SARS-CoV-2相互作用组的内在无序蛋白质和液-液相分离。

IF 3 3区 生物学 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY
Journal of cellular biochemistry Pub Date : 2024-12-01 Epub Date: 2023-11-22 DOI:10.1002/jcb.30502
Lazar M Vasović, Gordana M Pavlović-Lažetić, Jovana J Kovačević, Miloš V Beljanski, Vladimir N Uversky
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引用次数: 0

摘要

本文讨论了SARS-CoV-2蛋白质组中膜蛋白、非结构蛋白和完整蛋白质组中蛋白质的特性及其相互作用组中的关系。根据几种测量方法,选择蛋白质的无序性,液-液相分离概率和相互作用网络中的蛋白质节点度作为感兴趣的特征。此外,将病毒相互作用组与人肺组织的相互作用组结合,以检验由此产生的病毒-宿主相互作用组中的新连接是否与蛋白质紊乱有关。相关分析表明,感兴趣的原始特征之间没有明确的关系,而蛋白质紊乱与其邻近平均紊乱之间存在正相关关系。也有迹象表明,高度连接的病毒中心通常比连接较少的蛋白质更有序。这与以往对真核相互作用组的类似研究形成了对比,可能为病毒相互作用组的研究提出了新的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intrinsically disordered proteins and liquid-liquid phase separation in SARS-CoV-2 interactomes.

This paper discusses the properties of proteins and their relations in the interactomes of the selected subsets of SARS-CoV-2 proteome-the membrane protein, nonstructural proteins, and, finally, full proteome. Protein disorder according to several measures, liquid-liquid phase separation probabilities, and protein node degrees in the interaction networks were singled out as the features of interest. Additionally, viral interactomes were combined with the interactome of human lung tissue so as to examine if the new connections in the resulting viral-host interactome are linked to protein disorder. Correlation analysis shows that there is no clear relationship between raw features of interest, whereas there is a positive correlation between the protein disorder and its neighborhood mean disorder. There are also indications that highly connected viral hubs tend to be on average more ordered than proteins with a small number of connections. This is in contrast to previous similar studies conducted on eukaryotic interactomes and possibly raises new questions in research on viral interactomes.

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来源期刊
Journal of cellular biochemistry
Journal of cellular biochemistry 生物-生化与分子生物学
CiteScore
9.90
自引率
0.00%
发文量
164
审稿时长
1 months
期刊介绍: The Journal of Cellular Biochemistry publishes descriptions of original research in which complex cellular, pathogenic, clinical, or animal model systems are studied by biochemical, molecular, genetic, epigenetic or quantitative ultrastructural approaches. Submission of papers reporting genomic, proteomic, bioinformatics and systems biology approaches to identify and characterize parameters of biological control in a cellular context are encouraged. The areas covered include, but are not restricted to, conditions, agents, regulatory networks, or differentiation states that influence structure, cell cycle & growth control, structure-function relationships.
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