Alpha-fold looks great and is clearly a long way towards answering the question 
“this is the sequence, what is the structure?”

But I’ve always thought the more interesting question is “this is the 
structure, what does it do?”  Is there any progress on that question?

Phil


> On 11 Dec 2020, at 12:12, Tristan Croll <ti...@cam.ac.uk> wrote:
> 
> I'm not Randy, but I do have an answer: like this. This is T1049-D1. 
> AlphaFold prediction in red, experimental structure (6y4f) in green. 
> Agreement is close to perfect, apart from the C-terminal tail which is way 
> off - but clearly flexible and only resolved in this conformation in the 
> crystal due to packing interactions. GDT_TS is 93.1; RMS_CA is 3.68 - but if 
> you exclude those tail residues, it's 0.79. With an alignment cutoff of 1 A, 
> you can align 109 of 134 CAs with an RMSD of 0.46 A.
> From: CCP4 bulletin board <CCP4BB@JISCMAIL.AC.UK> on behalf of Leonid Sazanov 
> <saza...@ist.ac.at>
> Sent: 11 December 2020 10:36
> To: CCP4BB@JISCMAIL.AC.UK <CCP4BB@JISCMAIL.AC.UK>
> Subject: Re: [ccp4bb] External: Re: [ccp4bb] AlphaFold: more thinking and 
> less pipetting (?)
>  
> Dear Randy,
> 
> Can you comment on why for some of AplhaFold2 models with GDT_TS > 90 
> (supposedly as good as experimental model) the RMS_CA (backbone) is > 3.0 
> Angstrom? Such a deviation can hardly be described as good as experimental. 
> Could it be that GDT_TS is kind of designed to evaluate how well the general 
> sub-domain level fold is predicted, rather than overall detail?
> 
> Thanks,
> Leonid
> 
> 
> >>>>>
> Several people have mentioned lack of peer review as a reason to doubt the 
> significance of the AlphaFold2 results.  There are different routes to peer 
> review and, while the results have not been published in a peer review 
> journal, I would have to say (as someone who has been an assessor for two 
> CASPs, as well as having editorial responsibilities for a peer-reviewed 
> journal), the peer review at CASP is much more rigorous than the peer review 
> that most papers undergo.  The targets are selected from structures that have 
> recently been solved but not published or disseminated, and even just 
> tweeting a C-alpha trace is probably enough to get a target cancelled.  In 
> some cases (as we’ve heard here) the people determining the structure are 
> overly optimistic about when their structure solution will be finished, so 
> even they may not know the structure at the time it is predicted.  The 
> assessors are blinded to the identities of the predictors, and they carry out 
> months of calculations and inspections of the models, computing ranking 
> scores before they find out who made the predictions.  Most assessors try to 
> bring something new to the assessment, because the criteria should get more 
> stringent as the predictions get better, and they have new ideas of what to 
> look for, but there’s always some overlap with “traditional” measures such as 
> GDT-TS, GDT-HA (more stringent high-accuracy version of GDT) and lDDT.
> 
> 
> 
> Of course we’d all like to know the details of how AlphaFold2 works, and the 
> DeepMind people could have been (and should be) much more forthcoming, but 
> their results are real.  They didn’t have any way of cheating, being 
> selective about what they reported, or gaming the system in any other way 
> that the other groups couldn’t do.  (And yes, when we learned that DeepMind 
> was behind the exceptionally good results two years ago at CASP13, we made 
> the same half-jokes about whether Gmail had been in the database they were 
> mining!)
> 
> 
> 
> Best wishes,
> 
> 
> 
> Randy Read
> 
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