利用整数规划和反馈顶点集求布尔模型下代谢网络的最小反应切

Takeyuki Tamura, Kazuhiro Takemoto, T. Akutsu
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引用次数: 52

摘要

在本文中,作者考虑了给定一个代谢网络,一组源化合物和一组目标化合物,寻找最小尺寸反应切割的问题,其中使用布尔模型作为代谢网络的模型。该问题在代谢网络结构稳健性测量和药物靶点检测方面具有潜在的应用前景。他们开发了一种基于整数规划的方法来解决这个优化问题。为了处理循环和可逆反应,他们进一步发展了一种新的整数规划(IP)形式化方法,使用反馈顶点集(FVS)。当应用于从KEGG数据库获得的由糖酵解/糖异生、柠檬酸循环和戊糖磷酸途径组成的大肠杆菌代谢网络时,基于fvs的方法可以比单纯的基于ip的方法更快地找到一组最优的反应,比基于通量平衡的方法快几倍。作者还证实,我们提出的方法甚至适用于大型网络,并讨论了我们结果的生物学意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Finding Minimum Reaction Cuts of Metabolic Networks Under a Boolean Model Using Integer Programming and Feedback Vertex Sets
In this paper, the authors consider the problem of, given a metabolic network, a set of source compounds and a set of target compounds, finding a minimum size reaction cut, where a Boolean model is used as a model of metabolic networks. The problem has potential applications to measurement of structural robustness of metabolic networks and detection of drug targets. They develop an integer programming-based method for this optimization problem. In order to cope with cycles and reversible reactions, they further develop a novel integer programming (IP) formalization method using a feedback vertex set (FVS). When applied to an E. coli metabolic network consisting of Glycolysis/Glyconeogenesis, Citrate cycle and Pentose phosphate pathway obtained from KEGG database, the FVS-based method can find an optimal set of reactions to be inactivated much faster than a naive IP-based method and several times faster than a flux balance-based method. The authors also confirm that our proposed method works even for large networks and discuss the biological meaning of our results.
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