It's probably never going to be solved though right. To truly solve protein folding we'd have to have a program that can stimulate a small but still significant system at the QM level; looks like deep learning can get us 60% (conservatively estimating the whole problem domain ) but not all the edge cases, just like it did in other problem domains as well.
Despite this breakthrough by DeepMind, at this point we still do not understand protein folding. That makes it very hard to say precisely which features would be required to do the simulation correctly.
DeepMind/AlphaFold might have something to contribute there too, depending on how interpretable their network model(s?) are.
They seem to have a completely new tension algorithm that's doing the heavy lifting now, so it's likely we will learn much about how folding practically works from these results as well.
It remains unclear whether QM is required to fold proteins accurately. So far classical methods have shown they require far less computer power to get far closer to the right structure.
'Never' is a long timespan :) It will be solved, sooner or later. The universe will be fully understood and manipulated. By us, a modified version of us, or some other entity, perhaps even one we created. 300 years ago 'electricity' wasn't even a word. We can imagine what 500 years into the future will be, with an exponentially more advanced tech, worse than a caveman could imagine the concept of 'machine learning'.
