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The short answer is no. F@H used to study folding dynamics of proteins but moved on to study protein function using molecular dynamics. For these studies, they need experimentally derived proteins structures. Check out this link.
From the above link:
"There are many experimental methods for determining protein structures. While extremely powerful, they only reveal a single snapshot of a protein’s usual shape. But proteins have lots of moving parts, so we really want to see the protein in action. The structures we can’t see experimentally may be the key to discovering a new therapeutic."
A lot of the work at "folding@home" is using molecular dynamics to identify new sites for therapeutic intervention and screening drug-like molecules for binding in those sites (virtual screening). Perhaps the scientists at Deepmind could use a similar machine learning approach to develop better virtual screening algorithms.
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