SARS-CoV-2 structural coverage map reveals viral protein assembly, mimicry, and hijacking mechanisms

Seán I. O'Donoghue (Lead / Corresponding author), Andrea Schafferhans, Neblina Sikta, Christian Stolte, Sandeep Kaur, Bosco K. Ho, Stuart Anderson, James B. Procter, Christian Dallago, Nicola Bordin, Matt Adcock, Burkhard Rost

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)
147 Downloads (Pure)

Abstract

We modeled 3D structures of all SARS-CoV-2 proteins, generating 2,060 models that span 69% of the viral proteome and provide details not available elsewhere. We found that ˜6% of the proteome mimicked human proteins, while ˜7% was implicated in hijacking mechanisms that reverse post-translational modifications, block host translation, and disable host defenses; a further ˜29% self-assembled into heteromeric states that provided insight into how the viral replication and translation complex forms. To make these 3D models more accessible, we devised a structural coverage map, a novel visualization method to show what is-and is not-known about the 3D structure of the viral proteome. We integrated the coverage map into an accompanying online resource (https://aquaria.ws/covid) that can be used to find and explore models corresponding to the 79 structural states identified in this work. The resulting Aquaria-COVID resource helps scientists use emerging structural data to understand the mechanisms underlying coronavirus infection and draws attention to the 31% of the viral proteome that remains structurally unknown or dark.

Original languageEnglish
Article numbere10079
Number of pages24
JournalMolecular Systems Biology
Volume17
Issue number9
Early online date1 Sept 2021
DOIs
Publication statusPublished - 14 Sept 2021

Keywords

  • COVID-19
  • SARS-CoV-2
  • bioinformatics
  • data visualization
  • structural biology

ASJC Scopus subject areas

  • General Biochemistry,Genetics and Molecular Biology
  • General Immunology and Microbiology
  • General Agricultural and Biological Sciences
  • Applied Mathematics

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