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Resilience of protein-protein interaction networks as determined by their large-scale topological features

机译:蛋白质-蛋白质相互作用网络的弹性由其大规模拓扑特征决定

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摘要

The relationship between the structure and function of biological networks constitutes a fundamental issue in systems biology. Particularly, the structure of protein-protein interaction networks is related to important biological functions. In this work, we investigated how such a resilience is determined by the large scale features of the respective networks. Four species are taken into account, namely yeast Saccharomyces cerevisiae, worm Caenorhabditis elegans, fly Drosophila melanogaster and Homo sapiens. We adopted two entropy-related measurements (degree entropy and dynamic entropy) in order to quantify the overall degree of robustness of these networks. We verified that while they exhibit similar structural variations under random node removal, they differ significantly when subjected to intentional attacks (hub removal). As a matter of fact, more complex species tended to exhibit more robust networks. More specifically, we quantified how six important measurements of the networks topology (namely clustering coefficient, average degree of neighbors, average shortest path length, diameter, assortativity coefficient, and slope of the power law degree distribution) correlated with the two entropy measurements. Our results revealed that the fraction of hubs and the average neighbor degree contribute significantly for the resilience of networks. In addition, the topological analysis of the removed hubs indicated that the presence of alternative paths between the proteins connected to hubs tend to reinforce resilience. The performed analysis helps to understand how resilience is underlain in networks and can be applied to the development of protein network models.
机译:生物网络的结构和功能之间的关系构成了系统生物学中的一个基本问题。特别地,蛋白质-蛋白质相互作用网络的结构与重要的生物学功能有关。在这项工作中,我们研究了如何通过各个网络的大规模功能确定这种弹性。考虑了四种,即酵母酿酒酵母,线虫秀丽隐杆线虫,果蝇蝇和智人。为了量化这些网络的整体鲁棒性,我们采用了两种与熵有关的度量(度熵和动态熵)。我们验证了,尽管它们在随机节点移除下表现出相似的结构变化,但在受到有意攻击(集线器移除)时却有显着差异。事实上,更复杂的物种倾向于表现出更强大的网络。更具体地说,我们量化了网络拓扑的六个重要度量(即聚类系数,平均邻居度,平均最短路径长度,直径,分类系数和幂律度分布的斜率)与两个熵度量之间的关系。我们的结果表明,集线器的比例和平均邻居度对网络的恢复能力有很大贡献。另外,对去除的集线器的拓扑分析表明,连接到集线器的蛋白质之间存在替代路径,这往往会增强弹性。进行的分析有助于了解网络的弹性如何,并可将其应用于蛋白质网络模型的开发。

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  • 来源
    《Molecular BioSystems》 |2011年第4期|p.1263-1269|共7页
  • 作者单位

    Departamento de Matemdtica Aplicada e Estatistica, Instituto de Ciêneias Matematicas e de Computação, Universidade de Sao Paulo-Campus de São Carlos, Caixa Postal 668, 13560-970 São Carlos, SP, Brazil;

    Instituto de Fsica de São Carlos, Universidade de São Paulo,Av. Trabalhador Sao Carlense 400, Caixa Postal 369 CEP 13560-970, São Carlos, Sao Paulo, Brazil;

    Instituto de Fsica de São Carlos, Universidade de São Paulo,Av. Trabalhador Sao Carlense 400, Caixa Postal 369 CEP 13560-970, São Carlos, Sao Paulo, Brazil;

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