A Drosophila geneome-wide protein interaction map

描述(申请人提供)：相互作用的蛋白质网络调节一系列不同的生物过程。要想更彻底地了解生物系统，关键的一步是对构成每个基因组这些蛋白质网络的所有二元相互作用进行分类。该项目的长期目标是为遗传易驯化的模式生物--黑腹果蝇构建一个全面的高质量蛋白质相互作用图谱。酵母双杂交系统是一种检测生物信息性蛋白质相互作用的成熟技术。在该项目的完成阶段，为14,000个预测的果蝇基因中超过86%的基因构建了酵母双杂交克隆阵列。对这些阵列的初步筛选发现了数以千计的蛋白质相互作用，这对于了解蛋白质和途径功能是非常有价值的。分析还表明，到目前为止，只发现了这项技术可检测到的一小部分相互作用。该项目的第一个目标是通过持续的双杂交筛选来增加蛋白质相互作用数据的覆盖面，特别是在当前相互作用图谱中缺失的蛋白质的情况下；这将至少使现有的相互作用数量翻一番。在第二个目标中，将使用两种不同的检测系统来验证所有检测到的相互作用。使用这些结果和其他标准，每个相互作用都将被分配一个置信度分数，表明它在体内发挥功能作用的可能性。在第三个目标中，将执行共亲和纯化以进一步验证相互作用数据。在目标4中，将直接测试疑似功能相关的一组蛋白质或计算预测相互作用的蛋白质之间的二元相互作用。与随机筛选相比，这种方法可能会为这些蛋白质产生更完整和准确的相互作用数据，而且应该提供数据来帮助验证和进一步增强预测算法。在最终目标中，将克隆现有双杂交阵列中缺失的新预测基因，并将其纳入筛选过程。该项目的所有数据将通过至少两个独立的网络数据库以标准化格式公开提供。综合考虑，该项目的数据将为理解保守蛋白质网络的功能以及模拟复杂的生物过程和疾病提供基础。

DESCRIPTION (provided by applicant): Networks of interacting proteins mediate a diverse range of biological processes. An essential step toward developing a more thorough understanding of biological systems is to catalogue all of the binary interactions that comprise these protein networks for each genome. The long-term objective of this project is to construct a comprehensive high-quality protein interaction map for the genetically tractable model organism, Drosophila melanogaster. A proven technology for detecting biologically informative protein interactions is the yeast two-hybrid system. In a completed phase of this project, yeast two-hybrid clone arrays were constructed for over 86% of the 14,000 predicted Drosophila genes. Initial screening of these arrays detected thousands of protein interactions, which are proving invaluable for understanding protein and pathway function. Analyses have also revealed that only a small fraction of the interactions detectable with this technology have been identified thus far. The first aim of this project is to increase the coverage of protein interaction data by continued two-hybrid screening, particularly with the proteins missing from current interaction maps; this will at least double the existing number of interactions. In the second aim, two different assay systems will be used to verify all detected interactions. Using these results and other criteria, each interaction will be assigned a confidence score indicating the probability that it plays a functional role in vivo. In the third aim, co-affinity purifications will be performed to further validate the interaction data. In Aim 4, binary interactions will be directly tested for groups of proteins suspected of being functionally related or between proteins computationally predicted to interact. Compared to random screening, this approach is likely to produce more complete and accurate interaction data for these proteins, and moreover, should provide data to help validate and further enhance prediction algorithms. In the final aim, newly predicted genes missing from the existing two-hybrid arrays will be cloned and incorporated into the screening process. All data from this project will be publicly available in standardized formats via at least two independent web-based databases. Combined, the data from this project will provide a foundation for understanding the functions of conserved protein networks and for modeling complex biological processes and diseases.