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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

#481

Post by flobosg »

ashtonbaker wrote: post #478
heycosmo wrote: post #412

Fascinating! AlphaFold (and other competitors) seem to use MSA (Multiple Sequence Aligment) and this (brilliant) idea of co-evolving residues to build an initial graph of sections of protein chain that are likely proximal. This seems like a useful trick for predicting existing biological structures (i.e. ones that evolved) from genomic data. I wonder (as very much a non-biologist), do MSA-based approaches also help u…

This is a really insightful question and I need to take some time to fully understand the ensuing discussion. If my speculation is correct, then drug discovery should use a process of genetic programming, using something like this to score the resulting amino acid sequences. I'm wondering if an artificial process of evolution would be sufficient to satisfy the co-evolution assumption here.

> I'm wondering if an artificial process of evolution would be sufficient to satisfy the co-evolution assumption here.

In principle yes, if you can generate a significant number of artificially evolved variants that are folded/functional.

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

#483

Post by ribrars »

uuuuuuuuuuuu wrote: post #475

I feel like DeepMind has a disproportionately large scientific impact relative to its resource pool. How would one (or a group) go about replicating its success?

I think the key here to replicating the success is the deployment of deep learning effectively. But I would argue that deepmind's resource pool is immense, it's backed by Google. The resources of GPU's (and more advanced TPU's) are in abundance... not to mention the many brilliant PhD scientists who work there.

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

#484

Post by shawnz »

Rochus wrote: post #472
Rochus wrote: post #168

Earlier quoted context omitted.

Thank you very much; almost forgot I did a Phd on the subject ;-) But anyway your answer does not contradict my statement. What you say belongs to the basics of molecular biology, but does not justify that DNA should be considered when determining the structure of proteins. In practice, the amino acid sequence is always already present.

For the sceptics: if you read the referenced article, you will see that it is about protein structure determination by means of deep neural networks. It's not about gene expression, which is a different topic. What benefit does it have to respond to the question " What are the immediate real-world applications of this " (see above) by reciting some molecular biology dogmas from text books mixed with misconceptions, i…

Nobody is suggesting that this research has anything to do with gene expression or anything like that. Their point was simply that we now have better tools to actually see the meaning/effect of a given DNA sequence.

Also, there is no need to passive-agressively highlight your credentials. I already researched them before replying.

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

#485

Post by dmix »

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…

> However, if the (AlphaFold-adjusted) trend in the above figure were to continue, then perhaps in two CASPs, i.e. four years, we’ll actually get to a point where the problem can be called solved, in terms of gross topology (mean GDT_TS ~ 85% or so). Interesting prediction within.

It turned out only to be one more year instead of four (depending on whether getting to the 90~ range is "solved".

I'm curious to see if AlphaFold can do even better the next two years.

Those last mile percentages always tend to be small anyway.

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

#487

Post by softwaredoug »

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 major case in point being NLP

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

#488

Post by Rochus »

shawnz wrote: post #484
Rochus wrote: post #472

Earlier quoted context omitted.

For the sceptics: if you read the referenced article, you will see that it is about protein structure determination by means of deep neural networks. It's not about gene expression, which is a different topic. What benefit does it have to respond to the question " What are the immediate real-world applications of this " (see above) by reciting some molecular biology dogmas from text books mixed with misconceptions, i…

Nobody is suggesting that this research has anything to do with gene expression or anything like that. Their point was simply that we now have better tools to actually see the meaning/effect of a given DNA sequence. Also, there is no need to passive-agressively highlight your credentials. I already researched them before replying.

I rather think most people comment without even having a look at the referenced article. And since when is the reference to a qualification considered aggressive? If your doctor hangs his doctor's certificate on the wall, is he "passive-aggressive"? Pretty weird.

> that we now have better tools to actually see the meaning/effect of a given DNA sequence

Note that the "meaning/effect" of a DNA segment encoding a protein is known and unrelated to the protein folding process. The protein gets its conformation after the translation process.

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

#489

Post by [deleted] »

Rochus wrote: post #488
shawnz wrote: post #484

Earlier quoted context omitted.

Nobody is suggesting that this research has anything to do with gene expression or anything like that. Their point was simply that we now have better tools to actually see the meaning/effect of a given DNA sequence. Also, there is no need to passive-agressively highlight your credentials. I already researched them before replying.

I rather think most people comment without even having a look at the referenced article. And since when is the reference to a qualification considered aggressive? If your doctor hangs his doctor's certificate on the wall, is he "passive-aggressive"? Pretty weird. > that we now have better tools to actually see the meaning/effect of a given DNA sequence Note that the "meaning/effect" of a DNA segment encoding a protei…

[deleted]

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

#490

Post by rsiqueira »

pmastela wrote: post #371
ramraj07 wrote: post #236

Earlier quoted context omitted.

The most amazing part: > The organizers even worried DeepMind may have been cheating somehow. So Lupas set a special challenge: a membrane protein from a species of archaea, an ancient group of microbes. For 10 years, his research team tried every trick in the book to get an x-ray crystal structure of the protein. “We couldn’t solve it.” > But AlphaFold had no trouble. It returned a detailed image of a three-part pro…

Like the old Arthur C. Clark quote goes: “Any sufficiently advanced technology is indistinguishable from magic” -- unless it might be cheating in which case throw them a curve ball. Kudos to the DeepMind team for making magic happen.

"A sufficiently advanced Artificial Intelligence would be indistinguishable from God." (Way Of The Future - AI Church)
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