvalue)-criteria over the A(verage)-criterion, 4. Apply enzyme concentrations such that the reaction does not complete too fast, and 5. Few optimal experiments result in significantly improved parameter estimations. The graphical analysis also provides information about selecting appropriate optimization algorithms. This article is protected by copyright. All rights reserved.