A SARS-CoV-2 Protein Interaction Map Reveals Targets for Drug-Repurposing

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

SUMMARY

The novel coronavirus SARS-CoV-2, the causative agent of COVID-19 respiratory disease, has infected over 2.3 million people, killed over 160,000, and caused worldwide social and economic disruption ^{1,
2}. There are currently no antiviral drugs with proven clinical efficacy, nor are there vaccines for its prevention, and these efforts are hampered by limited knowledge of the molecular details of SARS-CoV-2 infection. To address this, we cloned, tagged and expressed 26 of the 29 SARS-CoV-2 proteins in human cells and identified the human proteins physically associated with each using affinity-purification mass spectrometry (AP-MS), identifying 332 high-confidence SARS-CoV-2-human protein-protein interactions (PPIs). Among these, we identify 66 druggable human proteins or host factors targeted by 69 compounds (29 FDA-approved drugs, 12 drugs in clinical trials, and 28 preclinical compounds). Screening a subset of these in multiple viral assays identified two sets of pharmacological agents that displayed antiviral activity: inhibitors of mRNA translation and predicted regulators of the Sigma1 and Sigma2 receptors. Further studies of these host factor targeting agents, including their combination with drugs that directly target viral enzymes, could lead to a therapeutic regimen to treat COVID-19.

Related collections

Most cited references 81

Record: found
Abstract: found
Article: not found

Cytoscape: a software environment for integrated models of biomolecular interaction networks.

Paul Shannon, Andrew Markiel, Owen Ozier … (2003)

Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.

0 comments Cited 11004 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

SARS-CoV-2 Cell Entry Depends on ACE2 and TMPRSS2 and Is Blocked by a Clinically Proven Protease Inhibitor

Markus Hoffmann, Hannah Kleine-Weber, Simon Schroeder … (2020)

Summary The recent emergence of the novel, pathogenic SARS-coronavirus 2 (SARS-CoV-2) in China and its rapid national and international spread pose a global health emergency. Cell entry of coronaviruses depends on binding of the viral spike (S) proteins to cellular receptors and on S protein priming by host cell proteases. Unravelling which cellular factors are used by SARS-CoV-2 for entry might provide insights into viral transmission and reveal therapeutic targets. Here, we demonstrate that SARS-CoV-2 uses the SARS-CoV receptor ACE2 for entry and the serine protease TMPRSS2 for S protein priming. A TMPRSS2 inhibitor approved for clinical use blocked entry and might constitute a treatment option. Finally, we show that the sera from convalescent SARS patients cross-neutralized SARS-2-S-driven entry. Our results reveal important commonalities between SARS-CoV-2 and SARS-CoV infection and identify a potential target for antiviral intervention.

0 comments Cited 9648 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

A new coronavirus associated with human respiratory disease in China

Fan Wu, Su Zhao, Bin Yu … (2020)

Emerging infectious diseases, such as severe acute respiratory syndrome (SARS) and Zika virus disease, present a major threat to public health 1–3 . Despite intense research efforts, how, when and where new diseases appear are still a source of considerable uncertainty. A severe respiratory disease was recently reported in Wuhan, Hubei province, China. As of 25 January 2020, at least 1,975 cases had been reported since the first patient was hospitalized on 12 December 2019. Epidemiological investigations have suggested that the outbreak was associated with a seafood market in Wuhan. Here we study a single patient who was a worker at the market and who was admitted to the Central Hospital of Wuhan on 26 December 2019 while experiencing a severe respiratory syndrome that included fever, dizziness and a cough. Metagenomic RNA sequencing 4 of a sample of bronchoalveolar lavage fluid from the patient identified a new RNA virus strain from the family Coronaviridae, which is designated here ‘WH-Human 1’ coronavirus (and has also been referred to as ‘2019-nCoV’). Phylogenetic analysis of the complete viral genome (29,903 nucleotides) revealed that the virus was most closely related (89.1% nucleotide similarity) to a group of SARS-like coronaviruses (genus Betacoronavirus, subgenus Sarbecovirus) that had previously been found in bats in China 5 . This outbreak highlights the ongoing ability of viral spill-over from animals to cause severe disease in humans.

0 comments Cited 5279 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Journal

Journal ID (nlm-journal-id): 0410462

Journal ID (pubmed-jr-id): 6011

Journal ID (nlm-ta): Nature

Journal ID (iso-abbrev): Nature

Title: Nature

ISSN (Print): 0028-0836

ISSN (Electronic): 1476-4687

Publication date Nihms-submitted: 14 May 2020

Publication date (Electronic): 30 April 2020

Publication date (Print): July 2020

Publication date PMC-release: 30 October 2020

Volume: 583

Issue: 7816

Pages: 459-468

Affiliations

[1 ]QBI COVID-19 Research Group (QCRG), San Francisco, CA, 94158, USA

[2 ]Quantitative Biosciences Institute (QBI), University of California San Francisco, San Francisco, CA, 94158, USA

[3 ]J. David Gladstone Institutes, San Francisco, CA 94158, USA

[4 ]Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, CA, 94158, USA

[5 ]Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA

[6 ]Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA

[7 ]Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, 48109, USA

[8 ]Viral Populations and Pathogenesis Unit, CNRS UMR 3569, Institut Pasteur, 75724 Paris cedex 15, France

[9 ]Department of Pharmaceutical Chemistry, University of California, San Francisco, CA 94158, USA

[10 ]Virus and Immunity Unit, Institut Pasteur, 75724 Paris Cedex 15, France

[11 ]Howard Hughes Medical Institute

[12 ]European Molecular Biology Laboratory (EMBL), European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK

[13 ]Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94158, USA

[14 ]The UC Berkeley-UCSF Graduate Program in Bioengineering, University of California San Francisco, San Francisco, CA, USA

[15 ]Center for Computational Biology and Bioinformatics, Department of Medicine, University of California San Diego, CA 92093, USA

[16 ]Department of Cell and Tissue Biology, University of California, San Francisco, CA 94143, USA

[17 ]Department of Pharmacology, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina 27599-7365, USA

[18 ]Biophysics Graduate Program, University of California, San Francisco

[19 ]Department of Biochemistry and Biophysics, University of California San Francisco, San Francisco, CA 94158, USA

[20 ]Zoic Labs, Culver City, CA, 90232, USA.

[21 ]Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA, 94158, USA

[22 ]Department of Urology, University of California, San Francisco, San Francisco, CA 94143, USA

[23 ]Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA, 94158, USA

[24 ]Division of Basic Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA

[25 ]Medical Scientist Training Program, University of California, San Francisco, CA 94143, USA

[26 ]George William Hooper Foundation, Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA 94143, USA

[27 ]Department of Medicine, University of California San Francisco, San Francisco, CA, USA

[28 ]Division of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, WA 98103, USA

[29 ]Department of Psychiatry, University of California San Francisco, San Francisco, CA, 94158, USA

[30 ]Buck Institute for Research on Aging, Novato, CA, 94945

[31 ]Direction Scientifique, Institut Pasteur, 75724 Paris cedex 15, France

[32 ]Division of Genetics, Department of Medicine, University of California San Diego, San Diego, CA 92093, USA

[33 ]Department of Medicine, Division of Infectious Diseases, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA

[34 ]The Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA

Author notes

AUTHOR CONTRIBUTIONS

Study conception by NJK, DEG. Genome annotation by DEG, GMJ, and BJP. Molecular cloning by DEG, GMJ, JZG. Cell culture, affinity purifications and peptide digestion by GMJ and JX. Mass spectrometer operation and peptide search by DLS, and proteomics data processing by MeB, YZ, BJP, DLS and RH. Network annotation led by MeB with support from DEG, NJK, RMK and the appendix literature review team. Interactome meta analysis by PB, MeB, HB, MC, ZZCN, IB-H, DM, CH-A, TP, SBR, MCO, YC, JCJC, DJB, SK. Drug selection and annotation by MJO, TAT, SP, YS, ZZ, WS, ITK, JEM, JSC, KL, SAD, JL, LC, SV, JL-L, YiL, X-PH, YoL, PPS, NAW, DK, H-YW, KMS, BKS. Structural modeling by CJPM, KBP, SJG, DJS, RR, XL, SAW, MaB, FSU, TK. Live SARS-CoV-2 virus assays led by KMW (MSSM) and VR (Pasteur) with support from FR, TV, AMK, LM, EM, CK, NSS, DT, DS, SJF, MH. Analysis of SARS-CoV-2 genomic diversity by MalS. Analysis of human gene positive selection by JMY, BM, HSM. Nsp5 cleavage prediction and analysis by MaB and CC with support from DEG. Figure preparation by DEG, MeB, KO, KMW, MJO, DLS TAT, RH, RMK, MK, HB, YZ, ZZ, CJPM, TP, SAW, MaB, MalS, FSU, NAW, DGF, SNF, JDG, DR, TK, PB, KMS, BKS, NJK. Appendix assembled by RMK with support from literature review team: KO, RH, RMK, ALR, BT, HF, JB, KH, MM, MK, PH, JMF, MaE, MarS, MJB, MC, MJM, QL, CJPM, TP, XL, LC, SV, JL-L, YiL, MaB, RT, DAC, JH, JLR, UR, AdS, JN, NJ, SM, SNF. Manuscript prepared by DEG, MeB, KO, MJO, DLS, TAT, RH, RMK, MaE, MarS, MJB, PB, KMS, BKS, NJK. Work supervised by RMS, ADF, OSR, KAV, DAA, MO, MiE, NJ, MVN, EV, AA, OS, CD’E, SM, MJ, HSM, DGF, TI, CSC, SNF, JSF, JDG, AnS, BLR, DR, JT, TK, PB, MV, AG-S, KMS, BKS, NJK.

[† ] Correspondence and requests for materials should be addressed to nevan.krogan@ 123456ucsf.edu

Article

Manuscript ID: NIHMS1587111

DOI: 10.1038/s41586-020-2286-9

PMC ID: 7431030

PubMed ID: 32353859

SO-VID: 9e3a182c-8fb9-422f-8ad2-2d06f2a7b974

License:

Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms

A SARS-CoV-2 Protein Interaction Map Reveals Targets for Drug-Repurposing

Read this article at

SUMMARY

Related collections

Novel Coronavirus Disease COVID-19

Most cited references 81

Cytoscape: a software environment for integrated models of biomolecular interaction networks.

SARS-CoV-2 Cell Entry Depends on ACE2 and TMPRSS2 and Is Blocked by a Clinically Proven Protease Inhibitor

A new coronavirus associated with human respiratory disease in China

Author and article information

Journal

Affiliations

Author notes

Article

History

Categories

Comments

Comment on this article

Similar content 278

Cited by 2,076

Most referenced authors 2,923