alt Hacker NewsThe accompanying preprint is interesting: https://www.biorxiv.org/content/10.64898/2026.06.03.729735v1
Modeling protein-protein binding is still a massively unsolved problem, mainly because we don't really have the data. Alphafold2 was great but didn't actually 'solve' protein-folding as all input data is from single 'state' X-ray crystallography of the proteins, not 'really' how these proteins behave in the wild. So it's still very, very had to predict what binds to what, which of course is a multi-billion-dollar industry.
I work in a pharma-field and I wish we could easily design molecular binders. We still spend millions every year finding targets that could 'smuggle' our drugs into cells.
Some other players in this field are Boltz Lab and Isomorphic Labs (the Alphafold Google spinoff led by Hasabi). None of them can predict anything complex or 'big', everything is peptide-level. OP's work is another step towards something better.
The most interesting part in the preprint is that they find no matches for their designed binders in the world-write protein database. An open question with protein-designers is whether they just regurgitate training material, which is far easier to test with English-language models.
Replies
> None of them can predict anything complex or 'big', everything is peptide-level.
Is this related to the current peptide boom?
> very had to predict what binds to what, which of course is a multi-billion-dollar industry.
Do you need to predict when AP-MS is so cheap?
Mapping interaction interfaces is challenging and is where there is attention. I don’t think we’re going to get complexes as a commercial focus outside of receptors with known quaternary structure. The first issue, as you allude to, is the absence of training data, which itself highlights the relative commercial unimportance of such an endeavor.