Metzner C, Sajitz-Hermstein M, Schmidberger M, Fabry B
Biophysics Group, Department of Physics, University of Erlangen, Henkestrasse 91, D-91052 Erlangen, Germany.
Phys Rev E Stat Nonlin Soft Matter Phys. 2009 Aug;80(2 Pt 1):021915. doi: 10.1103/PhysRevE.80.021915. Epub 2009 Aug 17.
Biochemical reaction networks in living cells usually involve reversible covalent modification of signaling molecules, such as protein phosphorylation. Under conditions of small molecule numbers, as is frequently the case in living cells, mass-action theory fails to describe the dynamics of such systems. Instead, the biochemical reactions must be treated as stochastic processes that intrinsically generate concentration fluctuations of the chemicals. We investigate the stochastic reaction kinetics of covalent modification cycles (CMCs) by analytical modeling and numerically exact Monte Carlo simulation of the temporally fluctuating concentration. Depending on the parameter regime, we find for the probability density of the concentration qualitatively distinct classes of distribution functions including power-law distributions with a fractional and tunable exponent. These findings challenge the traditional view of biochemical control networks as deterministic computational systems and suggest that CMCs in cells can function as versatile and tunable noise generators.
活细胞中的生化反应网络通常涉及信号分子的可逆共价修饰，比如蛋白质磷酸化。在小分子数量较少的情况下（活细胞中经常如此），质量作用定律无法描述这类系统的动力学。相反，生化反应必须被视为本质上会产生化学物质浓度波动的随机过程。我们通过对随时间波动的浓度进行解析建模和数值精确的蒙特卡罗模拟，研究了共价修饰循环（CMC）的随机反应动力学。根据参数范围，我们发现浓度的概率密度具有定性不同的分布函数类别，包括具有分数且可调指数的幂律分布。这些发现挑战了将生化控制网络视为确定性计算系统的传统观点，并表明细胞中的CMC可以作为通用且可调的噪声发生器发挥作用。
