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分析亲和纯化相关蛋白质组学数据,以研究细胞中的蛋白质-蛋白质相互作用网络。

Analysis of affinity purification-related proteomic data for studying protein-protein interaction networks in cells.

机构信息

Department of Developmental and Cell Biology, University of California, Irvine, Irvine, CA 92697, USA.

出版信息

Brief Bioinform. 2023 Mar 19;24(2). doi: 10.1093/bib/bbad010.

Abstract

During intracellular signal transduction, protein-protein interactions (PPIs) facilitate protein complex assembly to regulate protein localization and function, which are critical for numerous cellular events. Over the years, multiple techniques have been developed to characterize PPIs to elucidate roles and regulatory mechanisms of proteins. Among them, the mass spectrometry (MS)-based interactome analysis has been increasing in popularity due to its unbiased and informative manner towards understanding PPI networks. However, with MS instrumentation advancing and yielding more data than ever, the analysis of a large amount of PPI-associated proteomic data to reveal bona fide interacting proteins become challenging. Here, we review the methods and bioinformatic resources that are commonly used in analyzing large interactome-related proteomic data and propose a simple guideline for identifying novel interacting proteins for biological research.

摘要

在细胞内信号转导过程中,蛋白质-蛋白质相互作用(PPIs)促进蛋白质复合物的组装,从而调节蛋白质的定位和功能,这对许多细胞事件至关重要。多年来,已经开发出多种技术来描述蛋白质-蛋白质相互作用,以阐明蛋白质的作用和调节机制。其中,基于质谱(MS)的相互作用组分析由于其对理解蛋白质相互作用网络的无偏和信息丰富的方式而越来越受欢迎。然而,随着 MS 仪器的不断发展,产生的数据比以往任何时候都多,分析大量与蛋白质相互作用相关的蛋白质组学数据以揭示真正的相互作用蛋白变得具有挑战性。在这里,我们综述了常用于分析大量相互作用组相关蛋白质组学数据的方法和生物信息学资源,并为生物研究中识别新的相互作用蛋白提出了一个简单的指南。

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