Stochastic approach to molecular interactions and computational theory of metabolic and genetic regulations
Stochastic approach to molecular interactions and computational theory of metabolic and genetic regulations
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DOI：
10.1016/j.jtbi.2007.06.017
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发表时间：
2007-10-21
影响因子：
2
通讯作者：
Tanaka, R. J.
中科院分区：
文献类型：
--
作者：
Kimura, H.;Okano, H.;Tanaka, R. J.
代谢和遗传调节的潜在分子机制在计算上是相同的，并且可以通过有限状态马尔可夫过程来描述。我们建立了一个共同的计算模型，这两个法规的基础上平稳分布的马尔可夫过程的目的是建立一个统一的，定量模型的一般生物法规。各种现有的结果，细胞内的规定，包括经典的Michaelis-Menten方程及其推广到更复杂的变构酶在一个系统的方式。引入概率流的概念来区分平衡定态分布和非平衡定态分布，它在定态方程的分析中起着至关重要的作用。导出了保证平衡平稳分布存在的一个图形判据，它与经典的Wegscheider条件完全相同。简单的图形方法来计算的平衡和非平衡稳态分布的概率流的基础上，这大大简化了经典的方法仍然在酶学。(C)2007爱思唯尔有限公司版权所有。
The underlying molecular mechanisms of metabolic and genetic regulations are computationally identical and can be described by a finite state Markov process. We establish a common computational model for both regulations based on the stationary distribution of the Markov process with the aim of establishing a unified, quantitative model of general biological regulations. Various existing results regarding intracellular regulations are derived including the classical Michaelis-Menten equation and its generalization to more complex allosteric enzymes in a systematic way. The notion of probability flow is introduced to distinguish the equilibrium stationary distribution from the non-equilibrium one; it plays a crucial role in the analysis of stationary state equations. A graphical criterion to guarantee the existence of an equilibrium stationary distribution is derived, which turns out to be identical to the classical Wegscheider condition. Simple graphical methods to compute the equilibrium and non-equilibrium stationary distributions are derived based crucially on the probability flow, which dramatically simplifies the classical methods still used in enzymology. (C) 2007 Elsevier Ltd. All rights reserved.