4 ms·

Been out of the field for a while, could someone currently in it qualify these results? Hyperbolic title notwithstanding, they approach 90% median free modeling

Been out of the field for a while, could someone currently in it qualify these results? Hyperbolic title notwithstanding, they approach 90% median free modeling accuracy. The "other 90%" still remains to be solved...

asdfasgasdgasdg 6y ago
I don't think anyone on HN is going to have more authority to qualify the results than the independent experts quoted in the linked article. Among whom are numbered a Nobel laureate, the president of the group that designs the tests of protein folding systems, and the former CEO of Genentech+current CEO of Calico.
- dekhn 6y ago
  Art's a smart guy and I have a lot of respect for his biological intuition, but his understanding of computational biology is very limited.
  - asdfasgasdgasdg 6y ago
    I would imagine that he is not assessing this advancement merely using his own personal expertise, but rather the combined expertise of the resources he represents. CEOs don't just look at problems and potential solutions. They have people who look at those things, and then tell them their opinion. In any case, you've picked a nit with one of the three people quoted. Any objections to the other two?
    - dekhn 6y ago
      My main objection to Vivek (the Nobel Prize winner) is the prize in that case should have gone to my advisor, Harry Noller. John Moult... he's a nice guy but I think he's being a bit breathless here.
      - asdfasgasdgasdg 6y ago
        I see. The co-founder of the organization that tests protein folding is a "nice guy."
        dekhn 6y ago
        CASP is not "the organization that tests protein folding". It's an organization that every two years does a blind prediction and publishes the results (I've competed, some 20 years ago). John's a protein expert, no question about it. I knew him moderately well back in the day because our advisors moved in similar circles.
  - mrDmrTmrJ 6y ago
    dekhn, in what way is Art's "understanding of computational biology very limited?" I'd love to hear more. Specifically, what do you think that computational biology can do that you think Art doesn't understand or credit?
- WWWWH 6y ago
  Quite right. And the Nobel laureate in question is a structural biologist--so his expertise is directly relevant.
gmorainbows 6y ago
The method relies on multiple-sequence-alignment (MSA) of homologous proteins. This cannot fold arbitrary proteins, only biologically relevant ones that have high quality MSAs available. It's also worth pointing out that the gold-standard for validating MSAs relies on PDBs of folded proteins. This is exciting work that will assist NMR and XRay crystallographers, but it's not a panacea of protein folding. https://github.com/deepmind/deepmind-research/issues/18 https://github.com/deepmind/deepmind-research/issues/18
- flobosg 6y ago
  In their CASP abstract[1] they mention alternatives to typical co-evolution features which improve performance in shallow MSA depths. [1]: https://predictioncenter.org/casp14/doc/CASP14_Abstracts.pdf#page=23 https://predictioncenter.org/casp14/doc/CASP14_Abstracts.pdf...
  - gmorainbows 6y ago
    It doesn't matter so much how they perform the feature extraction, so much as what their inputs to the feature extraction are. This model requires a collection of wild-type proteins in an accurate MSA. Producing an accurate MSA is hard even if you have many homologs. They require protein homologs which means they can "only" do this for wild-type proteins. This work is useless with mutant and synthetic proteins. This is a big advancement that will assist crystallographers and NMR structural biologists with difficult wild-type proteins, but it doesn't "solve protein folding" by any stretch of the imagination.
    - flobosg 6y ago
      > Producing an accurate MSA is hard even if you have many homologs. To assess co-evolutionary couplings the amount of homologs in the MSA is not as important as the number of effective sequences (i.e. sequence depth and diversity) in it. > They require protein homologs which means they can "only" do this for wild-type proteins. Even remote homologs work, as shown by the widespread use of HHM-based methods in the prediction pipelines. > This work is useless with mutant and synthetic proteins. Unless you generate a flurry of data with them using deep mutational scanning for example. As long as correlated mutations are present in the MSA the technique should work as expected no matter where the protein sequences originated.

asdfasgasdgasdg 6y ago

I don't think anyone on HN is going to have more authority to qualify the results than the independent experts quoted in the linked article. Among whom are numbered a Nobel laureate, the president of the group that designs the tests of protein folding systems, and the former CEO of Genentech+current CEO of Calico.

dekhn 6y ago
Art's a smart guy and I have a lot of respect for his biological intuition, but his understanding of computational biology is very limited.
- asdfasgasdgasdg 6y ago
  I would imagine that he is not assessing this advancement merely using his own personal expertise, but rather the combined expertise of the resources he represents. CEOs don't just look at problems and potential solutions. They have people who look at those things, and then tell them their opinion. In any case, you've picked a nit with one of the three people quoted. Any objections to the other two?
  - dekhn 6y ago
    My main objection to Vivek (the Nobel Prize winner) is the prize in that case should have gone to my advisor, Harry Noller. John Moult... he's a nice guy but I think he's being a bit breathless here.
    - asdfasgasdgasdg 6y ago
      I see. The co-founder of the organization that tests protein folding is a "nice guy."
      - dekhn 6y ago
        CASP is not "the organization that tests protein folding". It's an organization that every two years does a blind prediction and publishes the results (I've competed, some 20 years ago). John's a protein expert, no question about it. I knew him moderately well back in the day because our advisors moved in similar circles.
- mrDmrTmrJ 6y ago
  dekhn, in what way is Art's "understanding of computational biology very limited?" I'd love to hear more. Specifically, what do you think that computational biology can do that you think Art doesn't understand or credit?
WWWWH 6y ago
Quite right. And the Nobel laureate in question is a structural biologist--so his expertise is directly relevant.

gmorainbows 6y ago

The method relies on multiple-sequence-alignment (MSA) of homologous proteins. This cannot fold arbitrary proteins, only biologically relevant ones that have high quality MSAs available. It's also worth pointing out that the gold-standard for validating MSAs relies on PDBs of folded proteins. This is exciting work that will assist NMR and XRay crystallographers, but it's not a panacea of protein folding. https://github.com/deepmind/deepmind-research/issues/18 https://github.com/deepmind/deepmind-research/issues/18

flobosg 6y ago
In their CASP abstract[1] they mention alternatives to typical co-evolution features which improve performance in shallow MSA depths. [1]: https://predictioncenter.org/casp14/doc/CASP14_Abstracts.pdf#page=23 https://predictioncenter.org/casp14/doc/CASP14_Abstracts.pdf...
- gmorainbows 6y ago
  It doesn't matter so much how they perform the feature extraction, so much as what their inputs to the feature extraction are. This model requires a collection of wild-type proteins in an accurate MSA. Producing an accurate MSA is hard even if you have many homologs. They require protein homologs which means they can "only" do this for wild-type proteins. This work is useless with mutant and synthetic proteins. This is a big advancement that will assist crystallographers and NMR structural biologists with difficult wild-type proteins, but it doesn't "solve protein folding" by any stretch of the imagination.
  - flobosg 6y ago
    > Producing an accurate MSA is hard even if you have many homologs. To assess co-evolutionary couplings the amount of homologs in the MSA is not as important as the number of effective sequences (i.e. sequence depth and diversity) in it. > They require protein homologs which means they can "only" do this for wild-type proteins. Even remote homologs work, as shown by the widespread use of HHM-based methods in the prediction pipelines. > This work is useless with mutant and synthetic proteins. Unless you generate a flurry of data with them using deep mutational scanning for example. As long as correlated mutations are present in the MSA the technique should work as expected no matter where the protein sequences originated.