311–320 of 343 posts
I think putting AlphaFold here was premature; it might not age well. AlphaFold is an impressive achievement but it simply has not "cracked the code for protein folding" - about 1/3rd of its predictions are too uncertain to be usable, it says nothing about dynamics, suffers from the same ML problems of failing on uncommon structures, and I was surprised to learn that many of its predictions are incorrect because it ig…
I think putting AlphaFold here was premature; it might not age well. AlphaFold is an impressive achievement but it simply has not "cracked the code for protein folding" - about 1/3rd of its predictions are too uncertain to be usable, it says nothing about dynamics, suffers from the same ML problems of failing on uncommon structures, and I was surprised to learn that many of its predictions are incorrect because it ig…
It's this also a problem with Alphafold2 or just the original Alphafold ?
Earlier quoted context omitted.
you assume likely with excellent results. perhaps his results weren't excellent?
likely because hassabis was a child prodigy. Was a chess master at 13. Lead Cambridge chess team. its not surmise to assume that demis had impeccable school record
Earlier quoted context omitted.
Yes, Rosetta did monte carlo substitution of 9-mers, followed by a refinement phase with 3-mers. Plus a bunch of other stuff to generate more specific backbone "moves" in weird circumstances. In order to create those fragment libraries , there was a step involving generation of multiple-sequence alignments, pruning the alignments, etc. Rosetta used sequence homology to generate structure. This wasn't a wild, untested…
> Rosetta used sequence homology Rosetta used remote sequence homology to generate the MSAs and find template fragments, which at the time was innovative. A similar strategy is employed for AlphaFold’s MSAs containing the evolutionary couplings.
Earlier quoted context omitted.
It doesn't deserve a Chemistry Nobel prize. It deserves a prize about computers.
So the Nobel commite was wrong to decide this because you think otherwise? Interesting. Any more indepth analys about this? Btw. you don't just build AlphaFold by doing only 'computers'. Take a look at any good docmentary about it and you will see that they do discuss chemistry on a deep level
It is possible that some committee members might have raised this same concern in their discussions.
relatively short : in comparison to real chemists, whose work is the basis for this development.
This is my first interaction in Hackernews, and I was expecting a more polite discussion. I just expressed my idea. You could ask for my explanations.
Earlier quoted context omitted.
So the Nobel commite was wrong to decide this because you think otherwise? Interesting. Any more indepth analys about this? Btw. you don't just build AlphaFold by doing only 'computers'. Take a look at any good docmentary about it and you will see that they do discuss chemistry on a deep level
Deepmind isn't a chemistry company. Demiss Hassabis isn't a chemist. A tool they developed in their area may turn out to be useful in Chemistry. They may spend some relatively short time and effort to apply their tool to Chemistry. They can do the same thing in many areas in every few years and collect all the Nobel's in many areas. That effort is worth for a prize but the context is different. It is possible that so…
And i personally really think if people from a different field, jump into a new field and revolutionize it, a nobel price is not a bad thing to appreciate this effort.
Earlier quoted context omitted.
They're referring to the structure of the protein when a drug is bound, that's what's novel. Novel as in, you can't think of it as "just" interpolation between known structures of evolutionarily related proteins. That said I'm not sure that's entirely fair, since Alphafold does, as far as I know, work for predicting structures that are far away from structures that have previously been measured. You're quite wrong ab…
But even drugs made by combinatorial chemistry still generally end up being analogues of natural products even if they aren't derived from them. As Leslie Orgel said "Evolution is cleverer than you are"; chemists are unlikely to discover a mechanism of action that millions of years of evolution hasn't already found.
I'm well aware of the impact of natural products and particularly plant secondary metabolites in drug discovery. I'm also aware of combinatorial synthesis occasionally hitting structures that are close to natural products.
But from first principles, why would you need to limit yourself to that subset of molecular space?
Obviously, your structure will need to look vaguely biochemical to be compatible with the bodies chemical environment, but natural products are limited to biochemically feasible syntheses, and are therefore dominated by structures derived from natural amino acids and similar basic biochemical building blocks.
For a concrete example off the top of my head, I'm not aware of any natural diazepines - the structure looks "organic" but biochemistry doesn't often make 7-rings, and those were made long before combinatorial chemistry. Might be wrong on this one, since there's so much out there, but I think it holds.
For those like myself who design proteins for a living, the open secret is that well before AlphaFold, it was pretty much possible to get a good-enough structure of any particular protein you really cared about (from say 2005) by other means, namely Baker’s Rosetta. I constantly use AlphaFold structures today [1]. And AlphaFold is fantastic. But it only replaces one small step in solving any real-world problem involv…
Rosetta was clunky and not even David Baker would endorse it
I worked on protein structure prediction for a couple years and it was sota.
Earlier quoted context omitted.
The multiplier would be significantly different. Think the Wright Brothers first aeroplane vs a rocket ship.
There were at least hundreds of thousands if not millions who had easier starts them Jeff Besos.
Of course, that's not possible, so then you do the same with other highly intelligent and skilled tech professionals. I'd argue that without the funding and other resources, those skilled pro's won't get anywhere. But with it, some would do incredibly well. It's not common in a global sense, but we see it every single day.
Comparing Bezos to thousands/millions of randomised others is pointless.
Then you may say, oh but Amazon is unique. Yes, but then there are other factors at play. Like the luck (skill? funding?) to take advantage of a unique moment in time at the start of the web. That moment isn't available eveI mean, try to start an Amazon today ... etc