SARS-CoV-2 structural coverage map reveals viral protein assembly, mimicry, and hijacking mechanisms
Friday 22 October, 12pm via Zoom
Presented by Professor Sean O’Donoghue, Lab Head & Senior Faculty Member, Garvan Institute and Visiting Scientist, CSIRO Data61
e used high-throughput machine learning to model 3D structures of all SARS-CoV-2 proteins, generating 2,060 models that span 69% of the viral proteome and provide detail 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 defences; 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. Publication: https://doi.org/10.15252/msb.202010079. Learn more here https://www.garvan.org.au/people/seaodo
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