Heuett William J, Qian Hong
Department of Applied Mathematics, University of Washington, Seattle, Washington 98195, USA.
J Chem Phys. 2006 Jan 28;124(4):044110. doi: 10.1063/1.2165193.
In this paper we present the results of a stochastic model of reversible biochemical reaction networks that are being driven through an open boundary, such that the system is interacting with its surrounding environment with explicit material exchange. The stochastic model is based on the master equation approach and is intimately related to the grand canonical ensemble of statistical mechanics. We show that it is possible to analytically calculate the joint probability function of the random variables describing the number of molecules in each state of the system for general linear networks. Definitions of reaction chemical potentials and conductances follow from inherent properties of this model, providing a description of energy dissipation in the system. We are also able to suggest novel methods for experimentally determining reaction fluxes and biochemical affinities at nonequilibrium steady state as well as the overall network connectivity.
在本文中，我们展示了一个可逆生化反应网络的随机模型的结果，该网络通过开放边界驱动，使得系统通过明确的物质交换与其周围环境相互作用。该随机模型基于主方程方法，并且与统计力学的巨正则系综密切相关。我们表明，对于一般的线性网络，可以解析计算描述系统每个状态下分子数的随机变量的联合概率函数。反应化学势和电导率的定义源于该模型的固有特性，从而对系统中的能量耗散进行了描述。我们还能够提出新颖的方法，用于在非平衡稳态下通过实验确定反应通量和生化亲和力以及整个网络的连通性。
