Re:No, DeepMind has not solved protein folding
by timr on Saturday December 05, 2020 @07:33PM
(#25319806)
So you're a structural biologist. Good for you? I'm not sure how it affects that substance of the argument you're making. I'm not trying to argue from authority here -- I'm pointing out that I have direct experience in this specific area, just so that you know I'm not some random commenter.
"It is my judgement that if you presented these results in 2003 anyone would have said "the protein folding problem has been solved"."
Your judgment is your own. At the very least, your use of the word "anyone" should give you pause.
"Nobody then expected "the solution to protein folding" to solve every single protein, and it's silly to now."
Not the argument I'm making.
"If you're complaining about the 33% error rate, you don't know enough about ML to realize that that gap is going to get closed, and rapidly."
Not the argument I'm making.
"My argument is that it is "good enough for the uses that are in the domain of protein folding"."
I have no idea what that means. Uses "in the domain of protein folding" are equivalent to uses "in the domain of structural biology". So obviously, it depends on the quality of the structure being generated.
"There are a lot of things that are adjacent to protein folding (enzyme pocket analysis .e.g), but they never have been considered to protein folding per se."
You seem to have some internal dialogue where there is a field called "protein folding", where there is an unambiguous threshold for success that has now been crossed. There is no such field, and there is no such threshold.
Are these structures good enough to do some kinds of things, like structural genomics or docking? I dunno...maybe? Are they good enough to do structure-based drug design? Not from what I've seen. TFA seems to be saying the same thing, and your comment was that TFA is just wildly wrong, which seemed...unfair, at best.
"It is my judgement that if you presented these results in 2003 anyone would have said "the protein folding problem has been solved"."
Your judgment is your own. At the very least, your use of the word "anyone" should give you pause.
"Nobody then expected "the solution to protein folding" to solve every single protein, and it's silly to now."
Not the argument I'm making.
"If you're complaining about the 33% error rate, you don't know enough about ML to realize that that gap is going to get closed, and rapidly."
Not the argument I'm making.
"My argument is that it is "good enough for the uses that are in the domain of protein folding"."
I have no idea what that means. Uses "in the domain of protein folding" are equivalent to uses "in the domain of structural biology". So obviously, it depends on the quality of the structure being generated.
"There are a lot of things that are adjacent to protein folding (enzyme pocket analysis .e.g), but they never have been considered to protein folding per se."
You seem to have some internal dialogue where there is a field called "protein folding", where there is an unambiguous threshold for success that has now been crossed. There is no such field, and there is no such threshold.
Are these structures good enough to do some kinds of things, like structural genomics or docking? I dunno...maybe? Are they good enough to do structure-based drug design? Not from what I've seen. TFA seems to be saying the same thing, and your comment was that TFA is just wildly wrong, which seemed...unfair, at best.