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AlphaFold 2 is here: what’s behind the structure prediction miracle

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Re: AlphaFold 2 is here: what’s behind the structure prediction miracle

#41

Post by mda »

dekhn wrote: post #31

So, unsurprisngly, it appears that applying a transformer to multiple sequence alignments extracts somewhat more spatial information about proteins than we had been able to previously squeeze out. It's pretty clear at this point that the work led to a large improvement in psp scores, but there's literally nothing else groundbreaking about it; I don't mean that in a bad way, except to criticize all the breathless pres…

Well it did gave geoundbreking results, it is weird to see people dismisses it as "Not groundbrraking enough".

Re: AlphaFold 2 is here: what’s behind the structure prediction miracle

#42

Post by kevstev »

Quarrel wrote: post #12

Awesome. I wrote a thesis on protein structure prediction in 1995. We weren't very good at it then. Amazing to see this.

I did some undergraduate research on this around 1999. At the time we were trying to prove that we could throw more firepower at the problem by building a beowulf cluster to solve the problem. After a bit of tweaking, we were able to get more performance than a single machine, but soon seti@home was released and to me at least the writing was on the wall that we were not taking the most optimal approach.

In hindsight though, we were so far off from both an algorithmic perspective and a hardware perspective to actually achieving meaningful results. I am glad, 20 years later it seems real progress is being made. I haven't really followed the folding@home project in many many years, but its not clear to me much came out of it that was all that useful, at least not in practical terms.

Re: AlphaFold 2 is here: what’s behind the structure prediction miracle

#43

Post by infogulch »

dekhn wrote: post #40
phkahler wrote: post #37

How does work like this get funded? It's awesome, but it seems so far removed from... let's say "profit". And there are several teams competing in these things. Are there places that really fund advanced work like this, or is it mostly graduate student underpaid labor?

Most of the US researchers who do CASP are funded by NIH or NSF. Some are funded by private foundations, or are independently wealthy. Typically, as a "principal investigator" (postdoc, professor, scientist at a national lab) you write a proposal saying "here's my preivous work, here's the next obvious step, plz give monies so I can feed the dean's fund and pay for my grad students to manage my modest closet cluster"…

Yikes that sounds bleak.

Re: AlphaFold 2 is here: what’s behind the structure prediction miracle

#44

Post by dekhn »

mda wrote: post #41
dekhn wrote: post #31

So, unsurprisngly, it appears that applying a transformer to multiple sequence alignments extracts somewhat more spatial information about proteins than we had been able to previously squeeze out. It's pretty clear at this point that the work led to a large improvement in psp scores, but there's literally nothing else groundbreaking about it; I don't mean that in a bad way, except to criticize all the breathless pres…

Well it did gave geoundbreking results, it is weird to see people dismisses it as "Not groundbrraking enough".

it was a nice improvement. that's fine. But it's ultimately just statistical modelling based on deep evolutionary information. It only works on homology modelling, it doesn't actually solve the larger protein structure prediction problem. Therefore it's not groundbreaking but a significant improvement.

Re: AlphaFold 2 is here: what’s behind the structure prediction miracle

#45

Post by IshKebab »

dekhn wrote: post #44
mda wrote: post #41

Earlier quoted context omitted.

Well it did gave geoundbreking results, it is weird to see people dismisses it as "Not groundbrraking enough".

it was a nice improvement. that's fine. But it's ultimately just statistical modelling based on deep evolutionary information. It only works on homology modelling, it doesn't actually solve the larger protein structure prediction problem. Therefore it's not groundbreaking but a significant improvement.

It's perfectly reasonable to describe a very large improvement as groundbreaking.

Re: AlphaFold 2 is here: what’s behind the structure prediction miracle

#46

Post by couteiral »

dekhn wrote: post #44
mda wrote: post #41

Earlier quoted context omitted.

Well it did gave geoundbreking results, it is weird to see people dismisses it as "Not groundbrraking enough".

it was a nice improvement. that's fine. But it's ultimately just statistical modelling based on deep evolutionary information. It only works on homology modelling, it doesn't actually solve the larger protein structure prediction problem. Therefore it's not groundbreaking but a significant improvement.

I respectfully disagree. AlphaFold 2 demonstrated almost perfect performance for a multitude of proteins for which no meaningful templates were available -- hence, it was not doing homology modelling as it is generally understood, but ab initio protein structure prediction.

What I would support is that AlphaFold 2 does not solve the protein folding problem: how, as opposed to what to, a protein folds.

Re: AlphaFold 2 is here: what’s behind the structure prediction miracle

#47

Post by 6gvONxR4sf7o »

londons_explore wrote: post #2

> Like most bioinformatics programs, AlphaFold 2 comes equipped with a “preprocessing pipeline”, which is the discipline’s lingo for “a Bash script that calls some other codes”. Having Bioinformatics people requiring to stray a long way from their core competency to learn a scripting language from the 80's to write glue code seems... suboptimal. How many hours of expert time has been wasted figuring out how to split…

Among the bioinformatics folks I know, bash is already a core competency. If you’re using your average biologist as your mental model, you’re thinking of the wrong people.

Re: AlphaFold 2 is here: what’s behind the structure prediction miracle

#48

Post by spywaregorilla »

ansible wrote: post #32
spywaregorilla wrote: post #29

What are the big implications of being good at predicting protein structures?

The goal all along has been to design proteins with a specific structure. This can be applied to just about any area of biology. You could design novel antigens to combat disease, and then easily mass-produce them. Or just inject the RNA to have the body produce them. But the applications are boundless, from genetically modifying crops, to anti-aging, and more. It is also one of the key pathways to molecular nanotech…

Is it the structure that's important? Or is the structure just a way to combine certain amino acids in a stable manner and its the combination of acids that we care about? Or is structure just a way of saying a specific permutation of amino acids?

Re: AlphaFold 2 is here: what’s behind the structure prediction miracle

#49

Post by ansible »

spywaregorilla wrote: post #48
ansible wrote: post #32

Earlier quoted context omitted.

The goal all along has been to design proteins with a specific structure. This can be applied to just about any area of biology. You could design novel antigens to combat disease, and then easily mass-produce them. Or just inject the RNA to have the body produce them. But the applications are boundless, from genetically modifying crops, to anti-aging, and more. It is also one of the key pathways to molecular nanotech…

Is it the structure that's important? Or is the structure just a way to combine certain amino acids in a stable manner and its the combination of acids that we care about? Or is structure just a way of saying a specific permutation of amino acids?

The structure is the whole point. As I understand it, you can link together nearly arbitrary sequences of amino acids. But a random string of AAs will just result in a jumbled protein that doesn't do anything useful.

Specific structures are useful in all manner of ways, from cleaving a DNA molecule at a specific point, enzymes for breaking apart molecules, etc.

Very, very useful.

Re: AlphaFold 2 is here: what’s behind the structure prediction miracle

#50

Post by dekhn »

couteiral wrote: post #46
dekhn wrote: post #44

Earlier quoted context omitted.

it was a nice improvement. that's fine. But it's ultimately just statistical modelling based on deep evolutionary information. It only works on homology modelling, it doesn't actually solve the larger protein structure prediction problem. Therefore it's not groundbreaking but a significant improvement.

I respectfully disagree. AlphaFold 2 demonstrated almost perfect performance for a multitude of proteins for which no meaningful templates were available -- hence, it was not doing homology modelling as it is generally understood, but ab initio protein structure prediction. What I would support is that AlphaFold 2 does not solve the protein folding problem: how, as opposed to what to, a protein folds.

how could they do ab initio? They depend on multiple sequence alignments.

If I'm mistaken about this then I'll happily take back what I said, but there's no way that AF2 could work wihtout MSAs, therefore, it is not ab initio.

Ah, OK checked the paper again. They're working on the "template" category which means there is structure-sequence information... maybe CASP organizers consider this ab initio ? The paper never mentions anything about ab initio predicitons. Is that what you're saying, that template methods are ab initio?

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