7 ms·

AlphaFold developers win $3M breakthrough prize

196 points by dopu 4y ago

xkgt 4y ago
Is there a good summary of how AlphaFold has made a difference in the few years since it has been released. I was quite excited to hear their success in 2020, so I am curious to see where have we got to in 2 years and what is in the horizon.
mellosouls 4y ago
Full list: https://breakthroughprize.org/News/73 https://breakthroughprize.org/News/73
dekhn 4y ago
I expect them to get the Nobel prize in Chemistry in about two-three weeks.
- amrrs 4y ago
  Isn't that quite a big claim? My question, Is that work with Alphafold that significant that it warrants the eyes of Nobel committee? Genuinely curious.
  - ISL 4y ago
    It could also draw the attention of the Physics Nobel committee. Oodles of physicists have been working on the folding inverse-problem for decades.
  - dhdc 4y ago
    The joke is that the Nobel prize in chemistry is often awarded to non-chemists.
  - _yb2s 4y ago
    In my opinion, absolutely. The "protein folding problem" has been widely regarded as one of the biggest challenges in molecular biology for over half a century, and Alphafold has effectively solved it. I would put this up there with Sanger winning the prize for discovering how to sequence DNA and Kary Mullis for inventing PCR... this will have widespread implications for allowing us to understand, and even design proteins.
    - dekhn 4y ago
      But they didn't solve the protein folding problem. They solved a simpler problem, protein structure prediction. What is important about their discovery is that we now know for certain that a judicious combination of expensive-to-obtain structure information, and easy-to-obtain protein sequence relationships can be used to build a generalized protein structure predictor (it can predict structures with no prior example of a fold, although there are limits)... and you don't have solve the general folding problem to do it. You do not need to know the path, to get to the destination! Many of us in the field expected this to be true but there wasn't any really good example to point to that was widely accepted by the community. And in the ~year or so since this was demonstrated, the community has already found a wide range of uses for this that have validated the structure predictions and demonstrated their utility- using open codes and models.
- mxwsn 4y ago
  The Nobel committee usually prefers to wait and evaluate longer-term impact, so I'd be quite surprised. CRISPR was obviously revolutionary in 2013 (imo, more than alphafold), and won the Nobel in 2020.
  - echelon 4y ago
    CRISPR is a revolutionary tool. AlphaFold doesn't solve folding. It makes metaheuristic guesses without writing a bunch of quantum chemistry, statistical physics, thermodyanamics, and topology maths / algorithms. I don't mean to downplay AlphaFold, but we haven't solved protein folding yet. This press is really getting ahead of itself.
    - frozencell 4y ago
      Echelon is revolutionary too, Peace Nobel prize worthy.
    - m00x 4y ago
      I have a Msc in microbio, not biochem, but my understanding is that proteins don't have a constant shape. They vibrate, interact with other molecules, etc. You won't have a perfect answer unless you want to predict its shape in a vacuum, which wouldn't be very useful either way. Having it "close enough" is already extremely useful. There are definitely edge cases where it gets it wrong, but there are always edge cases in ML. More data = better results with the same architecture. Tons of things that won Nobel prizes weren't 100% accurate, it's not a prize for solving science, rather a prize for advancing science. My wife is a neurobiologist and the impact of this advance is groundbreaking for her work.
      - bongoman37 4y ago
    - acapybara 4y ago
      This reminds me of the criticisms of Copilot (GPT-3 application to generate computer code). Many engineers will say it doesn't code. It just regurgitates and remixes the data it was trained on. It just makes "meta-heuristic guesses." But anyone taking an honest and objective view of it can see that Copilot does add value. It's no substitute for a real, human, engineer, but it clearly adds value. I don't think AlphaFold would get to this level of funding, resource commitment, etc. if it was adding 0 value. Being a domain expert, I'm curious what value, if any, you think a large transformer model could add to the domain of protein folding. Is it really zero value, in your view?
- epvgwwqe 4y ago
  Seems pretty doubtful. Is there any high impact scientific discovery that AlphaFold directly enabled at this point?
  - dekhn 4y ago
    The Nobel Prize does not only award scientists for enabling high impact discoveries, but occasionally to people who make a major discovery that has no immediate impact. There is literature dribbling out from folks using AlphaFold models, but that's not what they would be awarding here. This was a long-standing problem that was convincingly solved.
    - epvgwwqe 4y ago
      If there is precedent for that, then sure they could win.
- gone35 4y ago
  Not with recent results in Nature I believe reporting glaring mispredictions. Lots of promotion notwithstanding, AlphaFold may not be usable yet.
  - dekhn 4y ago
    Do you have links to that? have not seen those.
    - gone35 4y ago
      Yes. Posted here (and with some important qualifications): https://news.ycombinator.com/item?id=32948345 https://news.ycombinator.com/item?id=32948345
  - gone35 4y ago
    Not Nature but Molecular Systems Biology [2], apologies, in the context of reverse docking for antibiotics discovery: "We confirm extensive promiscuity, but find that the average area under the receiver operating characteristic curve (auROC) is 0.48, indicating weak model performance." Derek Lowe had a post about this earlier this month [1] (which includes important qualifications I failed to omit). [1] "Benchmarking AlphaFold-enabled molecular docking predictions for antibiotic discovery", Molecular Systems Biology 2022 18:e11081 https://doi.org/10.15252/msb.202211081 https://doi.org/10.15252/msb.202211081 [2] "Not AlphaFold's Fault", September 7 2022, https://www.science.org/content/blog-post/not-alphafold-s-fault https://www.science.org/content/blog-post/not-alphafold-s-fa...
    - flobosg 4y ago
      This is already known. Structural models are usually not well suited for protein-ligand docking, where proper pocket modelling and accurate side chain positioning are key for the determination of true positive hits.
  - dekhn 4y ago
    Sorry, you don't know what you're talking about. Nobody is truly claiming these models can be used directly for drug discovery (well, some people claim that; but they're wrong). We already knew that, though- the same problem exists with high quality crystal structures. What would be more interesting is if we did a whole bunch of crystal or cryo-EM structures far from what we've previously determined and demonstrate whether alphafold could make out-of-class predictions for them.
- nnm 4y ago
  From my chat with friends who work in the area of drug design, AlphaFold is accurate for overall structure, but is not that accurate for predicting structure around interaction locations.
GeorgeJIrwin 4y ago
When will we see the result of this breakthrough in our daily life? The article mentions: > So far, the data have been harnessed to tackle problems ranging from antibiotic resistance to crop resilience. Is any of them is about to be used in our daily life and solve a major problem?
- krastanov 4y ago
  More resilient crops and reliable antibiotics is "daily life" and "major problem".
- TaupeRanger 4y ago
  Except the article is wrong. "Tackle" is doing a lot of work...it doesn't actually mean anything in this case, as AlphaFold has not been shown to help in antibiotic resistance (compounds found using it haven't even been tested in the real world), and has not increased crop resilience in any independent peer reviewed studies or in the real world. It's all still hype at this point.
  - aardvarkr 4y ago
    “It’s all still hype at this point” implies this is vaporware when it’s a real thing that has solved one of the biggest roadblocks in microbiology. Your claim is analogous to lithium batteries, invented in 1976, taking 25+ years before completely DOMINATING the modern battery market. Science takes time to go from the research stage to mass market adoption. Level set your expectations.
    - TaupeRanger 4y ago
      You picked a convenient analogy. No one knew whether lithium batteries were going to be as useful as they were. Much additional testing and work was necessary to prove it. It COULD have failed. Same with Alpha Fold. Abandon your expectations.
    - mudrockbestgirl 4y ago
      Survivorship bias. There are 100x more tools and ideas that never got adopted, you just haven't heard of them.
deleted 4y ago
[deleted]
Royi 4y ago
I wonder what people, in 100 years, would say about our era. One might research, work hard and solve a problem that might change the course of development of a major field and win a recognition by $3M while someone which fills few numbers on a lottery ticket may earn 1-2 folds more. I wish the system would give this kind of efforts and stories a bigger exposure, recognition and compensation. Edit: The idea was about the prize amount, not those specific people. It wasn't the best choice, but the idea was that even as a statement, prizes for scientific achievements should be higher so they will be an extreme to all people to recognize and strive for. I guess one could find a better analogy than what I had in mind.
- derac 4y ago
  The lottery isn't comparable, first of all it's a money raising scheme. I'm sure the alphafold team is well compensated. Almost certainly making high 6 figures. Alphafold got a massive amount of well-deserved coverage as well.
- Drakim 4y ago
  Your point is good but the direction of your contempt is misplaced. Lottery winners accounts for a tiny fraction of people who have unearned and undeserved wealth, and in terms of how many people they screwed over to get to riches, they are like angels in comparison to other rich people.
  - Royi 4y ago
    I agree with you. I should have made a better choice than lottery. My intention was that the needle which sets the reward for research, long life work pursuing the solution of a problem should move to the right and get those people more. $3M isn't enough in our days to recognize remarkable work in my opinion. Yes, one of them made a lot of money, but is it true for all the past winners of this prize?
    - nightski 4y ago
      I'm curious, what would be the right amount in your opinion? How would you value it?
refulgentis 4y ago
Quite funny to me that: - for the first time, there isn't mountains and mountains of trolling in an Alphafold thread and the comments are _very_ quiet - the only reason why is a new account tried doing the trolling - comment is instadead without any manual flagging - but, people are afraid to post given the one try in 3 hours is dead
420official 4y ago
> ... were recognized for creating the tool that has predicted the 3D structures of almost every known protein on the planet. I wonder if relying on a tool that doesn't 100% accurately represent reality could have a negative effect on future research
- deleted 4y ago
  [deleted]
- flobosg 4y ago
  > that doesn't 100% accurately represent reality It could be argued that this is the case of every scientific tool ever used.
- JamesBarney 4y ago
  Current methods are not 100% accurate either. No study is 100%. Honestly the only field that has a P value that comes close to 100% is physics. Even medicine which is far more rigorous than most fields fails quite often in phase 3 trials after having vetted it in phase 2.
  - tedsanders 4y ago
    Even physics is nowhere close to “100% accurate.” Most fields of physics approximate many body problems that are infeasible to compute, let alone fully specify. E.g. Astrophysics, solid state physics, nuclear physics, etc. Practitioners regularly use empirically measured parameters like cross-sectional scattering areas, and those parameters are updated and narrowed over time.
- dekhn 4y ago
  The predictions made by AlphaFold are now indistinguishable from experimental data collection error so folks aren't super concerned. Anyway structures are typically qualititaive tools useful for thinking about proteins, rather than direct targets of computational predictions (hasn't stopped people from trying).
- stainablesteel 4y ago
keepquestioning 4y ago
What's the next AlphaFold? I want to get in early
- m00x 4y ago
  BetaFold
hanniabu 4y ago
Does this solve protein folding?
j7ake 4y ago
Congrats to DeepMind! But why did they give the prize to just two members of the alphafold team rather than everyone on the team? By contrast, the breakthrough prize in physics was awarded to the entire event horizon telescope collaboration for their image of the supermassive black hole. I would have assumed that the prize for alphafold would also been awarded to the whole team.
- KKKKkkkk1 4y ago
  One of the winners, Demis Hassabis, is the head of DeepMind, an org of about 1,000 employees and an annual budget of about $1 bn. One really has to wonder how closely he was involved in the work given his administrative responsibilities.
  - crakenzak 4y ago
    Completely unrelated, but whenever I see stats like "Deepmind, an org of about 1,000 employees" and then contrast that to the amount of interesting advancements they're making, I cant help but wonder where we'd be with 100,000+ people working on these type of issues. Kind of how most medical advancements come out of the US, which makes up only <4.25% of world population. I know orgs dont scale like that and there are hits to productivity with orgs getting less lean but still.
    - survirtual 4y ago
      Get rid of hierarchies and there might be 100,000 people working on these problems. The masses are limited by the ceiling of greedy egomaniacs. So tired of seeing singular human names take credit for the works of thousands.

196 points by dopu 4y ago

xkgt 4y ago

Is there a good summary of how AlphaFold has made a difference in the few years since it has been released. I was quite excited to hear their success in 2020, so I am curious to see where have we got to in 2 years and what is in the horizon.

mellosouls 4y ago

Full list: https://breakthroughprize.org/News/73 https://breakthroughprize.org/News/73

dekhn 4y ago

I expect them to get the Nobel prize in Chemistry in about two-three weeks.

amrrs 4y ago
Isn't that quite a big claim? My question, Is that work with Alphafold that significant that it warrants the eyes of Nobel committee? Genuinely curious.
- ISL 4y ago
  It could also draw the attention of the Physics Nobel committee. Oodles of physicists have been working on the folding inverse-problem for decades.
- dhdc 4y ago
  The joke is that the Nobel prize in chemistry is often awarded to non-chemists.
- _yb2s 4y ago
  In my opinion, absolutely. The "protein folding problem" has been widely regarded as one of the biggest challenges in molecular biology for over half a century, and Alphafold has effectively solved it. I would put this up there with Sanger winning the prize for discovering how to sequence DNA and Kary Mullis for inventing PCR... this will have widespread implications for allowing us to understand, and even design proteins.
  - dekhn 4y ago
    But they didn't solve the protein folding problem. They solved a simpler problem, protein structure prediction. What is important about their discovery is that we now know for certain that a judicious combination of expensive-to-obtain structure information, and easy-to-obtain protein sequence relationships can be used to build a generalized protein structure predictor (it can predict structures with no prior example of a fold, although there are limits)... and you don't have solve the general folding problem to do it. You do not need to know the path, to get to the destination! Many of us in the field expected this to be true but there wasn't any really good example to point to that was widely accepted by the community. And in the ~year or so since this was demonstrated, the community has already found a wide range of uses for this that have validated the structure predictions and demonstrated their utility- using open codes and models.
mxwsn 4y ago
The Nobel committee usually prefers to wait and evaluate longer-term impact, so I'd be quite surprised. CRISPR was obviously revolutionary in 2013 (imo, more than alphafold), and won the Nobel in 2020.
- echelon 4y ago
  CRISPR is a revolutionary tool. AlphaFold doesn't solve folding. It makes metaheuristic guesses without writing a bunch of quantum chemistry, statistical physics, thermodyanamics, and topology maths / algorithms. I don't mean to downplay AlphaFold, but we haven't solved protein folding yet. This press is really getting ahead of itself.
  - frozencell 4y ago
    Echelon is revolutionary too, Peace Nobel prize worthy.
  - m00x 4y ago
    I have a Msc in microbio, not biochem, but my understanding is that proteins don't have a constant shape. They vibrate, interact with other molecules, etc. You won't have a perfect answer unless you want to predict its shape in a vacuum, which wouldn't be very useful either way. Having it "close enough" is already extremely useful. There are definitely edge cases where it gets it wrong, but there are always edge cases in ML. More data = better results with the same architecture. Tons of things that won Nobel prizes weren't 100% accurate, it's not a prize for solving science, rather a prize for advancing science. My wife is a neurobiologist and the impact of this advance is groundbreaking for her work.
    - bongoman37 4y ago
  - acapybara 4y ago
    This reminds me of the criticisms of Copilot (GPT-3 application to generate computer code). Many engineers will say it doesn't code. It just regurgitates and remixes the data it was trained on. It just makes "meta-heuristic guesses." But anyone taking an honest and objective view of it can see that Copilot does add value. It's no substitute for a real, human, engineer, but it clearly adds value. I don't think AlphaFold would get to this level of funding, resource commitment, etc. if it was adding 0 value. Being a domain expert, I'm curious what value, if any, you think a large transformer model could add to the domain of protein folding. Is it really zero value, in your view?
epvgwwqe 4y ago
Seems pretty doubtful. Is there any high impact scientific discovery that AlphaFold directly enabled at this point?
- dekhn 4y ago
  The Nobel Prize does not only award scientists for enabling high impact discoveries, but occasionally to people who make a major discovery that has no immediate impact. There is literature dribbling out from folks using AlphaFold models, but that's not what they would be awarding here. This was a long-standing problem that was convincingly solved.
  - epvgwwqe 4y ago
    If there is precedent for that, then sure they could win.
gone35 4y ago
Not with recent results in Nature I believe reporting glaring mispredictions. Lots of promotion notwithstanding, AlphaFold may not be usable yet.
- dekhn 4y ago
  Do you have links to that? have not seen those.
  - gone35 4y ago
    Yes. Posted here (and with some important qualifications): https://news.ycombinator.com/item?id=32948345 https://news.ycombinator.com/item?id=32948345
- gone35 4y ago
  Not Nature but Molecular Systems Biology [2], apologies, in the context of reverse docking for antibiotics discovery: "We confirm extensive promiscuity, but find that the average area under the receiver operating characteristic curve (auROC) is 0.48, indicating weak model performance." Derek Lowe had a post about this earlier this month [1] (which includes important qualifications I failed to omit). [1] "Benchmarking AlphaFold-enabled molecular docking predictions for antibiotic discovery", Molecular Systems Biology 2022 18:e11081 https://doi.org/10.15252/msb.202211081 https://doi.org/10.15252/msb.202211081 [2] "Not AlphaFold's Fault", September 7 2022, https://www.science.org/content/blog-post/not-alphafold-s-fault https://www.science.org/content/blog-post/not-alphafold-s-fa...
  - flobosg 4y ago
    This is already known. Structural models are usually not well suited for protein-ligand docking, where proper pocket modelling and accurate side chain positioning are key for the determination of true positive hits.
- dekhn 4y ago
  Sorry, you don't know what you're talking about. Nobody is truly claiming these models can be used directly for drug discovery (well, some people claim that; but they're wrong). We already knew that, though- the same problem exists with high quality crystal structures. What would be more interesting is if we did a whole bunch of crystal or cryo-EM structures far from what we've previously determined and demonstrate whether alphafold could make out-of-class predictions for them.
nnm 4y ago
From my chat with friends who work in the area of drug design, AlphaFold is accurate for overall structure, but is not that accurate for predicting structure around interaction locations.

GeorgeJIrwin 4y ago

When will we see the result of this breakthrough in our daily life? The article mentions: > So far, the data have been harnessed to tackle problems ranging from antibiotic resistance to crop resilience. Is any of them is about to be used in our daily life and solve a major problem?

krastanov 4y ago
More resilient crops and reliable antibiotics is "daily life" and "major problem".
TaupeRanger 4y ago
Except the article is wrong. "Tackle" is doing a lot of work...it doesn't actually mean anything in this case, as AlphaFold has not been shown to help in antibiotic resistance (compounds found using it haven't even been tested in the real world), and has not increased crop resilience in any independent peer reviewed studies or in the real world. It's all still hype at this point.
- aardvarkr 4y ago
  “It’s all still hype at this point” implies this is vaporware when it’s a real thing that has solved one of the biggest roadblocks in microbiology. Your claim is analogous to lithium batteries, invented in 1976, taking 25+ years before completely DOMINATING the modern battery market. Science takes time to go from the research stage to mass market adoption. Level set your expectations.
  - TaupeRanger 4y ago
    You picked a convenient analogy. No one knew whether lithium batteries were going to be as useful as they were. Much additional testing and work was necessary to prove it. It COULD have failed. Same with Alpha Fold. Abandon your expectations.
  - mudrockbestgirl 4y ago
    Survivorship bias. There are 100x more tools and ideas that never got adopted, you just haven't heard of them.

deleted 4y ago

[deleted]

Royi 4y ago

I wonder what people, in 100 years, would say about our era. One might research, work hard and solve a problem that might change the course of development of a major field and win a recognition by $3M while someone which fills few numbers on a lottery ticket may earn 1-2 folds more. I wish the system would give this kind of efforts and stories a bigger exposure, recognition and compensation. Edit: The idea was about the prize amount, not those specific people. It wasn't the best choice, but the idea was that even as a statement, prizes for scientific achievements should be higher so they will be an extreme to all people to recognize and strive for. I guess one could find a better analogy than what I had in mind.

derac 4y ago
The lottery isn't comparable, first of all it's a money raising scheme. I'm sure the alphafold team is well compensated. Almost certainly making high 6 figures. Alphafold got a massive amount of well-deserved coverage as well.
Drakim 4y ago
Your point is good but the direction of your contempt is misplaced. Lottery winners accounts for a tiny fraction of people who have unearned and undeserved wealth, and in terms of how many people they screwed over to get to riches, they are like angels in comparison to other rich people.
- Royi 4y ago
  I agree with you. I should have made a better choice than lottery. My intention was that the needle which sets the reward for research, long life work pursuing the solution of a problem should move to the right and get those people more. $3M isn't enough in our days to recognize remarkable work in my opinion. Yes, one of them made a lot of money, but is it true for all the past winners of this prize?
  - nightski 4y ago
    I'm curious, what would be the right amount in your opinion? How would you value it?

refulgentis 4y ago

Quite funny to me that: - for the first time, there isn't mountains and mountains of trolling in an Alphafold thread and the comments are _very_ quiet - the only reason why is a new account tried doing the trolling - comment is instadead without any manual flagging - but, people are afraid to post given the one try in 3 hours is dead

420official 4y ago

> ... were recognized for creating the tool that has predicted the 3D structures of almost every known protein on the planet. I wonder if relying on a tool that doesn't 100% accurately represent reality could have a negative effect on future research

deleted 4y ago
[deleted]
flobosg 4y ago
> that doesn't 100% accurately represent reality It could be argued that this is the case of every scientific tool ever used.
JamesBarney 4y ago
Current methods are not 100% accurate either. No study is 100%. Honestly the only field that has a P value that comes close to 100% is physics. Even medicine which is far more rigorous than most fields fails quite often in phase 3 trials after having vetted it in phase 2.
- tedsanders 4y ago
  Even physics is nowhere close to “100% accurate.” Most fields of physics approximate many body problems that are infeasible to compute, let alone fully specify. E.g. Astrophysics, solid state physics, nuclear physics, etc. Practitioners regularly use empirically measured parameters like cross-sectional scattering areas, and those parameters are updated and narrowed over time.
dekhn 4y ago
The predictions made by AlphaFold are now indistinguishable from experimental data collection error so folks aren't super concerned. Anyway structures are typically qualititaive tools useful for thinking about proteins, rather than direct targets of computational predictions (hasn't stopped people from trying).
stainablesteel 4y ago

keepquestioning 4y ago

What's the next AlphaFold? I want to get in early

m00x 4y ago
BetaFold

hanniabu 4y ago

Does this solve protein folding?

j7ake 4y ago

Congrats to DeepMind! But why did they give the prize to just two members of the alphafold team rather than everyone on the team? By contrast, the breakthrough prize in physics was awarded to the entire event horizon telescope collaboration for their image of the supermassive black hole. I would have assumed that the prize for alphafold would also been awarded to the whole team.

KKKKkkkk1 4y ago
One of the winners, Demis Hassabis, is the head of DeepMind, an org of about 1,000 employees and an annual budget of about $1 bn. One really has to wonder how closely he was involved in the work given his administrative responsibilities.
- crakenzak 4y ago
  Completely unrelated, but whenever I see stats like "Deepmind, an org of about 1,000 employees" and then contrast that to the amount of interesting advancements they're making, I cant help but wonder where we'd be with 100,000+ people working on these type of issues. Kind of how most medical advancements come out of the US, which makes up only <4.25% of world population. I know orgs dont scale like that and there are hits to productivity with orgs getting less lean but still.
  - survirtual 4y ago
    Get rid of hierarchies and there might be 100,000 people working on these problems. The masses are limited by the ceiling of greedy egomaniacs. So tired of seeing singular human names take credit for the works of thousands.