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使用全准稳态近似法对耦合酶促反应网络进行建模。

Modeling networks of coupled enzymatic reactions using the total quasi-steady state approximation.

作者信息

Ciliberto Andrea, Capuani Fabrizio, Tyson John J

机构信息

The FIRC Institute for Molecular Oncology, Milan, Italy.

出版信息

PLoS Comput Biol. 2007 Mar 16;3(3):e45. doi: 10.1371/journal.pcbi.0030045.

DOI:10.1371/journal.pcbi.0030045
PMID:17367203
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC1828705/
Abstract

In metabolic networks, metabolites are usually present in great excess over the enzymes that catalyze their interconversion, and describing the rates of these reactions by using the Michaelis-Menten rate law is perfectly valid. This rate law assumes that the concentration of enzyme-substrate complex (C) is much less than the free substrate concentration (S0). However, in protein interaction networks, the enzymes and substrates are all proteins in comparable concentrations, and neglecting C with respect to S0 is not valid. Borghans, DeBoer, and Segel developed an alternative description of enzyme kinetics that is valid when C is comparable to S0. We extend this description, which Borghans et al. call the total quasi-steady state approximation, to networks of coupled enzymatic reactions. First, we analyze an isolated Goldbeter-Koshland switch when enzymes and substrates are present in comparable concentrations. Then, on the basis of a real example of the molecular network governing cell cycle progression, we couple two and three Goldbeter-Koshland switches together to study the effects of feedback in networks of protein kinases and phosphatases. Our analysis shows that the total quasi-steady state approximation provides an excellent kinetic formalism for protein interaction networks, because (1) it unveils the modular structure of the enzymatic reactions, (2) it suggests a simple algorithm to formulate correct kinetic equations, and (3) contrary to classical Michaelis-Menten kinetics, it succeeds in faithfully reproducing the dynamics of the network both qualitatively and quantitatively.

摘要

在代谢网络中,代谢物的含量通常大大超过催化其相互转化的酶,因此使用米氏速率定律描述这些反应的速率是完全有效的。该速率定律假定酶 - 底物复合物(C)的浓度远低于游离底物浓度(S0)。然而,在蛋白质相互作用网络中,酶和底物都是浓度相当的蛋白质,相对于S0忽略C是无效的。博尔汉斯、德布尔和西格尔提出了一种酶动力学的替代描述,当C与S0相当的时候该描述是有效的。我们将这种被博尔汉斯等人称为总准稳态近似的描述扩展到耦合酶促反应网络。首先,我们分析当酶和底物浓度相当的时候一个孤立的戈德贝特 - 科什兰德开关。然后,基于一个控制细胞周期进程的分子网络的实际例子,我们将两个和三个戈德贝特 - 科什兰德开关耦合在一起,以研究蛋白激酶和磷酸酶网络中的反馈效应。我们的分析表明,总准稳态近似为蛋白质相互作用网络提供了一种出色的动力学形式体系,因为(1)它揭示了酶促反应的模块化结构,(2)它提出了一种简单的算法来制定正确的动力学方程,并且(3)与经典的米氏动力学相反,它成功地在定性和定量方面忠实地再现了网络的动态。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16b3/1847993/3d9b6f058cbf/pcbi.0030045.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16b3/1847993/59c65b2d34af/pcbi.0030045.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16b3/1847993/80aba2a3f4ba/pcbi.0030045.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16b3/1847993/4f00b287ade8/pcbi.0030045.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16b3/1847993/5a76f3f41904/pcbi.0030045.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16b3/1847993/3d9b6f058cbf/pcbi.0030045.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16b3/1847993/59c65b2d34af/pcbi.0030045.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16b3/1847993/80aba2a3f4ba/pcbi.0030045.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16b3/1847993/4f00b287ade8/pcbi.0030045.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16b3/1847993/5a76f3f41904/pcbi.0030045.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16b3/1847993/3d9b6f058cbf/pcbi.0030045.g005.jpg

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