A third way in which you are wrong is that AlphaFold derives a lot of its power by referring to previously-solved protein structures, or parts of them. It doesn't fold the proteins from scratch in an "alpha-zero" way.
so its more like protein folding was useless until an AI could make sense of the 17% solved variations and using that for the other 83% of proteins found in humans?
> After decades of effort, 17% of the total residues in human protein sequences are covered by an experimentally-determined structure. Here we dramatically expand structural coverage by applying the state-of-the-art machine learning method, AlphaFold2, at scale to almost the entire human proteome (98.5% of human proteins).
I just don't actually understand the quote from the article if it isn't comparing the same thing
> After decades of effort, 17% of the total residues in human protein sequences are covered by an experimentally-determined structure. Here we dramatically expand structural coverage by applying the state-of-the-art machine learning method, AlphaFold2, at scale to almost the entire human proteome (98.5% of human proteins).
I just don't actually understand the quote from the article if it isn't comparing the same thing