Schlosser P M, Holcomb T, Bailey J E
Chemical Industry Institute Of Toxicology, 6 Davis Drive, PO Box 12137, Research Triangle Park, North Carolina 27709, USA.
Biotechnol Bioeng. 1993 May;41(11):1027-38. doi: 10.1002/bit.260411105.
The application of metabolic control theory (MCT), or other methods of determining metabolic sensitivity to the rates of specific cellular processes, such as enzymatic reactions, requires knowledge of the elasticity coefficients (system partial derivatives) for the processes under study. Although rate equations are available in the literature for some enzymatic reactions, there are many reactions and processes for which this is not the case. Although one could perform the experiments necessary to determine the rate equations for a given system, these equations are, in fact, not required for the calculation of sensitivities--only the elasticities (the derivatives) are needed. A more direct and efficient approach would be to compute elasticities directly from experimental data. Errors can analysis and alternative regression techniques are presented which not only allow one to eliminate data components with excessive noise, but also provide guidance as to what additional data may be require for accurate sensitivity analysis. This information indicates which measurements require more accuracy and what additional experiments should be conducted to reduce errors in calculated metabolic sensitivity coefficients.
代谢控制理论(MCT)或其他确定代谢对特定细胞过程(如酶促反应)速率敏感性的方法的应用,需要了解所研究过程的弹性系数(系统偏导数)。尽管文献中已有一些酶促反应的速率方程,但仍有许多反应和过程并非如此。虽然可以进行确定给定系统速率方程所需的实验,但实际上计算敏感性并不需要这些方程——只需要弹性系数(导数)。一种更直接有效的方法是直接从实验数据计算弹性系数。本文提出了误差分析和替代回归技术,这些技术不仅能让人们消除噪声过大的数据成分,还能为准确的敏感性分析所需的额外数据提供指导。这些信息表明哪些测量需要更高的精度,以及应该进行哪些额外的实验来减少计算出的代谢敏感性系数中的误差。