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首页> 外文期刊>PLoS Computational Biology >Age-Dependent Evolution of the Yeast Protein Interaction Network Suggests a Limited Role of Gene Duplication and Divergence
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Age-Dependent Evolution of the Yeast Protein Interaction Network Suggests a Limited Role of Gene Duplication and Divergence

机译:酵母蛋白质相互作用网络的年龄依赖性进化表明基因复制和发散的有限作用。

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Proteins interact in complex protein–protein interaction (PPI) networks whose topological properties—such as scale-free topology, hierarchical modularity, and dissortativity—have suggested models of network evolution. Currently preferred models invoke preferential attachment or gene duplication and divergence to produce networks whose topology matches that observed for real PPIs, thus supporting these as likely models for network evolution. Here, we show that the interaction density and homodimeric frequency are highly protein age–dependent in real PPI networks in a manner which does not agree with these canonical models. In light of these results, we propose an alternative stochastic model, which adds each protein sequentially to a growing network in a manner analogous to protein crystal growth (CG) in solution. The key ideas are (1) interaction probability increases with availability of unoccupied interaction surface, thus following an anti-preferential attachment rule, (2) as a network grows, highly connected sub-networks emerge into protein modules or complexes, and (3) once a new protein is committed to a module, further connections tend to be localized within that module. The CG model produces PPI networks consistent in both topology and age distributions with real PPI networks and is well supported by the spatial arrangement of protein complexes of known 3-D structure, suggesting a plausible physical mechanism for network evolution.
机译:蛋白质在复杂的蛋白质-蛋白质相互作用(PPI)网络中相互作用,其拓扑特性(例如无标度拓扑,分层模块化和可分配性)已提出了网络进化的模型。当前优选的模型调用优先附着或基因复制和发散,以产生其拓扑与实际PPI所观察到的拓扑相匹配的网络,从而支持这些作为网络进化的可能模型。在这里,我们证明了相互作用密度和同二聚体频率在真实的PPI网络中高度依赖蛋白质的年龄,其方式与这些规范模型不一致。根据这些结果,我们提出了另一种随机模型,该模型以类似于溶液中蛋白质晶体生长(CG)的方式,将每种蛋白质依次添加到生长网络中。关键思想是(1)交互作用概率随未使用的交互表面的可用性而增加,因此遵循反优先连接规则;(2)随着网络的增长,高度连接的子网络会变成蛋白质模块或复合物;(3)一旦将一种新蛋白质固定在模块上,其他连接就倾向于定位在该模块内。 CG模型产生的PPI网络在拓扑结构和年龄分布上都与真实的PPI网络一致,并且由已知3-D结构的蛋白质复合物的空间排列方式很好地支持,这暗示了网络进化的合理物理机制。

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