消除生化网络随机模拟中的快速反应：一种双稳态遗传开关
Eliminating fast reactions in stochastic simulations of biochemical networks: a bistable genetic switch
摘要：
在生物化学反应网络的许多随机模拟中，需要“粗粒度”反应集，去除快速反应，同时保留正确的系统动力学。已经提出了各种粗粒化方法，但仍然不清楚哪些方法是可靠的，哪些反应可以安全地消除。我们解决这些问题的模型基因调控网络，是特别敏感的动态波动：一个双稳态遗传开关。我们删除蛋白质-DNA和/或蛋白质-蛋白质缔合-解离反应的反应集，使用各种粗粒化策略。我们确定对稳态概率分布函数和波动驱动的开关翻转过渡的速率的影响。我们发现，蛋白质相互作用可以安全地从反应集中消除，但蛋白质-DNA相互作用可能不会。我们还发现，重要的是使用化学主方程，而不是宏观速率方程来计算有效的倾向函数的粗粒度反应。
英文摘要：
In many stochastic simulations of biochemical reaction networks, it is desirable to ``coarse-grain'' the reaction set, removing fast reactions while retaining the correct system dynamics. Various coarse-graining methods have been proposed, but it remains unclear which methods are reliable and which reactions can safely be eliminated. We address these issues for a model gene regulatory network that is particularly sensitive to dynamical fluctuations: a bistable genetic switch. We remove protein-DNA and/or protein-protein association-dissociation reactions from the reaction set, using various coarse-graining strategies. We determine the effects on the steady-state probability distribution function and on the rate of fluctuation-driven switch flipping transitions. We find that protein-protein interactions may be safely eliminated from the reaction set, but protein-DNA interactions may not. We also find that it is important to use the chemical master equation rather than macroscopic rate equations to compute effective propensity functions for the coarse-grained reactions.
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