A SARS-CoV-2-Human Protein-Protein Interaction Map Reveals Drug Targets and Potential Drug-Repurposing
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BiBTeXAn outbreak of the novel coronavirus SARS-CoV-2, the causative agent of COVID-19 respiratory disease, has infected over 290,000 people since the end of 2019, killed over 12,000, and caused worldwide social and economic disruption1,2. There are currently no antiviral drugs with proven efficacy nor are there vaccines for its prevention. Unfortunately, the scientific community has little knowledge of the molecular details of SARS-CoV-2 infection. To illuminate this, we cloned, tagged and expressed 26 of the 29 viral proteins in human cells and identified the human proteins physically associated with each using affinity-purification mass spectrometry (AP-MS), which identified 332 high confidence SARS-CoV-2-human protein-protein interactions (PPIs). Among these, we identify 67 druggable human proteins or host factors targeted by 69 existing FDA-approved drugs, drugs in clinical trials and/or preclinical compounds, that we are currently evaluating for efficacy in live SARS-CoV-2 infection assays. The identification of host dependency factors mediating virus infection may provide key insights into effective molecular targets for developing broadly acting antiviral therapeutics against SARS-CoV-2 and other deadly coronavirus strains.
SEEK ID: https://fairdomhub.org/publications/462
DOI: 10.1101/2020.03.22.002386
Projects: COVID-19 Disease Map
Publication type: Unpublished
Citation: biorxiv;2020.03.22.002386v1,[Preprint]
Date Published: 22nd Mar 2020
Registered Mode: by DOI
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Created: 3rd Apr 2020 at 17:28
Last updated: 8th Dec 2022 at 17:26
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Projects: FAIRDOM, Early Metabolic Injury (LiSyM-EMI - Pillar I), Chronic Liver Disease Progression (LiSyM-DP - Pillar II), Regeneration and Repair in Acute-on-Chronic Liver Failure (LiSyM-ACLF - Pillar III), LiSyM Core Infrastructure and Management (LiSyM-PD), Liver Function Diagnostics (LiSyM-LiFuDi - Pillar IV), Model Guided Pharmacotherapy In Chronic Liver Disease (LiSyM-MGP), Multi-Scale Models for Personalized Liver Function Tests (LiSyM-MM-PLF), The Hedgehog Signalling Pathway (LiSyM-JGMMS), Molecular Steatosis - Imaging & Modeling (LiSyM-MSIM), Kinetics on the move - Workshop 2016, Example use cases, FAIRDOM user meeting, MS_DILI, COMBINE Multicellular Modelling, FAIRDOM & LiSyM & de.NBI Data Structuring Training, EnzymeML, GMDS Project Group "FAIRe Dateninfrastrukturen für die Biomedizinische Informatik", FAIRDOM Community Workers, COVID-19 Disease Map, COVID-19 related studies and tools in Germany, nfdi4health - German National Research Data Infrastructure for Personal Health Data, ModeleXchange initiative, SDBV/HITS, EDITH (Ecosystem Digital Twins in Health) test project
Institutions: Heidelberg Institute for Theoretical Studies (HITS gGmbH)
https://orcid.org/0000-0002-8683-7084
Data management and standardization expert for systems biology and systems medicine, responsible for the data management user requirements and user contacts within the German LiSyM network (Liver Systems Medicine: http://lisym.org/) and associated to the FAIRDOM team. Involved in different standardization initiatives and committees, i.e. COMBINE (http://co.mbine.org), ISO/TC 276 Biotechnology (https://www.iso.org/committee/4514241.html), European COST action CHARME (http://www.cost-charme.eu) and ...
The Disease Maps Project is designed as a large-scale community effort. It is a network of groups that work together in order to better understand disease mechanisms. The project exchanges best practices, share information, develop tools to make it easier for all the involved groups to achieve their goals.
Projects: COVID-19 Disease Map
Web page: https://disease-maps.org
Here we share resources and best practices to develop a disease map for COVID-19. The project is progressing as a broad community-driven effort. We aim to establish a knowledge repository on virus-host interaction mechanisms specific to the SARS-CoV-2. The COVID-19 Disease Map is an assembly of molecular interaction diagrams established based on literature evidence.
Programme: Disease Maps
Public web page: http://doi.org/10.17881/covid19-disease-map
