Bauch Angela, Superti-Furga Giulio
CeMM, Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.
Immunol Rev. 2006 Apr;210:187-207. doi: 10.1111/j.0105-2896.2006.00369.x.
Systematic deciphering of protein-protein interactions has the potential to generate comprehensive and instructive signaling networks and to fuel new therapeutic and diagnostic strategies. Here, we describe how recent advances in high-throughput proteomic technologies, involving biochemical purification methods and mass spectrometry analysis, can be applied systematically to the characterization of protein complexes and the computation of molecular networks. The networks obtained form the basis for further functional analyses, such as knockdown by RNA interference, ultimately leading to the identification of nodes that represent candidate targets for pharmacological exploitation. No individual experimental approach can accurately elucidate all critical modulatory components and biological aspects of a signaling network. Such functionally annotated protein-protein interaction networks, however, represent an ideal platform for the integration of additional datasets. By providing links between molecules, they also provide links to all previous observations associated with these molecules, be they of genetic, pharmacological, or other origin. As exemplified here by the analysis of the tumor necrosis factor (TNF)-alpha/nuclear factor-kappaB (NF-kappaB) signaling pathway, the approach is applicable to any mammalian cellular signaling pathway in the immune system.
对蛋白质-蛋白质相互作用进行系统解密,有可能生成全面且具指导意义的信号网络,并推动新的治疗和诊断策略的发展。在此,我们描述了高通量蛋白质组学技术的最新进展,包括生化纯化方法和质谱分析,如何能够系统地应用于蛋白质复合物的表征以及分子网络的计算。所获得的网络构成了进一步功能分析的基础,例如通过RNA干扰进行基因敲除,最终导致识别出代表药物开发候选靶点的节点。没有任何一种单独的实验方法能够准确阐明信号网络的所有关键调节成分和生物学方面。然而,这种功能注释的蛋白质-蛋白质相互作用网络代表了整合其他数据集的理想平台。通过提供分子之间的联系,它们还提供了与这些分子相关的所有先前观察结果的联系,无论这些观察结果是遗传、药理学还是其他来源的。如此处通过对肿瘤坏死因子(TNF)-α/核因子-κB(NF-κB)信号通路的分析所例证的那样,该方法适用于免疫系统中的任何哺乳动物细胞信号通路。