tetano
Editor, Senior Moderator
Mol Syst Biol
. 2021 Sep;17(9):e10079.
doi: 10.15252/msb.202010079.
SARS-CoV-2 structural coverage map reveals viral protein assembly, mimicry, and hijacking mechanisms
Seán I O'Donoghue[SUP] 1 2 3 [/SUP], Andrea Schafferhans[SUP] 1 4 5 [/SUP], Neblina Sikta[SUP] 1 [/SUP], Christian Stolte[SUP] 1 [/SUP], Sandeep Kaur[SUP] 1 3 [/SUP], Bosco K Ho[SUP] 1 [/SUP], Stuart Anderson[SUP] 2 [/SUP], James B Procter[SUP] 6 [/SUP], Christian Dallago[SUP] 5 [/SUP], Nicola Bordin[SUP] 7 [/SUP], Matt Adcock[SUP] 2 [/SUP], Burkhard Rost[SUP] 5 [/SUP]
Affiliations
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.
Keywords: COVID-19; SARS-CoV-2; bioinformatics; data visualization; structural biology.
. 2021 Sep;17(9):e10079.
doi: 10.15252/msb.202010079.
SARS-CoV-2 structural coverage map reveals viral protein assembly, mimicry, and hijacking mechanisms
Seán I O'Donoghue[SUP] 1 2 3 [/SUP], Andrea Schafferhans[SUP] 1 4 5 [/SUP], Neblina Sikta[SUP] 1 [/SUP], Christian Stolte[SUP] 1 [/SUP], Sandeep Kaur[SUP] 1 3 [/SUP], Bosco K Ho[SUP] 1 [/SUP], Stuart Anderson[SUP] 2 [/SUP], James B Procter[SUP] 6 [/SUP], Christian Dallago[SUP] 5 [/SUP], Nicola Bordin[SUP] 7 [/SUP], Matt Adcock[SUP] 2 [/SUP], Burkhard Rost[SUP] 5 [/SUP]
Affiliations
- PMID: 34519429
- DOI: 10.15252/msb.202010079
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.
Keywords: COVID-19; SARS-CoV-2; bioinformatics; data visualization; structural biology.