Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

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

blopig.com

Post reply on HN
Print view View original

71–80 of 98 posts

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

#71

Post by jcranmer »

throwamon wrote: post #65

So... could anyone with experience in the area give an estimate of how much the likelihood of an unstoppable, untraceable "DIY" bioweapon appearing in the next decade has increased thanks to this?

So I don't have experience in the area, but I'd give it about 0%.

To paraphrase Derek Lowe a lot (see, e.g., https://blogs.sciencemag.org/pipeline/archives/2021/03/19/ai...), there are several hard problems in biology, and the kind of progress embodied in AlphaFold isn't progress towards the rate-limiting problems. And many of the things that make drugs hard to develop are going to carry over into making bioweapons hard to develop.

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

#72

Post by summerlight »

maliker wrote: post #24
bamboozled wrote: post #17

Thank you Google...thank you!

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

Because the core competency is not the model or code, but the people and organization that enable this project (and perhaps computing infrastructure as well?). The pharma industry will try to catch up of course, but they will also likely try to establish collaboration with DeepMind. This could be a good first step for Google into the medical/pharma business.

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

#73

Post by matt2000 »

throwamon wrote: post #65

So... could anyone with experience in the area give an estimate of how much the likelihood of an unstoppable, untraceable "DIY" bioweapon appearing in the next decade has increased thanks to this?

I'm not an expert, but in a recent article about the new mRNA synthesis techniques they were asked the same question. The answer was there's already lots of potential bioweapons and many simpler techniques for producing them, so these new technologies don't change the danger level much.

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

#74

Post by jonas21 »

Game_Ender wrote: post #28

To me the most interesting part of the article is the cometary on where basic research is going to happen in the future. The fear is that if it only happens in large companies, then the unbiased pool of experts society relies on will be smaller and less informed. Along with the issue of nobody being around for the slog of defining a field, setting up databases, competitions and standards. These are what allow well fu…

> DeepMind claimed that they used “128 TPUv3 cores or roughly equivalent to ~100-200 GPUs”. Although this amount of compute seems beyond the wildest dreams of most academic researchers...

So, we're talking like what? Maybe $100K to $300K of hardware? Wet biology labs often have multiple pieces of $100K+ equipment at their disposal. Why shouldn't computational labs too?

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

#75

Post by Synaesthesia »

jonas21 wrote: post #74
Game_Ender wrote: post #28

To me the most interesting part of the article is the cometary on where basic research is going to happen in the future. The fear is that if it only happens in large companies, then the unbiased pool of experts society relies on will be smaller and less informed. Along with the issue of nobody being around for the slog of defining a field, setting up databases, competitions and standards. These are what allow well fu…

> DeepMind claimed that they used “128 TPUv3 cores or roughly equivalent to ~100-200 GPUs”. Although this amount of compute seems beyond the wildest dreams of most academic researchers... So, we're talking like what? Maybe $100K to $300K of hardware? Wet biology labs often have multiple pieces of $100K+ equipment at their disposal. Why shouldn't computational labs too?

Yeah but it's also putting it together and properly utlizing it, which takes specialist knowledge.

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

#76

Post by ac29 »

kevstev wrote: post #42
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…

Not sure about folding@home, but the lab that runs rosetta@home released a paper earlier this month claiming they have a new algorithm with comparable results to AlphaFold2: https://science.sciencemag.org/content/early/2021/07/19/scie...

I don't believe this new approach runs on their distributed compute network, but its cool to see some good competition.

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

#78

Post by vokep »

ansible wrote: post #49
spywaregorilla wrote: post #48

Earlier quoted context omitted.

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.

>Very, very useful.

Just to frame it a particular way, biological systems are basically solved nanotechnology, extremely good, self-sustaining, resilient little machines that have spent a long time optimizing to be better and better. But all the designs are preset, if we can crack the code and design our own little machines, then amazing things like more plastic-like cellulose could be made, all sorts of problems are suddenly far easier to solve. But also a lot of new problems emerge that weren't even imaginable before, since the code being cracked is a big chunk of the code of life itself. So, yknow, playing God and all, so there probably will be some negative consequences of this too.

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

#79

Post by swayson »

maliker wrote: post #24
bamboozled wrote: post #17

Thank you Google...thank you!

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

If I were to speculate:

1. It is inline with their vision/mission of the organization, advancing science. 2. Differentiate themselves from OpenAI, which despite the name, is not really big on open source.

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

#80

Post by sheggle »

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…

Just for my reference, what percentage of known but unfolded proteins (a wild guess is good enough), would you consider to be ab initio? How many don't have parts in any database?
Post reply on HN