Predicting and analyzing protein interaction networks

描述（由申请人提供）：已经在实验中确定了几种生物的大规模蛋白质相互作用网络，这些网络的计算分析为揭示蛋白质功能和途径提供了新的机会。与此同时，尽管高通量技术有所改进，但在不久的将来，将它们应用于所有测序基因组仍然是不可行的。因此，对于绝大多数已测序的基因组，只有一小部分已知的蛋白质相互作用已经被实验确定，而新的计算方法为构建大型，高置信度的相互作用图提供了一种有前途的替代方法。本研究的长远目标是通过开发分析和预测蛋白质相互作用图的互补问题的算法，为理解蛋白质相互作用建立一个全面的研究计划。我们的具体目标是：(1)开发算法，利用全基因组蛋白质相互作用图的拓扑结构和蛋白质功能之间的关系，以便对蛋白质的生物学过程做出新的预测。(2)建立一个系统，使用“模板”来询问蛋白质相互作用网络，指定共同的相互作用模式或途径，以帮助发现新的实例。(3)开发一种通用的结构生物信息学方法来利用特定蛋白质相互作用界面的特性，并应用该方法来帮助预测基因组尺度上的Cys2HiS2锌指蛋白- dna相互作用。综上所述，我们希望所提出的工具将显著推进最先进的计算方法，用于在细胞相互作用、途径和网络的背景下表征蛋白质。所有的软件和预测都将通过互联网公开发布。

DESCRIPTION (provided by applicant): Large-scale protein interaction networks have been determined experimentally for several organisms, and computational analysis of these networks provides new opportunities to uncover protein functions and pathways. At the same time, despite improvements in high-throughput technologies, it is still not feasible in the near future to apply them to all sequenced genomes. Thus, for the vast majority of sequenced genomes, only a small fraction of known protein interactions have been experimentally determined, and novel computational approaches provide a promising, alternative means for building large, high- confidence interaction maps. The broad, long-term goal of this research is to build a comprehensive research program for understanding protein interactions, by developing algorithms for the complementary problems of analyzing and predicting protein interaction maps. Our specific aims are: (1) To develop algorithms that exploit the topology of whole-genome protein interaction maps and the relationships between protein functions, in order to make novel predictions about a protein's biological process. (2) To build a system for interrogating protein interaction networks using "templates" specifying common patterns of interactions or pathways, in order to help uncover novel instances. (3) To develop a general structural bioinformatics approach for leveraging properties of specific protein interaction interfaces, and to apply this approach in order to help predict Cys2HiS2 zinc finger protein-DNA interactions at the genomic scale. Taken together, we hope that the proposed tools will significantly advance the state-of-the-art in computational approaches for characterizing proteins within the context of their cellular interactions, pathways and networks. All software and predictions will be made publicly available via the internet.