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首页> 外文期刊>The FEBS journal >Clusters of reaction rates and concentrations in proteinnetworks such as the phosphotransferase system
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Clusters of reaction rates and concentrations in proteinnetworks such as the phosphotransferase system

机译：蛋白质网络（例如磷酸转移酶系统）中反应速率和浓度的簇

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To understand the functioning of living cells, it is often helpful or even necessaryto exploit inherent timescale disparities and focus on long-termdynamic behaviour. In the present study, we explore this type of behaviourfor the biochemical network of the phosphotransferase system. We showthat, during the slow phase that follows a fast initial transient, the networkreaction rates are partitioned into clusters corresponding to connected partsof the reaction network. Rates within any of these clusters assume essentiallythe same value: differences within each cluster are vastly smaller thanthat from one cluster to another. This rate clustering induces an analogousclustering of the reactive compounds: only the molecular concentrations onthe interface between these clusters are produced and consumed at substantiallydifferent rates and hence change considerably during the slow phase.The remaining concentrations essentially assume their steady-state valuesalready by the end of the transient phase. Further, we find that this clusteringphenomenon occurs for a large number of parameter values and alsofor models with different topologies; to each of these models, there correspondsa particular network partitioning. Our results show that, in spite ofits complexity, the phosphotransferase system tends to behave in a rathersimple (yet versatile) way. The persistence of clustering for the perturbedmodels we examined suggests that it is likely to be encountered in variousenvironmental conditions, as well as in other signal transduction pathwayswith network structures similar to that of the phosphotransferase system.
机译：要了解活细胞的功能，利用内在的时标差异并专注于长期动态行为通常是有帮助的，甚至是必要的。在本研究中，我们探索磷酸转移酶系统的生化网络的这种行为。我们表明，在跟随快速初始瞬变的缓慢阶段中，网络反应速率被分为与反应网络的连接部分相对应的簇。这些群集中任何一个的速率都假定具有基本相同的值：每个群集中的差异远小于一个群集与另一个群集之间的差异。这种速率聚集引起反应性化合物的类似聚集：仅在这些聚集之间的界面上的分子浓度以基本上不同的速率产生和消耗，因此在慢速阶段会发生相当大的变化。过渡阶段。此外，我们发现这种聚类现象发生在大量参数值以及具有不同拓扑的模型中。对于这些模型中的每一个，都有一个特定的网络分区。我们的结果表明，尽管其复杂性，但磷酸转移酶系统仍倾向于以一种相当简单（但仍通用）的方式运行。对于我们研究的扰动模型，聚类的持久性表明，它可能在各种环境条件下以及在具有与磷酸转移酶系统相似的网络结构的其他信号转导途径中遇到。

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