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@machine.learning.bio

Today I’m joining collaborators at a WEF/CEPI roundtable in New York to share our latest @nvidiabot.bsky.social AI for Life Sciences work. Featured in Nature: nature.com/articles/d41...

Christian Dallago

@machine.learning.bio

Building on the AlphaFold Database protein-complex release at GTC, we explored ~1.7M protein pairs across 2,800+ viral proteomes. That scale lets us compare how viral proteins assemble and identify conserved interfaces.

Christian Dallago

@machine.learning.bio

From viral assemblies to how proteases recognise their substrates: starting points for vaccine and antiviral experiments. The predictions are open through AFDB, so researchers can use them without repeating the computation: alphafold.ebi.ac.uk

Christian Dallago

@machine.learning.bio

A huge team effort with Google DeepMind (Risha Patel), EMBL-EBI (Jennifer Fleming, Sameer Velankar) and SNU (Yewon Han, Martin Steinegger), University of Glasgow (Joe Grove), SIB (Philippe Le Mercier), CEPI (Newton Wahome) and Sungkyunkwan University (Milot Mirdita).

Christian Dallago

@machine.learning.bio

A special shoutout to Riya Narain, who spent the summer interning on my team and did so much of the work behind this release. I’m proud of what she’s contributed.

24/9/26, 4:44 pm0 reposts1 like

Christian Dallago

@machine.learning.bio

NVIDIA blog: blogs.nvidia.com/blog/open-pr... EMBL-EBI: embl.org/news/science... Featured in Nature: nature.com/articles/d41... Explore the research and build on it: Paper: research.nvidia.com/labs/dbr Pipeline: github.com/NVIDIA-BioNe...