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Stochastic sequestration dynamics: a minimal model with extrinsic noise for bimodal distributions and competitors correlation

机译:随机螯合动力学:具有外部噪声的双峰分布和竞争者相关性的最小模型

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Many biological processes are known to be based on molecular sequestration. This kind of dynamics involves two types of molecular species, namely targets and sequestrants, that bind to form a complex. In the simple framework of mass-action law, key features of these systems appear to be threshold-like profiles of the amounts of free molecules as a function of the parameters determining their possible maximum abundance. However, biochemical processes are probabilistic and take place in stochastically fluctuating environments. How these different sources of noise affect the final outcome of the network is not completely characterised yet. In this paper we specifically investigate the effects induced by a source of extrinsic noise onto a minimal stochastic model of molecular sequestration. We analytically show how bimodal distributions of the targets can appear and characterise them as a result of noise filtering mediated by the threshold response. We then address the correlations between target species induced by the sequestrant and discuss how extrinsic noise can turn the negative correlation caused by competition into a positive one. Finally, we consider the more complex scenario of competitive inhibition for enzymatic kinetics and discuss the relevance of our findings with respect to applications.
机译:已知许多生物学过程都基于分子螯合。这种动力学涉及两种分子类型,即目标分子和螯合剂,它们结合形成复合物。在质量作用定律的简单框架中,这些系统的关键特征似乎是自由分子数量的阈值状分布,这是决定其可能最大丰度的参数的函数。但是,生化过程是概率性的,发生在随机波动的环境中。这些不同的噪声源如何影响网络的最终结果,目前尚不完全清楚。在本文中,我们专门研究了外部噪声源对分子螯合的最小随机模型产生的影响。我们分析性地显示了由于阈值响应介导的噪声过滤,目标的双峰分布如何出现并表征它们。然后,我们讨论了螯合剂诱导的目标物种之间的相关性,并讨论了外部噪声如何将竞争引起的负相关变成正相关。最后,我们考虑竞争抑制酶动力学的更为复杂的情况,并讨论我们的发现与应用之间的相关性。

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