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Chemistry Nobel: Computational protein design and protein structure prediction

nobelprize.org

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Re: Chemistry Nobel: Computational protein design and protein structure prediction

#151

Post by afthonos »

DevX101 wrote: post #145
aleph_minus_one wrote: post #137

Earlier quoted context omitted.

> The nature of scientific work has changed significantly since 1895, when the Nobel Prizes were established. 100 years ago, lots of scientific work really were driven forward largely by a singular person. That's rarely true today for groundbreaking research. The question is: is this a necessity for doing good science today, or rather an artifact of how important research is organized today (i.e. an artifact of the b…

So I did a mini research project on Claude to answer your question. From 1900-1930, 87% of Nobel Prizes in Physics, Chemistry and Physiology/Medicine were awarded to individual contributions, 13% were awarded to collaborative contributions. This ratio has flipped in the past 30 years, from 1994-2023, where 17% prizes were individual, 83% collaborative. So I'd say yes, collaborative work is increasingly a requirement…

This begs the question. If all science is now structured as big research teams, we'd expect the breakthroughs to come from such teams. That doesn’t necessarily imply that teams are needed.

Re: Chemistry Nobel: Computational protein design and protein structure prediction

#152

Post by jhbadger »

trott wrote: post #82
paulwetzel wrote: post #4

While I am skeptical about yesterdays award in physics, these are totally deserved and spot on. There are few approaches that will accelerate the field of drug development and chemistry as a whole in a way that the works of these three people will. Congratulations!

> There are few approaches that will accelerate the field of drug development and chemistry as a whole in a way that the works of these three people will. As the author of one such approach, I'm skeptical. AlphaFold 2 just predicts protein structures. The thing about proteins is that they are often related to each other. If you are trying to predict the structure of a naturally occurring protein, chances are that the…

Protein structures are similar to each other because of evolution (protein families exist because of shared ancestry of protein coding genes). It's not a weird coincidence that helps ML; it's inherent in the problem. Same with drug design -- very, very, few drugs are "novel" as opposed to being analogues of something naturally in the body.

Re: Chemistry Nobel: Computational protein design and protein structure prediction

#153

Post by dekhn »

I wasn't expecting to see David Baker in the list (just Demis and John). But I'm really glad to see it... David is a great guy.

At CASP (the biannual protein structure prediction competition) around 2000, I sat down with David and told him that eventually machine learning would supplant humans at structure prediction (at the time Rosetta was already the leading structure prediction/design tool, but was filled with a bunch of ad-hoc hand-coded features and optimizers). he chuckled and said he doubted it, every time he updated the Rosetta model with newer PDB structures, the predictions got worse.

I will say that the Nobel committee needs to stop saying "protein folding" when they mean "protein structure prediction".

Re: Chemistry Nobel: Computational protein design and protein structure prediction

#154

Post by lchengify »

ThePhysicist wrote: post #67

Demis Hasabis has a really interesting and unusual CV for a nobel laureate [1], he started his career in AI game programming (he worked e.g. on Popoulous II, Syndicate, Theme Park for Bullfrog, and later for Lionhead Studios on Black & White) before doing a PhD in neuroscience, becoming an entrepreneur and starting DeepMind. I would say this is a refreshing and highly uncommon pick for a nobel prize, really cool to s…

Didn't know he worked on Black & White. Black & White was really ahead of it's time for 2001, it did a much better job of having NPC simulations in groups based on how you played as a god.

Re: Chemistry Nobel: Computational protein design and protein structure prediction

#155

Post by DevX101 »

nextworddev wrote: post #135
singularity2001 wrote: post #128

Earlier quoted context omitted.

whose father was one of the leading local industrialists (installing the first electric lighting for the 1885 Munich Oktoberfest)

It’s fascinating how the affluent backgrounds of many famous scientists and entrepreneurs are downplayed. Eg Warren Buffet, Jeff Bezos, etc

If you gave the $300,000 Bezos got from his father to 10,000 random Americans in 1994, none of them would have created a company the equivalent of Amazon's scale.

Re: Chemistry Nobel: Computational protein design and protein structure prediction

#158

Post by beanjuice »

j7ake wrote: post #144
aithrowawaycomm wrote: post #101

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 would say alphafold is to structure prediction as crispr is to gene editing. Crispr did not solve gene editing either, but has been made accessible to the broad biochemistry and biology researchers to use. Both similar impact and changed the field significantly.

Entire fields are based upon the existence of crispr now, it demonstrated its impact. It has been 2? 3? years, people who were making papers anyway have implemented AlphaFold, it hasn't exactly spawned a new area.

Re: Chemistry Nobel: Computational protein design and protein structure prediction

#159

Post by [deleted] »

eig wrote: post #149
singularity2001 wrote: post #126

Earlier quoted context omitted.

>> I do think AlphaFold already has reached sufficient level of impact. how so?

Well I'm sure one could look at number of published papers etc, but that metric is a lot to do with hype and I see it as a lagging indicator. A better one is seeing my grad-school friends with zero background in comp-sci or math, presenting their cell-biology results with AlphaFold in conferences and at lab meetings. They are not protein folding people either- just molecular biologists trying to present more evidence…

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