An open index of research

A status.lu publication

Biology & Genetics

A SARS-CoV-2 protein interaction map reveals targets for drug repurposing

David E. Gordon, Gwendolyn M. Jang, Mehdi Bouhaddou · Large multi-institution collaboration (~120 authors); first authors Gordon, Jang, Bouhaddou; senior author Nevan J. Krogan (QCRG/QBI COVID-19 Research Group).

Published 30 April 2020 · Nature · Journal article

Summary

The authors expressed 26 of the 29 SARS-CoV-2 proteins in human cells and used affinity-purification mass spectrometry to map 332 high-confidence virus-human protein-protein interactions. They then identified 69 existing drugs and compounds that target the human proteins in this interactome and tested several for antiviral activity. Two pharmacological classes (mRNA translation inhibitors and Sigma1/Sigma2 receptor regulators) showed antiviral effects, providing candidate therapeutics for repurposing.

Key findings

  • Mapped 332 high-confidence SARS-CoV-2-human protein-protein interactions across 26 viral proteins.
  • Linked the host interactors to 69 existing FDA-approved drugs, clinical-trial compounds, and preclinical molecules.
  • Antiviral testing implicated translation inhibitors and Sigma receptor ligands as promising therapeutic candidates.

Subjects & keywords

Cite this paper

APA

David E. Gordon, Gwendolyn M. Jang, & Mehdi Bouhaddou [Large multi-institution collaboration (~120 authors); first authors Gordon, Jang, Bouhaddou; senior author Nevan J. Krogan (QCRG/QBI COVID-19 Research Group).] (2020). A SARS-CoV-2 protein interaction map reveals targets for drug repurposing. Nature. https://doi.org/10.1038/s41586-020-2286-9

BibTeX
@article{gordon2020sarscov2,
  author    = {David E. Gordon and Gwendolyn M. Jang and Mehdi Bouhaddou and {Large multi-institution collaboration (~120 authors); first authors Gordon, Jang, Bouhaddou; senior author Nevan J. Krogan (QCRG/QBI COVID-19 Research Group).}},
  title     = {A SARS-CoV-2 protein interaction map reveals targets for drug repurposing},
  journal   = {Nature},
  year      = {2020},
  doi       = {10.1038/s41586-020-2286-9},
  url       = {https://doi.org/10.1038/s41586-020-2286-9}
}

Related in Biology & Genetics

Accurate structure prediction of biomolecular interactions with AlphaFold 3

Josh Abramson, Jonas Adler and John M. Jumper

This paper introduced AlphaFold 3, a unified deep learning model that predicts the joint structure of complexes containing proteins, nucleic acids, small-molecule ligands, ions, and modified residues. It replaces much of the prior architecture with a diffusion-based module that directly generates atomic coordinates. The model achieved substantially improved accuracy over specialized tools across many interaction types, including protein-ligand and protein-nucleic acid complexes.

Nature Open access

De novo design of protein structure and function with RFdiffusion

Joseph L. Watson, David Juergens and David Baker

This paper introduced RFdiffusion, a generative diffusion model built on the RoseTTAFold network for de novo protein design. It enables a range of design tasks, including unconditional generation, symmetric oligomer design, functional motif scaffolding, and binder design. Many designs were experimentally validated, with solved structures closely matching the intended models.

Nature Open access

A draft human pangenome reference

Wen-Wei Liao, Mobin Asri and Jana Ebler

The Human Pangenome Reference Consortium presents a first draft human pangenome built from 47 phased, diploid genome assemblies of genetically diverse individuals. The assemblies cover more than 99% of the expected sequence per genome at over 99% base-level and structural accuracy, and are combined into a graph-based reference. Relative to GRCh38, the pangenome adds about 119 million base pairs of euchromatic polymorphic sequence and 1,115 gene duplications, improving representation of variation at structurally complex loci.

Nature Open access