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首页> 外文期刊>The Journal of Chemical Physics >Stochastic theory of large-scale enzyme-reaction networks: Finite copy number corrections to rate equation models
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Stochastic theory of large-scale enzyme-reaction networks: Finite copy number corrections to rate equation models

机译:大规模酶反应网络的随机理论:速率方程模型的有限拷贝数校正

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Chemical reactions inside cells occur in compartment volumes in the range of atto- to femtoliters. Physiological concentrations realized in such small volumes imply low copy numbers of interacting molecules with the consequence of considerable fluctuations in the concentrations. In contrast, rate equation models are based on the implicit assumption of infinitely large numbers of interacting molecules, or equivalently, that reactions occur in infinite volumes at constant macroscopic concentrations. In this article we compute the finite-volume corrections (or equivalently the finite copy number corrections) to the solutions of the rate equations for chemical reaction networks composed of arbitrarily large numbers of enzyme-catalyzed reactions which are confined inside a small subcellular compartment. This is achieved by applying a mesoscopic version of the quasisteady-state assumption to the exact Fokker-Planck equation associated with the Poisson representation of the chemical master equation. The procedure yields impressively simple and compact expressions for the finite-volume corrections. We prove that the predictions of the rate equations will always underestimate the actual steady-state substrate concentrations for an enzyme-reaction network confined in a small volume. In particular we show that the finite-volume corrections increase with decreasing subcellular volume, decreasing Michaelis-Menten constants, and increasing enzyme saturation. The magnitude of the corrections depends sensitively on the topology of the network. The predictions of the theory are shown to be in excellent agreement with stochastic simulations for two types of networks typically associated with protein methylation and metabolism.
机译:细胞内部的化学反应在隔室容积中以atto至femL的范围发生。在如此小的体积中实现的生理浓度意味着相互作用分子的拷贝数低,其结果是浓度有很大的波动。相反,速率方程模型基于无限大量相互作用分子的隐含假设,或者等效地,反应在恒定的宏观浓度下以无限的体积发生。在本文中,我们计算了化学反应网络速率方程解的有限体积校正(或等效的有限拷贝数校正),该化学反应网络由任意数量的酶催化反应组成,并限制在一个小的亚细胞室内。这是通过将准稳态假设的介观形式应用于与化学主方程的泊松表示相关的精确Fokker-Planck方程来实现的。该过程为有限体积校正提供了令人印象深刻的简单且紧凑的表达式。我们证明速率方程的预测将始终低估局限在小体积内的酶反应网络的实际稳态底物浓度。特别是,我们显示出有限体积的校正随着亚细胞体积的减少,Michaelis-Menten常数的减少以及酶饱和度的增加而增加。校正的幅度敏感地取决于网络的拓扑。该理论的预测与两种通常与蛋白质甲基化和代谢相关的网络的随机模拟非常吻合。

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