通过小图度签名揭示生物网络功能
Uncovering Biological Network Function via Graphlet Degree Signatures
摘要：
蛋白质是生命体中必不可少的大分子，因此了解它们的功能非常重要。功能上未分类的蛋白质的数量很大，即使是简单的和充分研究的生物体，如面包酵母。用于确定蛋白质功能的方法已经将其焦点从仅基于序列同源性的靶向特定蛋白质转移到基于蛋白质相互作用（PPI）网络的整个蛋白质组的分析。由于蛋白质聚集以执行特定功能，因此分析PPI网络的结构特性可能会提供有关单个蛋白质、它们参与的蛋白质复合物甚至更大的亚细胞机器的生物功能的有用线索。我们设计了一个灵敏的图论方法来比较节点邻域的局部结构，证明在PPI网络中，节点的生物功能和它的局部网络结构是密切相关的。该方法分组拓扑相似的蛋白质在PPI网络的这种措施下，并表明，这些蛋白质组属于相同的蛋白质复合物，执行相同的生物功能，定位在相同的亚细胞区室，并具有相同的组织表达。此外，我们将我们的技术应用于蛋白质组规模的网络数据，并推断尚未分类的蛋白质的生物学功能，这表明我们的方法可以为未来的实验研究提供有价值的指导。
英文摘要：
Proteins are essential macromolecules of life and thus understanding their function is of great importance. The number of functionally unclassified proteins is large even for simple and well studied organisms such as baker's yeast. Methods for determining protein function have shifted their focus from targeting specific proteins based solely on sequence homology to analyses of the entire proteome based on protein-protein interaction (PPI) networks. Since proteins aggregate to perform a certain function, analyzing structural properties of PPI networks may provide useful clues about the biological function of individual proteins, protein complexes they participate in, and even larger subcellular machines. We design a sensitive graph theoretic method for comparing local structures of node neighborhoods that demonstrates that in PPI networks, biological function of a node and its local network structure are closely related. The method groups topologically similar proteins under this measure in a PPI network and shows that these protein groups belong to the same protein complexes, perform the same biological functions, are localized in the same subcellular compartments, and have the same tissue expressions. Moreover, we apply our technique on a proteome-scale network data and infer biological function of yet unclassified proteins demonstrating that our method can provide valuable guidelines for future experimental research.
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