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AlphaFold 3 predicts the structure and interactions of life's molecules

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Re: AlphaFold 3 predicts the structure and interactions of life's molecules

#141

Post by dekhn »

nybsjytm wrote: post #114
dekhn wrote: post #83

Earlier quoted context omitted.

Yep, I know Paul Adams (used to work with him at Berkeley Lab) and that's exactly the paper he'd publish. If you read that paper carefully (as we all have, since it's the strongest we've seen from the crystallography community so far) they're basically saying the results from AF are absolutely excellent, and fit for purpose. (put another way: if Paul publishes a paper saying your structure predictions have issues, an…

I don't know Paul Adams, so it's hard for me to know how to interpret your post. Is there anything else I can read that discusses the accuracy of AlphaFold?

Yes, https://predictioncenter.org/casp15/ https://www.sciencedirect.com/science/article/pii/S0959440X2... https://dasher.wustl.edu/bio5357/readings/oxford-alphafold2....

I can't find the link at the moment but from the perspective of the CASP leaders, AF2 was accurate enough that it's hard to even compare to the best structures determined experimentally, due to noise in the data/inadequacy of the metric.

A number of crystallographers have also reported that the predictions helped them find errors in their own crystal-determined structures.

If you're not really familiar enough with the field to understand the papers above, I recommend spending more time learning about the protein structure prediction problem, and how it relates to the epxerimental determination of structure using crystallography.

Re: AlphaFold 3 predicts the structure and interactions of life's molecules

#142

Post by dekhn »

fikama wrote: post #100
dekhn wrote: post #66

Earlier quoted context omitted.

I don't trust NMR structures in nearly all cases. The reasons are complex enough that I don't think it's worthwhile to discuss on Hacker News.

Hmm, I would say its always worth to share knowledge. Could you paste some links or maybe type a few key-words for anyone willing to reasearch the topic further on his own.

Read this, and recursively (breadth-first) read all its transitive references: https://www.sciencedirect.com/science/article/pii/S096921262...

Re: AlphaFold 3 predicts the structure and interactions of life's molecules

#143

Post by 6gvONxR4sf7o »

moconnor wrote: post #32

Stepping back, the high-order bit here is an ML method is beating physically-based methods for accurately predicting the world. What happens when the best methods for computational fluid dynamics, molecular dynamics, nuclear physics are all uninterpretable ML models? Does this decouple progress from our current understanding of the scientific process - moving to better and better models of the world without human-int…

"Best methods" is doing a lot of heavy lifting here. "Best" is a very multidimensional thing, with different priorities leading to different "bests." Someone will inevitably prioritize reliability/accuracy/fidelity/interpretability, and that's probably going to be a significant segment of the sciences. Maybe it's like how engineers just need an approximation that's predictive enough to build with, but scientists still want to understand the underlying phenomena. There will be an analogy to how some people just want an opaque model that works on a restricted domain for their purposes, but others will be interested in clearer models or unrestricted/less restricted domain models.

It could lead to a very interesting ecosystem of roles.

Even if you just limit the discussion to using the best model of X to design a better Y, limited to the model's domain of validity, that might translate the usage problem to finding argmax_X of valueFunction of modelPrediction of design of X. In some sense a good predictive model is enough to solve this with brute force, but this still leaves room for tons of fascinating foundational work. Maybe you start to find that the (wow so small) errors in modelPrediction are correlated with valueFunction, so the most accurate predictions don't make it the best for argmax (aka optimization might exploit model errors rather than optimizing the real thing). Or maybe brute force just isn't computationally feasible, so you need to understand something deeper about the problem to simplify the optimization to make it cheap.

Re: AlphaFold 3 predicts the structure and interactions of life's molecules

#144

Post by lupire »

scotty79 wrote: post #112
moconnor wrote: post #32

Stepping back, the high-order bit here is an ML method is beating physically-based methods for accurately predicting the world. What happens when the best methods for computational fluid dynamics, molecular dynamics, nuclear physics are all uninterpretable ML models? Does this decouple progress from our current understanding of the scientific process - moving to better and better models of the world without human-int…

We should be thankful that we live in the universe that obeys math simple enough to comprehend that we were able to reach that level. Imagine if optis was complex enough that it would require ML model to predict anything. We'd be in permanent stone age without a way out.

What would a universe look like that lacked simple things, and somehow only complex things existed?

It makes me think of how Gaussian integers have irreducibles but not prime numbers, where some large things cannot be uniquely expressed as combination of smaller things.

Re: AlphaFold 3 predicts the structure and interactions of life's molecules

#145

Post by _just7_ »

HanClinto wrote: post #101
boxed wrote: post #91

Earlier quoted context omitted.

Are you an editor or reviewer?

Good question. Also makes me wonder -- where's the line? Is it reasonable to have "layperson" reviewers? Is it reasonable to think that regular citizens could review such content?

No, infact most journals have peer reviews cordoned off, not viewable to the general public.

Re: AlphaFold 3 predicts the structure and interactions of life's molecules

#146

Post by obmelvin »

mhrmsn wrote: post #24
Metacelsus wrote: post #4

From: https://www.nature.com/articles/d41586-024-01383-z >Unlike RoseTTAFold and AlphaFold2, scientists will not be able to run their own version of AlphaFold3, nor will the code underlying AlphaFold3 or other information obtained after training the model be made public. Instead, researchers will have access to an ‘AlphaFold3 server’, on which they can input their protein sequence of choice, alongside a selection of…

Also no commercial use, from the paper: > AlphaFold 3 will be available as a non-commercial usage only server at https://www.alphafoldserver.com , with restrictions on allowed ligands and covalent modifications. Pseudocode describing the algorithms is available in the Supplementary Information. Code is not provided.

If you need to submit to their server, I don't know who would use it for commercial reasons anyway. Most biotech startups and pharma companies are very careful about entering sequences into online tools like this.

Re: AlphaFold 3 predicts the structure and interactions of life's molecules

#147

Post by lupire »

perihelions wrote: post #102
l33tman wrote: post #10

Earlier quoted context omitted.

That sucks a bit. I was just wondering why they are touting that 3rd party company in their own blog post, who commercialise research tools, as well. Maybe there are some corporate agreements with them that prevents them from opening the system... Imagine the goodwill for humanity for releasing these pure research systems for free. I just have a hard time understanding how you can motivate to keep it closed. Let's ho…

- "Imagine the goodwill for humanity for releasing these pure research systems for free." The entire point[0] is that they want to sell an API to drug-developer labs, at exclusive-monopoly pricing. Those labs in turn discover life-saving drugs, and recoup their costs from e.g. parents of otherwise-terminally-ill children—again, priced as an exclusive monopoly. [0] As signaled by "it is not possible to obtain structur…

The parents of those otherwise terminally ill children disagree with you in the strongest possible terms.

Re: AlphaFold 3 predicts the structure and interactions of life's molecules

#148

Post by gmarx »

xanderlewis wrote: post #43
moconnor wrote: post #32

Stepping back, the high-order bit here is an ML method is beating physically-based methods for accurately predicting the world. What happens when the best methods for computational fluid dynamics, molecular dynamics, nuclear physics are all uninterpretable ML models? Does this decouple progress from our current understanding of the scientific process - moving to better and better models of the world without human-int…

It depends whether the value of science is human understanding or pure prediction. In some realms (for drug discovery, and other situations where we just need an answer and know what works and what doesn’t), pure prediction is all we really need. But if we could build an uninterpretable machine learning model that beats any hand-built traditional ‘physics’ model, would it really be physics? Maybe there’ll be an inter…

The success of these ML models has me wondering if this is what Quantum Mechanics is. QM is notoriously difficult to interpret yet makes amazing predictions. Maybe wave functions are just really good at predicting system behavior but don't reflect the underlying way things work.

OTOH, Newtonian mechanics is great at predicting things under certain circumstances yet, in the same way, doesn't necessarily reflect the underlying mechanism of the system.

So maybe philosophers will eventually tell us the distinction we are trying to draw, although intuitive, isn't real

Re: AlphaFold 3 predicts the structure and interactions of life's molecules

#149

Post by arolihas »

ein0p wrote: post #81

I’m inclined to ignore such pr fluff until they actually demonstrate a _practical_ result. Eg. cure some form of cancer or some autoimmune disease. All this “prediction of structure” has been in the news for years, and it seems to have resulted in nothing practically usable IRL as far as I can tell. I could be wrong of course, I do not work in this field

There are a few AI-designed drugs in various phases of clinical trials, these things take time.

Re: AlphaFold 3 predicts the structure and interactions of life's molecules

#150

Post by kolinko »

optimalsolver wrote: post #139
pen2l wrote: post #132

Earlier quoted context omitted.

The most moneyed and well-coordinated organizations have honed a large hammer, and they are going to use it for everything, and so almost certainly future big findings in the areas you mention, probabilistically inclined models coming from ML will be the new gold standard. But yet the only thing that can save us from ML will be ML itself because it is ML that has the best chance to be able to extrapolate patterns fro…

Spoiler: "Interpretable ML" will optimize for output that either looks plausible to humans, reinforces our preconceptions, or appeals to our aesthetic instincts. It will not converge with reality.

That is not considered interpretable then, and I think most people working in the field are aware of this gotcha.

Iirc when EU required banks to have interpretable rules for loans, a plain explanation was not considered enough. What was required was a clear process that was used from the beginning - i.e. you can use an AI to develop an algorightm to make a decision, but you can’t use AI to make a decision and explains reasons afterwards.

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