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Protein interactions study through proximity-labeling.
Expert Review of Proteomics ( IF 3.4 ) Pub Date : 2019-07-18 , DOI: 10.1080/14789450.2019.1638769
Benoît Béganton 1, 2 , Isabelle Solassol 3 , Alain Mangé 1 , Jérôme Solassol 1, 2
Affiliation  

Introduction: The proteome is a dynamic system in which protein-protein interactions play a crucial part in shaping the cell phenotype. However, given the current limitations of available technologies to describe the dynamic nature of these interactions, the identification of protein-protein interactions has long been a major challenge in proteomics. In recent years, the development of BioID and APEX, two proximity-tagging technologies, have opened-up new perspectives and have already started to change our conception of protein-protein interactions, and more generally, of the proteome. With a broad range of application encompassing health, these new technologies are currently setting milestones crucial to understand fine cellular mechanisms.

Area covered: In this article, we describe both the recent and the more conventional available tools to study protein-protein interactions, compare the advantages and the limitations of these techniques, and discuss the recent advancements led by the proximity tagging techniques to refine our conception of the proteome.

Expert opinion: The recent development of proximity labeling techniques emphasizes the growing importance of such technologies to decipher cellular mechanism. Although several challenges still need to be addressed, many fields can benefit from these tools and notably the detection of new therapeutic targets for patient care



中文翻译:

通过邻近标记研究蛋白质相互作用。

简介:蛋白质组是一个动态系统,其中蛋白质与蛋白质之间的相互作用在塑造细胞表型中起着至关重要的作用。然而,鉴于描述这些相互作用的动态性质的现有技术的局限性,蛋白质-蛋白质相互作用的鉴定长期以来一直是蛋白质组学的主要挑战。近年来,两种邻近标签技术BioID和APEX的发展开辟了新的视角,并且已经开始改变我们对蛋白质-蛋白质相互作用的理解,尤其是蛋白质组的相互作用。这些新技术具有广泛的应用范围,涉及健康,目前正在树立里程碑,这对于理解精细细胞机制至关重要。

涵盖的领域:在本文中,我们描述了研究蛋白质间相互作用,比较这些技术的优势和局限性的最新工具和更常规的可用工具,并讨论了由邻近标记技术引领的最新进展以完善我们的概念蛋白质组。

专家意见:邻近标记技术的最新发展强调了此类技术对解密细胞机制的重要性。尽管仍然需要解决几个挑战,但是许多领域都可以从这些工具中受益,尤其是为患者护理检测新的治疗靶标

更新日期:2019-07-18
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