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PNAS Plus: Reaction dynamics analysis of a reconstituted Escherichia coli protein translation system by computational modeling

机译:PNAS Plus:通过计算模型对重构的大肠杆菌蛋白质翻译系统进行反应动力学分析

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摘要

To elucidate the dynamic features of a biologically relevant large-scale reaction network, we constructed a computational model of minimal protein synthesis consisting of 241 components and 968 reactions that synthesize the Met-Gly-Gly (MGG) peptide based on an Escherichia coli-based reconstituted in vitro protein synthesis system. We performed a simulation using parameters collected primarily from the literature and found that the rate of MGG peptide synthesis becomes nearly constant in minutes, thus achieving a steady state similar to experimental observations. In addition, concentration changes to 70% of the components, including intermediates, reached a plateau in a few minutes. However, the concentration change of each component exhibits several temporal plateaus, or a quasi-stationary state (QSS), before reaching the final plateau. To understand these complex dynamics, we focused on whether the components reached a QSS, mapped the arrangement of components in a QSS in the entire reaction network structure, and investigated time-dependent changes. We found that components in a QSS form clusters that grow over time but not in a linear fashion, and that this process involves the collapse and regrowth of clusters before the formation of a final large single cluster. These observations might commonly occur in other large-scale biological reaction networks. This developed analysis might be useful for understanding large-scale biological reactions by visualizing complex dynamics, thereby extracting the characteristics of the reaction network, including phase transitions.
机译:为了阐明生物学相关的大规模反应网络的动态特征,我们构建了一个最小蛋白质合成的计算模型,该模型由241个成分和968个反应组成,这些反应基于基于大肠杆菌的合成Met-Gly-Gly(MGG)肽重组体外蛋白质合成系统。我们使用主要从文献中收集的参数进行了模拟,发现MGG肽的合成速率在数分钟内几乎变得恒定,因此达到了类似于实验观察的稳定状态。此外,包括中间体在内的70%组分的浓度变化在几分钟内达到了平稳状态。但是,每种成分的浓度变化在达到最终平稳之前都表现出几个时间平稳状态或准平稳状态(QSS)。为了了解这些复杂的动力学过程,我们重点研究了组件是否达到QSS,在整个反应网络结构中映射了QSS中组件的排列,并研究了随时间变化的情况。我们发现,QSS中的组件形成随时间增长但不以线性方式增长的群集,并且此过程涉及群集的折叠和再生长,直到形成最终的大型单个群集。这些观察通常可能发生在其他大规模生物反应网络中。通过可视化复杂动力学,从而提取反应网络的特征(包括相变),这种发达的分析对于理解大规模生物反应可能有用。

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