Global protein function prediction from protein-protein interaction networks
Global protein function prediction from protein-protein interaction networks
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DOI：
10.1038/nbt825
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发表时间：
2003-06-01
影响因子：
46.9
通讯作者：
Vespignani, A
中科院分区：
文献类型：
--
作者：
Vazquez, A;Flammini, A;Vespignani, A
确定蛋白质功能是后基因组时代最具挑战性的问题之一。全基因组序列的可用性和确定基因共表达模式的高通量能力已经将研究重点从单个蛋白质或小复合物的研究转移到整个蛋白质组的研究（1）。在这种情况下，寻找可靠的方法分配蛋白质功能是至关重要的。有各种方法可用于推断未知功能的蛋白质的功能，使用来自共调节基因的序列相似性或聚类模式的信息（2，3），系统发育谱（4），蛋白质-蛋白质相互作用（参考文献2，4）。5-8和Samanta，M.和Liang，S.，未发表的数据）和蛋白质复合物（9，10）。在这里，我们提出了分配的蛋白质的功能类的基础上，其网络的物理相互作用，通过最大限度地减少不同的功能类别之间的蛋白质相互作用的数量。功能分配是蛋白质组范围内的，由蛋白质网络的全局连接模式决定。该方法导致多个功能分配，多个等价的解决方案的存在的后果。我们应用该方法来分析酵母酿酒酵母蛋白质-蛋白质相互作用网络（5）。该方法的鲁棒性进行了测试，在一个系统中含有高比例的未分类的蛋白质，也在特定的蛋白质相互作用的缺失和插入的情况下。
Determining protein function is one of the most challenging problems of the post-genomic era. The availability of entire genome sequences and of high-throughput capabilities to determine gene coexpression patterns has shifted the research focus from the study of single proteins or small complexes to that of the entire proteome(1). In this context, the search for reliable methods for assigning protein function is of primary importance. There are various approaches available for deducing the function of proteins of unknown function using information derived from sequence similarity or clustering patterns of coregulated genes(2,3), phylogenetic profiles(4), protein-protein interactions (refs. 5-8 and Samanta, M. P. and Liang, S., unpublished data), and protein complexes(9,10). Here we propose the assignment of proteins to functional classes on the basis of their network of physical interactions as determined by minimizing the number of protein interactions among different functional categories. Function assignment is proteome-wide and is determined by the global connectivity pattern of the protein network. The approach results in multiple functional assignments, a consequence of the existence of multiple equivalent solutions. We apply the method to analyze the yeast Saccharomyces cerevisiae protein-protein interaction network(5). The robustness of the approach is tested in a system containing a high percentage of unclassified proteins and also in cases of deletion and insertion of specific protein interactions.