Suppr超能文献

蛋白质-蛋白质相互作用网络作为生物发现的挖掘者。

Protein-protein interaction networks as miners of biological discovery.

机构信息

Department of Biological Sciences, Columbia University, New York, New York, USA.

Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA.

出版信息

Proteomics. 2022 Aug;22(15-16):e2100190. doi: 10.1002/pmic.202100190. Epub 2022 May 24.

Abstract

Protein-protein interactions (PPIs) form the basis of a myriad of biological pathways and mechanism, such as the formation of protein complexes or the components of signaling cascades. Here, we reviewed experimental methods for identifying PPI pairs, including yeast two-hybrid (Y2H), mass spectrometry (MS), co-localization, and co-immunoprecipitation. Furthermore, a range of computational methods leveraging biochemical properties, evolution history, protein structures and more have enabled identification of additional PPIs. Given the wealth of known PPIs, we reviewed important network methods to construct and analyze networks of PPIs. These methods aid biological discovery through identifying hub genes and dynamic changes in the network, and have been thoroughly applied in various fields of biological research. Lastly, we discussed the challenges and future direction of research utilizing the power of PPI networks.

摘要

蛋白质-蛋白质相互作用 (PPIs) 构成了许多生物途径和机制的基础,例如蛋白质复合物的形成或信号级联的组成部分。在这里,我们回顾了用于识别 PPI 对的实验方法,包括酵母双杂交 (Y2H)、质谱 (MS)、共定位和共免疫沉淀。此外,一系列利用生化特性、进化历史、蛋白质结构等的计算方法已经能够识别其他 PPI。鉴于已知 PPI 的丰富性,我们回顾了构建和分析 PPI 网络的重要网络方法。这些方法通过识别枢纽基因和网络中的动态变化来帮助进行生物发现,并已在生物学研究的各个领域得到了广泛应用。最后,我们讨论了利用 PPI 网络的力量进行研究的挑战和未来方向。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验