31–40 of 683 posts
Nonetheless, I'd like to hear more from specialists outside the context of a marketing blog post before I fully buy into a claim of a solution.
There's also a rabbit hole about what 'solution' actually means. Is the performance sufficient for any protein folding prediction application that might arise in the future?
Been out of the field for a while, could someone currently in it qualify these results? Hyperbolic title notwithstanding, they approach 90% median free modeling accuracy. The "other 90%" still remains to be solved...
This sounds wonderful and frightening. On the one hand, now we can engineer drugs at light speed. But wasn't protein folding supposed to be NP-hard? Can deep learning find the cracks in P vs NP? Perhaps making clever guesses at prime factors because it learned some weird structural fact that has eluded mathematicians. If we break crypto, there goes the modern world. Banks, bitcoin, privacy, Internet, the whole sheban…
Not knowing a lot about biotechnology, I read the article and it sounds great, but how big is this as a gamechanger? Can someone comment on how big are the implications of this in, let’s say, 5 years from now, on day to day life? Does this mean that biotech is going to explode? Or just that drugs will come to market faster, perhaps cheaper for rare diseases, but from the same industry structure as always?
Protein folding is a big and important problem, so this is certainly big news if it works as well as it seems. But I wouldn't assume that this changes everything, we can already determine how proteins fold by experimental work. The disadvantage is that this is a lot of work, though the methods there also improved a lot. One question is how robust the predictions are that DeepMind produces. I would also assume that ri…
What an accurate model of protein folding allows us to do, is to take our big database of DNA, predict protein foldings for all of it, and then stand up a search index for this database, keying each amino-acid "row" by the "words" of its predicted protein's structural features.
We could then, with a simple search query that executes in O(log n) time, find DNA targets that produce molecules with interesting structures that might be worthy of study.
This would, for example, be a game-changer in how biopharmaceutical macromolecule-therapy R&D is conducted. Right now we have to notice that some bacterium or another produces some interesting protein, and then engineer a bioreactor to get more of that protein. With this tech, we can work backward from an entirely hyothetical, under-specified "interesting protein", to figure out what catalogued-but-unstudied DNA sequences produce never-before-catalogued proteins that fit that particular functional "shape", and therefore might do the interesting thing. Then we can either directly synthesize that same DNA, or find the organism we originally sampled it from and study it more.
Not knowing a lot about biotechnology, I read the article and it sounds great, but how big is this as a gamechanger? Can someone comment on how big are the implications of this in, let’s say, 5 years from now, on day to day life? Does this mean that biotech is going to explode? Or just that drugs will come to market faster, perhaps cheaper for rare diseases, but from the same industry structure as always?
So imagine you gave an iPhone to someone in the 1800's, they wouldn't understand how most of it works, but this may be analogous to them finally figuring out some key aspects of the transistor. So it's another tool in the toolbelt and like all good tools will be used in all sorts of unpredictable ways.
Someone else I'm sure could do a lot better at explaining how important shape is to understanding the function and behavior of proteins.
This sounds wonderful and frightening. On the one hand, now we can engineer drugs at light speed. But wasn't protein folding supposed to be NP-hard? Can deep learning find the cracks in P vs NP? Perhaps making clever guesses at prime factors because it learned some weird structural fact that has eluded mathematicians. If we break crypto, there goes the modern world. Banks, bitcoin, privacy, Internet, the whole sheban…
Amazing day for structural biology! If it weren't for the pandemic, I would be out at the bars celebrating tonight!