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AlphaFold: a solution to a 50-year-old grand challenge in biology

deepmind.com

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Re: AlphaFold: a solution to a 50-year-old grand challenge in biology

#621

Post by isoprophlex »

Ono-Sendai wrote: post #618

Can some explain why you can't just run a simulation simulating the forces between the amino acids, and let the protein curl up based on those forces?

Accurate modelling on such a detailed level becomes intractable due to long time scales needed for folding, and the presence of forces that are not adequately described at the "ball and spring" level of abstraction that molecular mechanics simulation usually employs.

Its better to abstract everything away by a neural net, apparently...

Re: AlphaFold: a solution to a 50-year-old grand challenge in biology

#622

Post by adwn »

calf wrote: post #527
softwaredoug wrote: post #487

Earlier quoted context omitted.

> I don’t think we would do ourselves a service by not recognizing that what just happened presents a serious indictment of academic science. Much like other fields, I do begin to question the academic structure to making advances. It appears something is rotten in the state of academia. Oddly it's academia doing incremental improvements to existing methods but industry making novel leaps and bounds... The other majo…

Is this a scientific advance or a technological one though? Academia doesn't have the capital like industry or government to implement the latter. In America it's small small groups of young students led by a professor. Not full grown PhDs with Google levels of staff and money.

> Is this a scientific advance or a technological one though?

Where's the difference?

(this is a genuine question, I'm not trying to trick you)

Re: AlphaFold: a solution to a 50-year-old grand challenge in biology

#623

Post by ben_w »

FeepingCreature wrote: post #600
chubs wrote: post #572

Earlier quoted context omitted.

The answer i've read is that he _logically_ precedes it, not _temporally_. But yes that only makes a tad more sense :)

That's a distinction without a difference though.

There is a potential difference, I think.

Consider if this universe exists only as a simulation (I’ve met some theists making this category of comparison but with different language). The laws of physics are identical in both directions for the arrow of time, so the starting point of the simulation from the point one view of the outside universe can be any point in time from the perspective of the inhabitants.

In this case, the “before” in the outer universe is a logical rather than temporal one from the point of view of us inhabitants.

(Disclaimer: my philosophy qualification is really bad)

Re: AlphaFold: a solution to a 50-year-old grand challenge in biology

#624

Post by Valakas »

ramraj07 wrote: post #149
EgoIncarnate wrote: post #88

"AlphaFold achieves a median score of 87.0 GDT". Game changing, and a huge improvement, but not 100% solved. Also this is for static folding. Dynamic folding and interaction is a much harder problem. Those need to be tackled too before I would consider protein folding 'solved'.

It's probably never going to be solved though right. To truly solve protein folding we'd have to have a program that can stimulate a small but still significant system at the QM level; looks like deep learning can get us 60% (conservatively estimating the whole problem domain ) but not all the edge cases, just like it did in other problem domains as well.

'Never' is a long timespan :) It will be solved, sooner or later. The universe will be fully understood and manipulated. By us, a modified version of us, or some other entity, perhaps even one we created. 300 years ago 'electricity' wasn't even a word. We can imagine what 500 years into the future will be, with an exponentially more advanced tech, worse than a caveman could imagine the concept of 'machine learning'.

Re: AlphaFold: a solution to a 50-year-old grand challenge in biology

#625

Post by dwheeler »

calf wrote: post #527
softwaredoug wrote: post #487

Earlier quoted context omitted.

> I don’t think we would do ourselves a service by not recognizing that what just happened presents a serious indictment of academic science. Much like other fields, I do begin to question the academic structure to making advances. It appears something is rotten in the state of academia. Oddly it's academia doing incremental improvements to existing methods but industry making novel leaps and bounds... The other majo…

Is this a scientific advance or a technological one though? Academia doesn't have the capital like industry or government to implement the latter. In America it's small small groups of young students led by a professor. Not full grown PhDs with Google levels of staff and money.

I would claim that this is a technological advance that is likely to lead to many scientific advances.

Perhaps a good analogy are the inventions of the microscope and telescope. They were advances in technology, which then led to advances in science. I don't know if this will have the same effect as the microscope and telescope, but it would be great if it did. It certainly seems extremely promising.

Re: AlphaFold: a solution to a 50-year-old grand challenge in biology

#627

Post by Veedrac »

whimsicalism wrote: post #5
partingshots wrote: post #3

I continue to be impressed by how quickly DeepMind has managed to progress in such a short time. CASP13 was a shocker to all of us I think, but many were skeptical as to the longevity of the performance DeepMind was able to achieve. I believe with CASP14 rankings now released, it's safe to say that they've proven themselves. Congratulations to the team! This work will have far reaching impacts, and I hope that you co…

Progress like this was, in my view, inevitable after the invention of unsupervised transformers. It'll be genetics next. e: although AlphaFold appears to be convolutionally based! I suspect that'll change soon.

> e: although AlphaFold appears to be convolutionally based! I suspect that'll change soon.

“For the latest version of AlphaFold, used at CASP14, we created an attention-based neural network system”

?

Re: AlphaFold: a solution to a 50-year-old grand challenge in biology

#628

Post by dekhn »

deeviant wrote: post #562
dekhn wrote: post #87

Earlier quoted context omitted.

you give pharma too much credit. I had built a previous system to do something similar to this that produced excellent results and tried to give it away for free to Genentech, which ignored me. They said it didn't work for their purchasing department.

I feel that the "produced excellent results" has a lot of unpack there. It obviously wasn't scoring 90+ in CASP. Actually, after reading your linked blog post, it's pretty obvious why they weren't exactly chomping on the bit: "To gain insights into the receptor’s dynamics, Kai performed detailed molecular simulations using hundreds of millions of core hours on Google’s infrastructure, generating hundreds of terabytes…

If you note, the paper has an enormous number of citations from pharma, since modelling protein dynamics, rather than static structure, is key to understsanding ligand binding firehose.

You can see another paper we published where attacking the problem with a firehose helped unlock a long-standing problem: https://pubmed.ncbi.nlm.nih.gov/24265211/ in this case, showed that bond angles need to be 'free' to move rather than fully constrained,to build the most accurate models. This paper is also heavily cited amongst protein modellers.

It is correct that the MD simulations don't directly work for CASP- in a sense, the results they produce directly disagree with CASP's mental model of protein structure and function.

Re: AlphaFold: a solution to a 50-year-old grand challenge in biology

#629

Post by C4stor »

softwaredoug wrote: post #487
cs702 wrote: post #118

Two years ago, after DeepMind submitted its first set of predictions to CASP (Critical Assessment of protein Structure Prediction), Mohammed AlQuraishi, an expert in the field, asked, "What just happened?" https://moalquraishi.wordpress.com/2018/12/09/alphafold-casp... Now that the problem of static protein structure prediction has been solved (prediction errors are below the threshold that is considered acceptable i…

> I don’t think we would do ourselves a service by not recognizing that what just happened presents a serious indictment of academic science. Much like other fields, I do begin to question the academic structure to making advances. It appears something is rotten in the state of academia. Oddly it's academia doing incremental improvements to existing methods but industry making novel leaps and bounds... The other majo…

The deepmind research team is essentially all PhD though, so it seems academia isn't doing such a bad job.

Re: AlphaFold: a solution to a 50-year-old grand challenge in biology

#630

Post by complexmango »

drusepth wrote: post #535
mensetmanusman wrote: post #523

Earlier quoted context omitted.

That would require the AI to exist outside of time and space.

Well, this relies on the assumption that a God also inherently exists outside of time and space, which is debatable even among religious scholars.

There is an in depth explanation in Zen, Buddhism and Hinduism of this phenomenon.

I would suggest reading anything by Nisargadatta Maharaj, who expanded on this in detail to questioners from all over the world who came to his humble dwellings in a Mumbai tenement to observe him. I’d suggest starting with ‘I am That’, available on Amazon, iBooks etc.

He claimed to be outside of time and space himself.

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