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AlphaFold 2 is here: what’s behind the structure prediction miracle

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Re: AlphaFold 2 is here: what’s behind the structure prediction miracle

#61

Post by dekhn »

couteiral wrote: post #58
dekhn wrote: post #50

Earlier quoted context omitted.

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…

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, man…

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.

Re: AlphaFold 2 is here: what’s behind the structure prediction miracle

#62

Post by timr »

dekhn wrote: post #60
timr wrote: post #54

Earlier quoted context omitted.

> 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 ha…

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 exper…

> If CASP is calling methods that use any sequence similarity (the grey area) 'ab initio', that's disingenuous and intellectually dishonest.

The category is given the name, not the methods. People can use any method they like to solve the structures. The organizers are not zealots.

The ab initio portion of CASP consists of proteins that the organizers know have low sequence identity to anything in the existing databases. They represent proteins that are "difficult" to solve using what any practitioner might call homology modeling. That doesn't mean that you can't use a method that takes into account the biological databases -- and essentially all of the good methods do!

For example, the Rosetta method has competed in both the homology modeling and the ab initio categories for many years. They mix a bit of both -- using homology models to get the fold, and fragment insertion to model the floppy bits.

I haven't paid close attention to CASP in a long time, but I assume the competitor list still has tons of entries from people who cling tightly to the purist vision of ab initio modeling. They don't tend to do very well.

Re: AlphaFold 2 is here: what’s behind the structure prediction miracle

#63

Post by dekhn »

cing wrote: post #51
infogulch wrote: post #43

Earlier quoted context omitted.

Yikes that sounds bleak.

Yet, there were still 136 human teams who competed in CASP14 ( https://predictioncenter.org/casp14/docs.cgi?view=groupsbyna... ), including DeepMind. Even if a significant fraction of these projects were done piggy-backing another grant, this work does receive research funding.

Be fair. Many of those rows contain duplicate names (identical teams), so the count is much smaller.

Re: AlphaFold 2 is here: what’s behind the structure prediction miracle

#64

Post by alphabetting »

maliker wrote: post #24
bamboozled wrote: post #17

Thank you Google...thank you!

Why did they open source it? Wouldn’t this model be very valuable to the pharma industry?

As an outsider it seems Google has a much more academia friendly culture than other megacap tech companies. Guessing the talent which this culture draws are likely more adamant about their work being open sourced.

Re: AlphaFold 2 is here: what’s behind the structure prediction miracle

#66

Post by couteiral »

dekhn wrote: post #61
couteiral wrote: post #58

Earlier quoted context omitted.

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, man…

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 reas…

Yes: they predict structures using MSAs, without alignments to known protein structures in a majority of the cases.

Re: AlphaFold 2 is here: what’s behind the structure prediction miracle

#67

Post by dekhn »

timr wrote: post #62
dekhn wrote: post #60

Earlier quoted context omitted.

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 exper…

> If CASP is calling methods that use any sequence similarity (the grey area) 'ab initio', that's disingenuous and intellectually dishonest. The category is given the name, not the methods. People can use any method they like to solve the structures. The organizers are not zealots. The ab initio portion of CASP consists of proteins that the organizers know have low sequence identity to anything in the existing databa…

OK, be aware the person you're correcting has: competed in CASP (on a competitor team with Sali), and published papers with Baker on Rosetta methods (my paper is cited in the most RoseTTA paper).

"They mix a bit of both -- using homology models to get the fold, and fragment insertion to model the floppy bits."

that's the best description of what I believe AF2 is doing, but that AF2 is being marketed as not depending on any sequence similarity.

If the CASP folks really are saying "if you have 20% sequence identity and use the structure from that alignment it's ab initio"... that's really just totally misleading.

Of course, even ab initio methods are parameterized on biological information; for example, I used AMBER to do MD simulations and many of the force field terms were determined using spectroscopic data from fragments of biological models. That, however is ab initio, because nothing even as large as a single amino acid is parameterized.

I'm not saying there's anything wrong with homology modelling, or that the purist vision of ab initio is right. For practical purposes, exploiting subtle structural information through sequence alignment is a very nice way to save enormous amounts of computer time.

Re: AlphaFold 2 is here: what’s behind the structure prediction miracle

#68

Post by dekhn »

couteiral wrote: post #66
dekhn wrote: post #61

Earlier quoted context omitted.

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 reas…

Yes: they predict structures using MSAs, without alignments to known protein structures in a majority of the cases.

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%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".

Re: AlphaFold 2 is here: what’s behind the structure prediction miracle

#69

Post by timr »

dekhn wrote: post #67
timr wrote: post #62

Earlier quoted context omitted.

> If CASP is calling methods that use any sequence similarity (the grey area) 'ab initio', that's disingenuous and intellectually dishonest. The category is given the name, not the methods. People can use any method they like to solve the structures. The organizers are not zealots. The ab initio portion of CASP consists of proteins that the organizers know have low sequence identity to anything in the existing databa…

OK, be aware the person you're correcting has: competed in CASP (on a competitor team with Sali), and published papers with Baker on Rosetta methods (my paper is cited in the most RoseTTA paper). "They mix a bit of both -- using homology models to get the fold, and fragment insertion to model the floppy bits." that's the best description of what I believe AF2 is doing, but that AF2 is being marketed as not depending…

> OK, be aware the person you're correcting has: competed in CASP (on a competitor team with Sali), and published papers with Baker on Rosetta methods (my paper is cited in the most RoseTTA paper).

OK, great. Me too. I'm not saying anything controversial here. Right from the top of the "ab initio" tab on predictioncenter.org:

"Modeling proteins with no or marginal similarity to existing structures (ab initio, new fold, non-template or free modeling) is the most challenging task in tertiary structure prediction."

Re: AlphaFold 2 is here: what’s behind the structure prediction miracle

#70

Post by dekhn »

timr wrote: post #69
dekhn wrote: post #67

Earlier quoted context omitted.

OK, be aware the person you're correcting has: competed in CASP (on a competitor team with Sali), and published papers with Baker on Rosetta methods (my paper is cited in the most RoseTTA paper). "They mix a bit of both -- using homology models to get the fold, and fragment insertion to model the floppy bits." that's the best description of what I believe AF2 is doing, but that AF2 is being marketed as not depending…

> OK, be aware the person you're correcting has: competed in CASP (on a competitor team with Sali), and published papers with Baker on Rosetta methods (my paper is cited in the most RoseTTA paper). OK, great. Me too. I'm not saying anything controversial here. Right from the top of the "ab initio" tab on predictioncenter.org: "Modeling proteins with no or marginal similarity to existing structures (ab initio, new fol…

I think the more important question to resolve here is: did AlphaFold change anything with respect to structure prediction that enabled them to make accurate predictions in the complete absence of sequence similarity to proteins with known structure?

My understanding is no, they did the equivalent of template modelling, which uses sequence/structure relationships (that are more subtle than the ones you get from homology modelling).

I'm less interested in reconciling my internal mental model of psp wiht CASPs, than I am in understanding if AF2 is somehow able to get all the necessarily structural constraints through coevolution of amino acid pairs entirely without some (direct or indirect) learned relationship between the sequence similarity to known structures (be it even short fragments like helices).

If they really did do that, and nobody did it before, that's great and I will happily promote the DM work, as it supports what I said when I did CASP: ML and MD will eventually win, although in a way that exploits the rich sequence evolutionary information we have, rather than predominantly by having an accurate force field and good smapling methods.

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