zlacker

>>ChrisA+(OP)
AlphaFold is optimization, not thinking. Propaganda 'r us.

>>DrierC+R1
Not sure why this is downvoted. The comment cuts to the core of the "Intelligence vs. Curve-Fitting" debate. From my humble perspective as a PhD in the molecular biology /biophysics field you are fundamentally correct: AlphaFold is optimization (curve-fitting), not thinking. But calling it "propaganda" might be a slight oversimplification of why that optimization is useful. If you ask AlphaFold to predict a protein that violates the laws of physics (e.g. a designed sequence with impossible steric clashes), it will sometimes still confidently predict a folded structure because it is optimizing for "looking like a protein", not for "obeying physics". The "Propaganda" label likely comes from DeepMind's marketing, which uses words like "Solved"; instead, DeepMind found a way to bypass the protein folding problem.

>>Rochus+xj
It seems that to solve the protein folding problem in a fundamental way would require solving chemistry, yet the big lie (or false hope) of reductionism is that discovering the fundamental laws of the universe such as quantum theory doesn't in fact help that much with figuring out the laws/dynamics at higher levels of abstraction such as chemistry.

So, in the meantime (or perhaps for ever), we look for patterns rather than laws, with neural nets being one of the best tools we have available to do this.

Of course ANNs need massive amounts of data to "generalize" well, while protein folding only had a small amount available due to the months of effort needed to experimentally discover how any protein is folded, so DeepMind threw the kitchen sink at the problem, apparently using a diffusion like process in AlphaFold 3 to first determine large scale structure then refine it, and using co-evolution of proteins as another source of data to address the paucity.

So, OK, they found a way around our lack of knowledge of chemistry and managed to get an extremely useful result all the same. The movie, propaganda or not, never suggested anything different, and "at least 90% correct" was always the level at which it was understood the result would be useful, even if 100% based on having solved chemistry / molecular geometry would be better.

>>HarHar+QP
We have seen some suggestion that the classical molecular dynamics force fields are sufficient to predict protein folding (in the case of stable, soluble, globular proteins), in the sense that we don't need to solve chemistry but only need to know a coarse approximation of it.