AlphaFold developers win $3M breakthrough prize (opens in new tab)

> more than half a million researchers have used the machine-learning system, generating thousands of papers

Funny things is how the general scientific community (including nature) defines 'impact'. I somehow still strangley trust the Nobel committee to take a different approach here. Was curious and found this interesting collection of references: https://www.researchgate.net/project/Enacting-Excellency-Awa... .

CRISPR is a revolutionary tool.

AlphaFold doesn't solve folding. It makes metaheuristic guesses without writing a bunch of quantum chemistry, statistical physics, thermodyanamics, and topology maths / algorithms.

I don't mean to downplay AlphaFold, but we haven't solved protein folding yet. This press is really getting ahead of itself.

The same Nobel Committee that gave Obama a Peace Prize within months of taking office?

In my opinion, absolutely. The "protein folding problem" has been widely regarded as one of the biggest challenges in molecular biology for over half a century, and Alphafold has effectively solved it. I would put this up there with Sanger winning the prize for discovering how to sequence DNA and Kary Mullis for inventing PCR... this will have widespread implications for allowing us to understand, and even design proteins.

The joke is that the Nobel prize in chemistry is often awarded to non-chemists.

It could also draw the attention of the Physics Nobel committee. Oodles of physicists have been working on the folding inverse-problem for decades.

The Nobel Prize does not only award scientists for enabling high impact discoveries, but occasionally to people who make a major discovery that has no immediate impact. There is literature dribbling out from folks using AlphaFold models, but that's not what they would be awarding here. This was a long-standing problem that was convincingly solved.

Not Nature but Molecular Systems Biology [2], apologies, in the context of reverse docking for antibiotics discovery:

"We confirm extensive promiscuity, but find that the average area under the receiver operating characteristic curve (auROC) is 0.48, indicating weak model performance."

Derek Lowe had a post about this earlier this month [1] (which includes important qualifications I failed to omit).

[1] "Benchmarking AlphaFold-enabled molecular docking predictions for antibiotic discovery", Molecular Systems Biology 2022 18:e11081 https://doi.org/10.15252/msb.202211081

[2] "Not AlphaFold's Fault", September 7 2022, https://www.science.org/content/blog-post/not-alphafold-s-fa...

Sorry, you don't know what you're talking about. Nobody is truly claiming these models can be used directly for drug discovery (well, some people claim that; but they're wrong). We already knew that, though- the same problem exists with high quality crystal structures.

What would be more interesting is if we did a whole bunch of crystal or cryo-EM structures far from what we've previously determined and demonstrate whether alphafold could make out-of-class predictions for them.

Do you have links to that? have not seen those.

Completely unrelated, but whenever I see stats like "Deepmind, an org of about 1,000 employees" and then contrast that to the amount of interesting advancements they're making, I cant help but wonder where we'd be with 100,000+ people working on these type of issues.

Kind of how most medical advancements come out of the US, which makes up only <4.25% of world population.

I know orgs dont scale like that and there are hits to productivity with orgs getting less lean but still.

“It’s all still hype at this point” implies this is vaporware when it’s a real thing that has solved one of the biggest roadblocks in microbiology. Your claim is analogous to lithium batteries, invented in 1976, taking 25+ years before completely DOMINATING the modern battery market. Science takes time to go from the research stage to mass market adoption. Level set your expectations.

Even physics is nowhere close to “100% accurate.” Most fields of physics approximate many body problems that are infeasible to compute, let alone fully specify. E.g. Astrophysics, solid state physics, nuclear physics, etc. Practitioners regularly use empirically measured parameters like cross-sectional scattering areas, and those parameters are updated and narrowed over time.

I agree with you. I should have made a better choice than lottery. My intention was that the needle which sets the reward for research, long life work pursuing the solution of a problem should move to the right and get those people more.

$3M isn't enough in our days to recognize remarkable work in my opinion. Yes, one of them made a lot of money, but is it true for all the past winners of this prize?

Alice walton comes to mind

https://www.mic.com/articles/79039/the-untold-story-of-alice...

And let's not talk about the Sacklers

I agree, my wording was not perfect.

My point was that such a prize should be backed with more money. Even for the sake of a statement what we consider to be important.

So the emphasize was about the enormous ratio between the two and not about lottery being wrong (Moreover it pays for itself).