6 ms·

While I am skeptical about yesterdays award in physics, these are totally deserved and spot on. There are few approaches that will accelerate the field of drug

While I am skeptical about yesterdays award in physics, these are totally deserved and spot on. There are few approaches that will accelerate the field of drug development and chemistry as a whole in a way that the works of these three people will. Congratulations!

ackbar03 2y ago
I was just wondering when they were going to award the alphafold2 guys the nobel after after seeing Hinton win the physics one. 100% agree, all three of them totally deserve this one. Baker's lab is pretty much keeping Deepmind in check at this point and ensuring open source research is keeping up. Hats off
- theGnuMe 2y ago
  Baker has been in the protein folding game for a long time and was the leader before Alphafold came in... His generative paper came out what last year (2023)? I mean this is a fast award cycle.
  - divbzero 2y ago
    David Baker’s RoseTTAFold was first released in 2021. [1]: https://www.science.org/doi/10.1126/science.abj8754 https://www.science.org/doi/10.1126/science.abj8754 [2]: https://cen.acs.org/analytical-chemistry/structural-biology/Accurate-protein-structure-prediction-AI/99/i26 https://cen.acs.org/analytical-chemistry/structural-biology/...
tomp 2y ago
Are they? What did Demis do?
- world2vec 2y ago
  He's founder and CEO of the AI lab that build Alphafold?
  - devilzhong 2y ago
    Then maybe Sergey and Larry should also get the prize since they founded Google, which owns Deepmind?
    - world2vec 2y ago
      They were not equal contributors to the seminal paper that got the prize. From another post in this thread: "These authors contributed equally: John Jumper, Richard Evans, Alexander Pritzel, Tim Green, Michael Figurnov, Olaf Ronneberger, Kathryn Tunyasuvunakool, Russ Bates, Augustin Žídek, Anna Potapenko, Alex Bridgland, Clemens Meyer, Simon A. A. Kohl, Andrew J. Ballard, Andrew Cowie, Bernardino Romera-Paredes, Stanislav Nikolov, Rishub Jain, Demis Hassabis"
    - theGnuMe 2y ago
      They bought it and it runs autonomously (or did mostly)
- onursurme 2y ago
  He writes software in different areas, so he has the potential to get a Nobel prize in any area soon.
- seydor 2y ago
  didn't he lead early successes in RL which popularized it and culminated in protein prediction?
cowsandmilk 2y ago
Both Rosetta and DeepMind have made contributions outside of protein structure prediction that are far more important for drug discovery.
mihaaly 2y ago
The physics prize should have went to Elon Musk! Also I really hope the Nobel Prize of Economics goes to Bill Gates! He facilitated sooo much advances by releasing Excel that this must be recognized! And based on this year's announcements so far I am not sure that my sarcastic comments should be taken as a joke!
- theGnuMe 2y ago
  Except Excel has introduced way to many bugs and how many people has it killed?
trott 2y ago
> There are few approaches that will accelerate the field of drug development and chemistry as a whole in a way that the works of these three people will. As the author of one such approach, I'm skeptical. AlphaFold 2 just predicts protein structures. The thing about proteins is that they are often related to each other. If you are trying to predict the structure of a naturally occurring protein, chances are that there are related ones in the dataset of known 3D structures. This makes it much easier for ML. You are (roughly speaking) training on the test set. However, for drug design, which is what AlphaFold 3 targets, you need to do well on actually novel inputs. It's a completely different use case. More here: https://olegtrott.substack.com/p/are-alphafolds-new-results-a-miracle https://olegtrott.substack.com/p/are-alphafolds-new-results-...
- jhbadger 2y ago
  Protein structures are similar to each other because of evolution (protein families exist because of shared ancestry of protein coding genes). It's not a weird coincidence that helps ML; it's inherent in the problem. Same with drug design -- very, very, few drugs are "novel" as opposed to being analogues of something naturally in the body.
  - svara 2y ago
    They're referring to the structure of the protein when a drug is bound, that's what's novel. Novel as in, you can't think of it as "just" interpolation between known structures of evolutionarily related proteins. That said I'm not sure that's entirely fair, since Alphafold does, as far as I know, work for predicting structures that are far away from structures that have previously been measured. You're quite wrong about small molecule drug structures. Historically that has been the case but these days many lead structures are made by combinatorial chemistry and are not derived from natural products.
    - jhbadger 2y ago
      But even drugs made by combinatorial chemistry still generally end up being analogues of natural products even if they aren't derived from them. As Leslie Orgel said "Evolution is cleverer than you are"; chemists are unlikely to discover a mechanism of action that millions of years of evolution hasn't already found.
refurb 2y ago
As someone in the drug discovery business I’m skeptical as I’ve seen many such “advances” flop. I remember when computer aided drug design first came out (and several “quantum jumps” along the way). While useful they failed often at the most important cases. New drugs tend to be developed in spaces we know very little about. Thus there is nothing useful for AI to be trained on. Nothing quite like hearing from the computational scientist “if you make this one change it will improve binding by 1000x”. Then spending 3 weeks making it to find out it actually binds worse.
hackernewds 2y ago
Well deserved! My only qualm is it should've been awarded to the team, vs individuals It needed Oriol as well doing IC work

ackbar03 2y ago

I was just wondering when they were going to award the alphafold2 guys the nobel after after seeing Hinton win the physics one. 100% agree, all three of them totally deserve this one. Baker's lab is pretty much keeping Deepmind in check at this point and ensuring open source research is keeping up. Hats off

theGnuMe 2y ago
Baker has been in the protein folding game for a long time and was the leader before Alphafold came in... His generative paper came out what last year (2023)? I mean this is a fast award cycle.
- divbzero 2y ago
  David Baker’s RoseTTAFold was first released in 2021. [1]: https://www.science.org/doi/10.1126/science.abj8754 https://www.science.org/doi/10.1126/science.abj8754 [2]: https://cen.acs.org/analytical-chemistry/structural-biology/Accurate-protein-structure-prediction-AI/99/i26 https://cen.acs.org/analytical-chemistry/structural-biology/...

tomp 2y ago

Are they? What did Demis do?

world2vec 2y ago
He's founder and CEO of the AI lab that build Alphafold?
- devilzhong 2y ago
  Then maybe Sergey and Larry should also get the prize since they founded Google, which owns Deepmind?
  - world2vec 2y ago
    They were not equal contributors to the seminal paper that got the prize. From another post in this thread: "These authors contributed equally: John Jumper, Richard Evans, Alexander Pritzel, Tim Green, Michael Figurnov, Olaf Ronneberger, Kathryn Tunyasuvunakool, Russ Bates, Augustin Žídek, Anna Potapenko, Alex Bridgland, Clemens Meyer, Simon A. A. Kohl, Andrew J. Ballard, Andrew Cowie, Bernardino Romera-Paredes, Stanislav Nikolov, Rishub Jain, Demis Hassabis"
  - theGnuMe 2y ago
    They bought it and it runs autonomously (or did mostly)
onursurme 2y ago
He writes software in different areas, so he has the potential to get a Nobel prize in any area soon.
seydor 2y ago
didn't he lead early successes in RL which popularized it and culminated in protein prediction?

cowsandmilk 2y ago

Both Rosetta and DeepMind have made contributions outside of protein structure prediction that are far more important for drug discovery.

mihaaly 2y ago

The physics prize should have went to Elon Musk! Also I really hope the Nobel Prize of Economics goes to Bill Gates! He facilitated sooo much advances by releasing Excel that this must be recognized! And based on this year's announcements so far I am not sure that my sarcastic comments should be taken as a joke!

theGnuMe 2y ago
Except Excel has introduced way to many bugs and how many people has it killed?

trott 2y ago

> There are few approaches that will accelerate the field of drug development and chemistry as a whole in a way that the works of these three people will. As the author of one such approach, I'm skeptical. AlphaFold 2 just predicts protein structures. The thing about proteins is that they are often related to each other. If you are trying to predict the structure of a naturally occurring protein, chances are that there are related ones in the dataset of known 3D structures. This makes it much easier for ML. You are (roughly speaking) training on the test set. However, for drug design, which is what AlphaFold 3 targets, you need to do well on actually novel inputs. It's a completely different use case. More here: https://olegtrott.substack.com/p/are-alphafolds-new-results-a-miracle https://olegtrott.substack.com/p/are-alphafolds-new-results-...

jhbadger 2y ago
Protein structures are similar to each other because of evolution (protein families exist because of shared ancestry of protein coding genes). It's not a weird coincidence that helps ML; it's inherent in the problem. Same with drug design -- very, very, few drugs are "novel" as opposed to being analogues of something naturally in the body.
- svara 2y ago
  They're referring to the structure of the protein when a drug is bound, that's what's novel. Novel as in, you can't think of it as "just" interpolation between known structures of evolutionarily related proteins. That said I'm not sure that's entirely fair, since Alphafold does, as far as I know, work for predicting structures that are far away from structures that have previously been measured. You're quite wrong about small molecule drug structures. Historically that has been the case but these days many lead structures are made by combinatorial chemistry and are not derived from natural products.
  - jhbadger 2y ago
    But even drugs made by combinatorial chemistry still generally end up being analogues of natural products even if they aren't derived from them. As Leslie Orgel said "Evolution is cleverer than you are"; chemists are unlikely to discover a mechanism of action that millions of years of evolution hasn't already found.

refurb 2y ago

As someone in the drug discovery business I’m skeptical as I’ve seen many such “advances” flop. I remember when computer aided drug design first came out (and several “quantum jumps” along the way). While useful they failed often at the most important cases. New drugs tend to be developed in spaces we know very little about. Thus there is nothing useful for AI to be trained on. Nothing quite like hearing from the computational scientist “if you make this one change it will improve binding by 1000x”. Then spending 3 weeks making it to find out it actually binds worse.

hackernewds 2y ago

Well deserved! My only qualm is it should've been awarded to the team, vs individuals It needed Oriol as well doing IC work