In principle, being able to predict protein structures with high accuracy could greatly enhance the rate at which we can understand human diseases and come up with treatments and cures. In practice.... that's not really true.
BUt it's still nice to be able to point to a specific ML model and say "this 30+ year problem was substantially addressed"; it shows people banged their heads on something for 30 years, got stuck, and finally ML found a nice way out
Language models have been used by Meta and others to enhance the protein fold work of Alphafold2. Conjoined with diffusion networks, they're able to generate de novo proteins[0].
OpenAI has nothing going [publicly] in the burgeoning generative protein space.