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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.

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

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.

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...