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

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31–40 of 98 posts

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

#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 press about applications and pharma.

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

#32

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 nanotechnology, where instead of building arbitrary structures out of amino acids, we increase the range of arbitrary molecules we can design, build, and produce in quantity.

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

#34

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

That remains to be seen. People hope it will lead to new treatments for diseases of all kinds. Whether or not that materializes is big question mark.

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

#35
post #24

Earlier quoted context omitted.

Why did they open source it? Wouldn’t this model be very valuable to the pharma industry?

It is written in the article. A few reasons could be pressure from the publishing magazine, emerging open source implementations of the same idea, and the fact that this is still far from easy to comercialize.

Don't forget internal pressure.

A lot of people will say "Unless you opensource my work and that of my colleagues, I quit".

When faced with all your best people threatening to quit, you might just opensource that work. It turns out you still have an advantage by being ~1 year ahead on applying it to anything, and having all the people who know how it works on your staff.

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

#36
post #24

Earlier quoted context omitted.

Why did they open source it? Wouldn’t this model be very valuable to the pharma industry?

It is written in the article. A few reasons could be pressure from the publishing magazine, emerging open source implementations of the same idea, and the fact that this is still far from easy to comercialize.

Another reason could be that whoever wants to run it will very likely run it in the cloud, and there's a chance they'd run it in the Google Cloud. A machine similar to the one they mention on the alphafold github page (12 vCPU, 1 GPU, 85 GB) costs you between $1 and $4/hour.

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

#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?

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

#38

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?

Government funding (eg. DARPA) or from large corporations that have skunkworks teams (Google, IBM, Microsoft, etc.)

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

#39
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 remember that the scientific game "Fold It" was also quite exciting when it came out 12-13 years ago or so, since populations of players could get results beyond what either specialists or computer systems could achieve. I guess one could argue that an AI such as this could be compared to a large automated population of trained players trying to solve a 3D puzzle.

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

#40

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".

A group of your competitors then trashes your proposal in a group and if you've properly massaged the right backs, you get a pittance, which permits you to struggle to keep up with all your promises.

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