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PXD035805 is an original dataset announced via ProteomeXchange.

Dataset Summary
TitleA comprehensive SARS-CoV-2-human protein-protein interactome network that can identify pathobiology and host-targeting therapies for COVID-19
DescriptionPhysical interactions between viral and host proteins are responsible for almost all aspects of the viral life cycle and the host’s immune response. Studying viral-host protein-protein interactions is thus crucial for identifying strategies for treatment and prevention of viral infection. Here, we use high-throughput yeast two-hybrid and affinity purification followed by mass spectrometry to generate a comprehensive SARS-CoV-2-human protein-protein interactome network consisting of both binary and co-complex interactions. We report a total of 739 high-confidence interactions, showing the highest overlap of interaction partners among published datasets as well as the highest overlap with genes differentially expressed in samples (such as upper airway and bronchial epithelial cells) from patients with SARS-CoV-2 infection. Showcasing the utility of our network, we describe a novel interaction between the viral accessory protein ORF3a and the host zinc finger transcription factor ZNF579 to illustrate a SARS-CoV-2 factor mediating a direct impact on host transcription. Leveraging our interactome, we performed network-based drug screens for over 2,900 FDA-approved/investigational drugs and obtained a curated list of 23 drugs that had significant network proximities to SARS-CoV-2 host factors, one of which, carvedilol, showed promising antiviral properties. We performed electronic health record-based validation using two independent large-scale, longitudinal COVID-19 patient databases and found that carvedilol usage was associated with a significantly lowered probability (17%-20%, P < 0.001) of obtaining a SARS-CoV-2 positive test after adjusting various confounding factors. Carvedilol additionally showed anti-viral activity against SARS-CoV-2 in a human lung epithelial cell line [(half maximal effective concentration (EC 50 ) value of 4.1 µM]), suggesting a mechanism for its beneficial effect in COVID-19. Our study demonstrates the value of large-scale network systems biology approaches for extracting biological insight from complex biological processes.
ReviewLevelPeer-reviewed dataset
DatasetOriginOriginal dataset
RepositorySupportUnsupported dataset by repository
SpeciesList scientific name: Homo sapiens (Human); NCBI TaxID: 9606; scientific name: Severe acute respiratory syndrome coronavirus 2; NCBI TaxID: 2697049;
ModificationListTMT6plex-126 reporter+balance reagent acylated residue
InstrumentOrbitrap Fusion Lumos
Dataset History
RevisionDatetimeStatusChangeLog Entry
02022-08-04 07:57:16ID requested
12023-03-10 23:45:38announced
Publication List
Zhou Y, Liu Y, Gupta S, Paramo MI, Hou Y, Mao C, Luo Y, Judd J, Wierbowski S, Bertolotti M, Nerkar M, Jehi L, Drayman N, Nicolaescu V, Gula H, Tay S, Randall G, Wang P, Lis JT, Feschotte C, Erzurum SC, Cheng F, Yu H, A comprehensive SARS-CoV-2-human protein-protein interactome reveals COVID-19 pathobiology and potential host therapeutic targets. Nat Biotechnol, 41(1):128-139(2023) [pubmed]
Keyword List
ProteomeXchange project tag: Sars-cov-2, Covid-19
submitter keyword: Y2H,SARS-CoV-2, TMT, Human, IP-MS, virus pathobiology
Contact List
contact affiliationWeill Institute for Cell and Molecular Biology, Department of Computational Biology, Cornell University
contact emailhaiyuan.yu@cornell.edu
lab head
contact affiliationCornell University
contact emailsg2369@cornell.edu
dataset submitter
Full Dataset Link List
Dataset FTP location
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PRIDE project URI
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