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全面的 SARS-CoV-2-人类蛋白质-蛋白质相互作用组揭示了 COVID-19 的发病机制和潜在的宿主治疗靶点。

A comprehensive SARS-CoV-2-human protein-protein interactome reveals COVID-19 pathobiology and potential host therapeutic targets.

机构信息

Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA.

Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, NY, USA.

出版信息

Nat Biotechnol. 2023 Jan;41(1):128-139. doi: 10.1038/s41587-022-01474-0. Epub 2022 Oct 10.

Abstract

Studying viral-host protein-protein interactions can facilitate the discovery of therapies for viral infection. We use high-throughput yeast two-hybrid experiments and mass spectrometry to generate a comprehensive SARS-CoV-2-human protein-protein interactome network consisting of 739 high-confidence binary and co-complex interactions, validating 218 known SARS-CoV-2 host factors and revealing 361 novel ones. Our results show the highest overlap of interaction partners between published datasets and of genes differentially expressed in samples from COVID-19 patients. We identify an interaction between the viral protein ORF3a and the human transcription factor ZNF579, illustrating a direct viral impact on host transcription. We perform network-based screens of >2,900 FDA-approved or investigational drugs and identify 23 with significant network proximity to SARS-CoV-2 host factors. One of these drugs, carvedilol, shows clinical benefits for COVID-19 patients in an electronic health records analysis and antiviral properties in a human lung cell line infected with SARS-CoV-2. Our study demonstrates the value of network systems biology to understand human-virus interactions and provides hits for further research on COVID-19 therapeutics.

摘要

研究病毒-宿主蛋白-蛋白相互作用可以促进发现治疗病毒感染的方法。我们使用高通量酵母双杂交实验和质谱技术,生成了一个由 739 个高可信度二元和共复合物相互作用组成的全面的 SARS-CoV-2-人类蛋白质相互作用网络,验证了 218 个已知的 SARS-CoV-2 宿主因子,并揭示了 361 个新的宿主因子。我们的结果显示,与已发表的数据集相比,我们的交互作用伙伴的重叠率最高,与 COVID-19 患者样本中差异表达的基因的重叠率也最高。我们发现了病毒蛋白 ORF3a 与人类转录因子 ZNF579 之间的相互作用,这表明病毒对宿主转录有直接影响。我们对超过 2900 种 FDA 批准或正在研究的药物进行了基于网络的筛选,发现其中 23 种与 SARS-CoV-2 宿主因子具有显著的网络接近性。这些药物中的一种,卡维地洛,在电子健康记录分析中对 COVID-19 患者具有临床益处,并在感染 SARS-CoV-2 的人肺细胞系中具有抗病毒特性。我们的研究表明网络系统生物学在理解人类-病毒相互作用方面的价值,并为 COVID-19 治疗的进一步研究提供了线索。

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