Viewing a single comment thread. View all comments

GimmickNG t1_j7mm8cs wrote

Now that google DeepMind and other AI tools can predict protein structures, what's the real utility of programs like Folding@Home and FoldIt?

1

IHaque_Recursion t1_j7mv6ze wrote

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!

2

GimmickNG t1_j7n4avs wrote

I see, thanks! Good to know the effort in running Folding@Home hasn't been made redundant by AI just yet, although I certainly look forward to developments in the field!

1