Advanced Research Centers, Keio University, Yokohama, Japan.
PLoS One. 2010 Feb 24;5(2):e9289. doi: 10.1371/journal.pone.0009289.
Large-scale data sets of protein-protein interactions (PPIs) are a valuable resource for mapping and analysis of the topological and dynamic features of interactome networks. The currently available large-scale PPI data sets only contain information on interaction partners. The data presented in this study also include the sequences involved in the interactions (i.e., the interacting regions, IRs) suggested to correspond to functional and structural domains. Here we present the first large-scale IR data set obtained using mRNA display for 50 human transcription factors (TFs), including 12 transcription-related proteins. The core data set (966 IRs; 943 PPIs) displays a verification rate of 70%. Analysis of the IR data set revealed the existence of IRs that interact with multiple partners. Furthermore, these IRs were preferentially associated with intrinsic disorder. This finding supports the hypothesis that intrinsically disordered regions play a major role in the dynamics and diversity of TF networks through their ability to structurally adapt to and bind with multiple partners. Accordingly, this domain-based interaction resource represents an important step in refining protein interactions and networks at the domain level and in associating network analysis with biological structure and function.
蛋白质-蛋白质相互作用（PPIs）的大规模数据集是映射和分析互作网络拓扑和动态特征的有价值资源。目前可用的大规模 PPI 数据集仅包含关于相互作用伙伴的信息。本研究中提供的数据还包括涉及相互作用的序列（即，交互区域，IRs），这些序列被认为与功能和结构域相对应。在这里，我们展示了使用 mRNA 展示技术获得的第一个涉及 50 个人类转录因子（TFs）的大规模 IR 数据集，其中包括 12 种与转录相关的蛋白质。核心数据集（966 个 IRs；943 个 PPIs）显示出 70%的验证率。对 IR 数据集的分析表明，存在与多个伙伴相互作用的 IR。此外，这些 IR 更倾向于与内在无序相关。这一发现支持了这样一种假设，即内在无序区域通过其与多个伙伴结构上适应和结合的能力，在 TF 网络的动态和多样性中发挥主要作用。因此，这个基于结构域的相互作用资源代表了在结构域水平上细化蛋白质相互作用和网络以及将网络分析与生物结构和功能联系起来的重要步骤。
