Ramadan Emad, Ward Michael, Guo Xin, Durkin Sarah S, Sawyer Adam, Vilela Marcelo, Osgood Christopher, Pothen Alex, Semmes Oliver J
George L, Wright Center for Biomedical Proteomics, Eastern Virginia Medical School, Norfolk, VA, USA.
Retrovirology. 2008 Oct 15;5:92. doi: 10.1186/1742-4690-5-92.
We have initiated an effort to exhaustively map interactions between HTLV-1 Tax and host cellular proteins. The resulting Tax interactome will have significant utility toward defining new and understanding known activities of this important viral protein. In addition, the completion of a full Tax interactome will also help shed light upon the functional consequences of these myriad Tax activities. The physical mapping process involved the affinity isolation of Tax complexes followed by sequence identification using tandem mass spectrometry. To date we have mapped 250 cellular components within this interactome. Here we present our approach to prioritizing these interactions via an in silico culling process.
We first constructed an in silico Tax interactome comprised of 46 literature-confirmed protein-protein interactions. This number was then reduced to four Tax-interactions suspected to play a role in DNA damage response (Rad51, TOP1, Chk2, 53BP1). The first-neighbor and second-neighbor interactions of these four proteins were assembled from available human protein interaction databases. Through an analysis of betweenness and closeness centrality measures, and numbers of interactions, we ranked proteins in the first neighborhood. When this rank list was compared to the list of physical Tax-binding proteins, DNA-PK was the highest ranked protein common to both lists. An overlapping clustering of the Tax-specific second-neighborhood protein network showed DNA-PK to be one of three bridge proteins that link multiple clusters in the DNA damage response network.
The interaction of Tax with DNA-PK represents an important biological paradigm as suggested via consensus findings in vivo and in silico. We present this methodology as an approach to discovery and as a means of validating components of a consensus Tax interactome.
我们已着手全面绘制人类嗜T淋巴细胞病毒1型(HTLV-1)Tax蛋白与宿主细胞蛋白之间的相互作用图谱。由此产生的Tax相互作用组对于定义这种重要病毒蛋白的新活性以及理解其已知活性具有重要作用。此外,完整的Tax相互作用组的完成也将有助于揭示这些众多Tax活性的功能后果。物理图谱绘制过程包括对Tax复合物进行亲和分离,随后使用串联质谱进行序列鉴定。到目前为止,我们已在这个相互作用组中绘制了250个细胞成分。在此,我们展示通过计算机筛选过程对这些相互作用进行优先级排序的方法。
我们首先构建了一个由46种文献证实的蛋白质-蛋白质相互作用组成的计算机Tax相互作用组。然后将这个数量减少到4种怀疑在DNA损伤反应中起作用的Tax相互作用(Rad51、TOP1、Chk2、53BP1)。这四种蛋白质的第一邻域和第二邻域相互作用是从现有的人类蛋白质相互作用数据库中收集的。通过对介数中心性和接近中心性度量以及相互作用数量的分析,我们对第一邻域中的蛋白质进行了排名。当将这个排名列表与物理Tax结合蛋白列表进行比较时,DNA-PK是两个列表中排名最高的共同蛋白。Tax特异性第二邻域蛋白质网络的重叠聚类显示DNA-PK是连接DNA损伤反应网络中多个簇的三种桥梁蛋白之一。
Tax与DNA-PK的相互作用代表了一种重要的生物学模式,这在体内和计算机模拟的共识研究结果中都有所体现。我们将这种方法作为一种发现途径以及验证共识Tax相互作用组成分的手段进行展示。