4 ms·

I respectfully disagree. AlphaFold 2 demonstrated almost perfect performance for a multitude of proteins for which no meaningful templates were available -- hen

I respectfully disagree. AlphaFold 2 demonstrated almost perfect performance for a multitude of proteins for which no meaningful templates were available -- hence, it was not doing homology modelling as it is generally understood, but ab initio protein structure prediction. What I would support is that AlphaFold 2 does not solve the protein folding problem: how, as opposed to what to, a protein folds.

dekhn 5y ago
how could they do ab initio? They depend on multiple sequence alignments. If I'm mistaken about this then I'll happily take back what I said, but there's no way that AF2 could work wihtout MSAs, therefore, it is not ab initio. Ah, OK checked the paper again. They're working on the "template" category which means there is structure-sequence information... maybe CASP organizers consider this ab initio ? The paper never mentions anything about ab initio predicitons. Is that what you're saying, that template methods are ab initio?
- couteiral 5y ago
  Just in case there is a confusion: there is a difference between available sequences (~300 million in standard protein sequence repositories) and structures (~170k structures in the PDB, perhaps about ~120k that are structurally non-redundant). A large amount of CASP14 targets have no available templates; in fact, many of them represented previously unseen topologies. However, all of them had some (in most cases, many) available sequences. The commonly accepted definition of homology modelling implies using a known structure ("template") as a scaffold to model the protein's topology. Since there are many CASP14 targets without appropriate templates, AlphaFold 2 simply cannot "just do homology modelling". I do take the point that the correct term is "free modelling" (it does not have, or does not use, any good structure as a template), and not "ab initio modelling" (it uses physics to fold the protein), though. A deep enough MSA is generally a requirement.
  - dekhn 5y ago
    Again, it's entirely possible I missed some very subtle point in AF2's system, but my understanding is that each target AF2 predicted had an underlying structural template covering the majority of the domain and the mapping was established through the MSA. IE, any MSAs would always include alignments to known protein structures. Are you saying their MSAs don't include alignments to known protein structures? (the reason I'm asking all this is because if I'm mistaken, then AF2 did do something "interesting", but everything in the paper says that everything they did is template based. If they are just folding proteins using MSAs without alignments to protein structures, that's far more interesting. I don't think they did that. edit: I've now reread the paper again, and I believe their claim of making predictions where there is no structural homology is incorrect from a technical perspective. I've communicated this to both the CASP organizers (whom I know) and DeepMind.
    - couteiral 5y ago
      Yes: they predict structures using MSAs, without alignments to known protein structures in a majority of the cases.
      - dekhn 5y ago
        OK if that's truly accurate, then they did make a significant accomplishment. However, I'm 99% certain (from reading the paper) that they actually do have alignments to structures, but the similarity is very low. It would help if you coould point to one of the alignmennts they made that has no underlying structure (even a template fragment) support. I reread the methods section, https://static-content.springer.com/esm/art%3A10.1038%2Fs41586-021-03819-2/MediaObjects/41586_2021_3819_MOESM1_ESM.pdf https://static-content.springer.com/esm/art%3A10.1038%2Fs415... They train jointly on the results of genetic search and template search (template search). Can you show an example of a prediction made using only genetic search and not template search. Those templates are fastas made from PDB files, which, while not homology modelling, is definitely not "ab initio".
      - dekhn 5y ago
        I've been in communication with several different teams and leaders at CASP and I've confirmed that this does appear to be the case. I'm going to be a bit skeptical but if that's the case, then it really is a significant improvement. Glad to see that with just the idea, the academic community was able to reach near parity in a short time, demonstrating there was nothing unique to DM except their huge amount of compute, storage, and talent, and this would have happened in the next CASP anyway.
timr 5y ago
> it was not doing homology modelling as it is generally understood, but ab initio protein structure prediction. Maybe according to the current definition of the term, which has drifted over the years. Homology modeling and "ab initio" structure prediction have been drifting toward each other for a long time. These days, the categories are separated by (an essentially arbitrary) sequence identity threshold. If you have a protein sequence with high homology to some other protein with a structure, then you're homology modeling. If you have no matches at all, you're doing "ab initio". In the middle, you have a gray area where you can mix the approaches and call it whatever you like. This is not a pedantic point. If your method requires homology -- however distant and fragmented -- in order to work, then you're always limited to the knowledge in the database. Maybe we've sampled enough of protein space to get the major folds, but certainly, the databases don't have enough information to get the small details right. I have never been a huge believer in the idea that we can go directly from protein sequence to protein structure simply using a mathematical model of physics, but that is the original meaning of "ab initio structure prediction", and if you could do it, it would be far more valuable than alphafold. At risk of making a trivially nerd-snipable metaphor, it's kind of like the difference between google translate and a theoretical model of human intelligence that understands concepts and can generate language. The latter is obviously immensely more capable than the former.
- dekhn 5y ago
  If CASP is calling methods that use any sequence similarity (the grey area) 'ab initio', that's disingenuous and intellectually dishonest. ab initio means from nothing, and at most, you're allowed to have physically inspired force fields, not sequence similarity to known structures. I put a lot of effort into improving the state of the art in that area, but ultimately concluded it made more sense to concentrate experimental structural determination in the area that was most useful- in proteins that had unknown folds or no known homology (see https://scholar.google.com/citations?view_op=view_citation&hl=en&user=TFgipkIAAAAJ&citation_for_view=TFgipkIAAAAJ:Y0pCki6q_DkC https://scholar.google.com/citations?view_op=view_citation&h... for some previous work I did in this area).
  - timr 5y ago

dekhn 5y ago

how could they do ab initio? They depend on multiple sequence alignments. If I'm mistaken about this then I'll happily take back what I said, but there's no way that AF2 could work wihtout MSAs, therefore, it is not ab initio. Ah, OK checked the paper again. They're working on the "template" category which means there is structure-sequence information... maybe CASP organizers consider this ab initio ? The paper never mentions anything about ab initio predicitons. Is that what you're saying, that template methods are ab initio?

couteiral 5y ago
Just in case there is a confusion: there is a difference between available sequences (~300 million in standard protein sequence repositories) and structures (~170k structures in the PDB, perhaps about ~120k that are structurally non-redundant). A large amount of CASP14 targets have no available templates; in fact, many of them represented previously unseen topologies. However, all of them had some (in most cases, many) available sequences. The commonly accepted definition of homology modelling implies using a known structure ("template") as a scaffold to model the protein's topology. Since there are many CASP14 targets without appropriate templates, AlphaFold 2 simply cannot "just do homology modelling". I do take the point that the correct term is "free modelling" (it does not have, or does not use, any good structure as a template), and not "ab initio modelling" (it uses physics to fold the protein), though. A deep enough MSA is generally a requirement.
- dekhn 5y ago
  Again, it's entirely possible I missed some very subtle point in AF2's system, but my understanding is that each target AF2 predicted had an underlying structural template covering the majority of the domain and the mapping was established through the MSA. IE, any MSAs would always include alignments to known protein structures. Are you saying their MSAs don't include alignments to known protein structures? (the reason I'm asking all this is because if I'm mistaken, then AF2 did do something "interesting", but everything in the paper says that everything they did is template based. If they are just folding proteins using MSAs without alignments to protein structures, that's far more interesting. I don't think they did that. edit: I've now reread the paper again, and I believe their claim of making predictions where there is no structural homology is incorrect from a technical perspective. I've communicated this to both the CASP organizers (whom I know) and DeepMind.
  - couteiral 5y ago
    Yes: they predict structures using MSAs, without alignments to known protein structures in a majority of the cases.
    - dekhn 5y ago
      OK if that's truly accurate, then they did make a significant accomplishment. However, I'm 99% certain (from reading the paper) that they actually do have alignments to structures, but the similarity is very low. It would help if you coould point to one of the alignmennts they made that has no underlying structure (even a template fragment) support. I reread the methods section, https://static-content.springer.com/esm/art%3A10.1038%2Fs41586-021-03819-2/MediaObjects/41586_2021_3819_MOESM1_ESM.pdf https://static-content.springer.com/esm/art%3A10.1038%2Fs415... They train jointly on the results of genetic search and template search (template search). Can you show an example of a prediction made using only genetic search and not template search. Those templates are fastas made from PDB files, which, while not homology modelling, is definitely not "ab initio".
    - dekhn 5y ago
      I've been in communication with several different teams and leaders at CASP and I've confirmed that this does appear to be the case. I'm going to be a bit skeptical but if that's the case, then it really is a significant improvement. Glad to see that with just the idea, the academic community was able to reach near parity in a short time, demonstrating there was nothing unique to DM except their huge amount of compute, storage, and talent, and this would have happened in the next CASP anyway.

timr 5y ago

> it was not doing homology modelling as it is generally understood, but ab initio protein structure prediction. Maybe according to the current definition of the term, which has drifted over the years. Homology modeling and "ab initio" structure prediction have been drifting toward each other for a long time. These days, the categories are separated by (an essentially arbitrary) sequence identity threshold. If you have a protein sequence with high homology to some other protein with a structure, then you're homology modeling. If you have no matches at all, you're doing "ab initio". In the middle, you have a gray area where you can mix the approaches and call it whatever you like. This is not a pedantic point. If your method requires homology -- however distant and fragmented -- in order to work, then you're always limited to the knowledge in the database. Maybe we've sampled enough of protein space to get the major folds, but certainly, the databases don't have enough information to get the small details right. I have never been a huge believer in the idea that we can go directly from protein sequence to protein structure simply using a mathematical model of physics, but that is the original meaning of "ab initio structure prediction", and if you could do it, it would be far more valuable than alphafold. At risk of making a trivially nerd-snipable metaphor, it's kind of like the difference between google translate and a theoretical model of human intelligence that understands concepts and can generate language. The latter is obviously immensely more capable than the former.

dekhn 5y ago
If CASP is calling methods that use any sequence similarity (the grey area) 'ab initio', that's disingenuous and intellectually dishonest. ab initio means from nothing, and at most, you're allowed to have physically inspired force fields, not sequence similarity to known structures. I put a lot of effort into improving the state of the art in that area, but ultimately concluded it made more sense to concentrate experimental structural determination in the area that was most useful- in proteins that had unknown folds or no known homology (see https://scholar.google.com/citations?view_op=view_citation&hl=en&user=TFgipkIAAAAJ&citation_for_view=TFgipkIAAAAJ:Y0pCki6q_DkC https://scholar.google.com/citations?view_op=view_citation&h... for some previous work I did in this area).
- timr 5y ago