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Title | SARS-CoV-2 structural coverage map reveals viral protein assembly, mimicry, and hijacking mechanisms. |
Publication Type | Journal Article |
Year of Publication | 2021 |
Authors | O'Donoghue, SI, Schafferhans, A, Sikta, N, Stolte, C, Kaur, S, Ho, BK, Anderson, S, Procter, JB, Dallago, C, Bordin, N, Adcock, M, Rost, B |
Journal | Mol Syst Biol |
Volume | 17 |
Issue | 9 |
Pagination | e10079 |
Date Published | 2021 09 |
ISSN | 1744-4292 |
Keywords | Amino Acid Transport Systems, Neutral, Angiotensin-Converting Enzyme 2, Binding Sites, Computational Biology, Coronavirus Envelope Proteins, Coronavirus Nucleocapsid Proteins, COVID-19, Host-Pathogen Interactions, Humans, Mitochondrial Membrane Transport Proteins, Models, Molecular, Molecular Mimicry, Neuropilin-1, Phosphoproteins, Protein Binding, Protein Conformation, alpha-Helical, Protein Conformation, beta-Strand, Protein Interaction Domains and Motifs, Protein Interaction Mapping, Protein Multimerization, Protein Processing, Post-Translational, SARS-CoV-2, Spike Glycoprotein, Coronavirus, Viral Matrix Proteins, Viroporin Proteins, Virus Replication |
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. |
DOI | 10.15252/msb.202010079 |
Alternate Journal | Mol Syst Biol |
PubMed ID | 34519429 |
PubMed Central ID | PMC8438690 |
Grant List | 01IS17049 / / Bundesministerium für Bildung und Forschung (BMBF) / 031L0168 / / Bundesministerium für Bildung und Forschung (BMBF) / / / Tour de Cure Australia / BB/R009597/1 / / Biotechnology and Biological Sciences Research Council (BBSRC) / / WT_ / Wellcome Trust / United Kingdom 218259/Z/19/Z / / Wellcome Trust, UK / / / Garvan Research Foundation / / / Sony Foundation Australia / |