All of our data is available! We released a deeply sampled, 55k variant library of NucB’s enzymatic function.

Get started here: github.com/google-deepm...

If you’re interested in learning more, check out our @ml4proteins.bsky.social seminar talk on this work

www.youtube.com/watch?v=eGNE...

This was a collaborative effort between myself, David Belanger, Lucy Colwell and our whole team: Chenling Xu, Hanson Lee, Kathleen Hirano, Kosuke Iwai, Vanja Polic, Kendra Nyberg, Kevin Hoff, Lucas Frenz, Charlie Emrich, Jun Kim, Mariya Chavarha, Abi Ramanan, Jeremy Agresti

This campaign was completed in 2021! Since then, the field has evolved tremendously. We’re excited about work that pushes forward:
1) Multi-objective optimization
2) Generative models (e.g. ESM3, ProGen, RFDiffusion)
3) Synergy with randomized library design
… to name a few