Sajitz-Hermstein Max, Nikoloski Zoran
Systems Biology and Mathematical Modeling Group, Max Planck Institute of Molecular Plant Physiology, Am Mühlenweg 1, 14476, Potsdam, Germany.
BMC Res Notes. 2016 Jun 21;9:317. doi: 10.1186/s13104-016-2117-0.
The flux phenotype describes the entirety of biochemical conversions in a cell, which renders it a key characteristic of metabolic function. To quantify the functional relevance of individual biochemical reactions, functional centrality has been introduced based on cooperative game theory and structural modeling. It was shown to be capable to determine metabolic control properties utilizing only structural information. Here, we demonstrate the capability of functional centrality to predict changes in the flux phenotype.
We use functional centrality to successfully predict changes of metabolic flux triggered by switches in the environment. The predictions via functional centrality improve upon predictions using control-effective fluxes, another measure aiming at capturing metabolic control using structural information.
The predictions of flux changes via functional centrality corroborate the capability of the measure to gain a mechanistic understanding of metabolic control from the structure of metabolic networks.
通量表型描述了细胞内生化转化的整体情况,这使其成为代谢功能的一个关键特征。为了量化单个生化反应的功能相关性,基于合作博弈论和结构建模引入了功能中心性。结果表明,它仅利用结构信息就能确定代谢控制特性。在此,我们展示了功能中心性预测通量表型变化的能力。
我们使用功能中心性成功预测了环境切换引发的代谢通量变化。通过功能中心性进行的预测比使用控制有效通量的预测有所改进,控制有效通量是另一种旨在利用结构信息捕捉代谢控制的度量。
通过功能中心性对通量变化的预测证实了该度量从代谢网络结构中获得代谢控制机制理解的能力。