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首页> 外文期刊>Physica, A. Statistical mechanics and its applications >The maximum entropy production and maximum Shannon information entropy in enzyme kinetics
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The maximum entropy production and maximum Shannon information entropy in enzyme kinetics

机译:酶动力学中的最大熵生产和最大香农信息熵

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We demonstrate that the maximum entropy production principle (MEPP) serves as a physical selection principle for the description of the most probable non-equilibrium steady states in simple enzymatic reactions. A theoretical approach is developed, which enables maximization of the density of entropy production with respect to the enzyme rate constants for the enzyme reaction in a steady state. Mass and Gibbs free energy conservations are considered as optimization constraints. In such a way computed optimal enzyme rate constants in a steady state yield also the most uniform probability distribution of the enzyme states. This accounts for the maximal Shannon information entropy. By means of the stability analysis it is also demonstrated that maximal density of entropy production in that enzyme reaction requires flexible enzyme structure, which enables rapid transitions between different enzyme states. These results are supported by an example, in which density of entropy production and Shannon information entropy are numerically maximized for the enzyme Glucose Isomerase. (C) 2018 Elsevier B.V. All rights reserved.
机译:我们证明了最大熵生产原理(MEPP)作为物理选择原理,用于描述在简单的酶促反应中最可能的非平衡稳态。开发了理论方法,这使得能够在稳定状态下最大限度地实现酶率常数的熵产生的密度。质量和吉布斯自由节能被认为是优化约束。以这种方式,在稳态产量中计算的最佳酶速率常数也是酶态的最均匀概率分布。这占最大香农信息熵。通过稳定性分析,还证明了酶反应中的熵产生的最大密度需要柔性酶结构,这使得不同酶态之间的快速转变。这些结果由示例支持,其中熵产生的密度和香农信息熵的密度为酶葡萄糖异构酶的数量最大化。 (c)2018年elestvier b.v.保留所有权利。

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