I did my PhD in the Folding@home lab, so I like this one. There’s a distinction between what’s formally called “ground-state structure” and “structural dynamics”. “Ground state structure” is the lowest-energy, most stable structure of a protein; for me, the ground state structure is “lying in bed”. But only knowing that doesn’t tell you how the structure moves around, which it turns out is important. For example, when I sprained my shoulder, the movement of my arm was highly restricted, but you wouldn’t have known that from looking at one position in which I sleep (you creep). Folding@home is more focused on modeling the dynamics of proteins than their ground state structures. For example, the most effective recent COVID vaccines used a modification to the spike protein called “S-2P”/”prefusion-stabilized” that effectively froze the protein in one particular shape rather than allowing it to fluctuate, which enhanced its ability to generate a useful immune response.
That said, dynamics is the obvious next step for ML methods in protein structure, so I would not be surprised to see new developments here!