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Identification of Conserved Moieties in Metabolic Networks by Graph Theoretical Analysis of Atom Transition Networks

机译:利用原子跃迁网络的图论分析识别代谢网络中的保守部分

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摘要

Conserved moieties are groups of atoms that remain intact in all reactions of a metabolic network. Identification of conserved moieties gives insight into the structure and function of metabolic networks and facilitates metabolic modelling. All moiety conservation relations can be represented as nonnegative integer vectors in the left null space of the stoichiometric matrix corresponding to a biochemical network. Algorithms exist to compute such vectors based only on reaction stoichiometry but their computational complexity has limited their application to relatively small metabolic networks. Moreover, the vectors returned by existing algorithms do not, in general, represent conservation of a specific moiety with a defined atomic structure. Here, we show that identification of conserved moieties requires data on reaction atom mappings in addition to stoichiometry. We present a novel method to identify conserved moieties in metabolic networks by graph theoretical analysis of their underlying atom transition networks. Our method returns the exact group of atoms belonging to each conserved moiety as well as the corresponding vector in the left null space of the stoichiometric matrix. It can be implemented as a pipeline of polynomial time algorithms. Our implementation completes in under five minutes on a metabolic network with more than 4,000 mass balanced reactions. The scalability of the method enables extension of existing applications for moiety conservation relations to genome-scale metabolic networks. We also give examples of new applications made possible by elucidating the atomic structure of conserved moieties.
机译:保守部分是在代谢网络的所有反应中保持完整的原子组。保守部分的鉴定使人们深入了解代谢网络的结构和功能,并促进了代谢建模。所有部分保守性关系都可以表示为化学计量矩阵对应于生化网络的左侧零空间中的非负整数向量。存在仅基于反应化学计量来计算这样的载体的算法,但是它们的计算复杂性将其应用限制在相对小的代谢网络中。此外,现有算法返回的向量通常不表示具有定义的原子结构的特定部分的保守性。在这里,我们表明保守部分的鉴定除了化学计量之外还需要有关反应原子映射的数据。我们提出了一种新的方法,通过对其潜在的原子过渡网络的图论分析来识别代谢网络中的保守部分。我们的方法返回属于每个保守部分的精确原子组以及化学计量矩阵的左空空间中的相应向量。可以将其实现为多项式时间算法的流水线。我们的代谢过程在不到5分钟的时间内完成,并具有4,000多个质量平衡反应。该方法的可扩展性使得能够将用于部分保守性关系的现有应用扩展到基因组规模的代谢网络。我们还给出了通过阐明保守部分的原子结构而使新应用成为可能的示例。

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