I see, thanks, that looks good.
Where can one download predicted_model+exp_model PDBs together?
I could easily find predicted models but not experimental - CASP website
seems very cryptic.
Also, can you comment on how much GDT_TS depends on CA and how much on
side chains positioning?
E.g. if it is >90, can one be sure that most side-chains are in the
right place?
Thanks.
Leonid
On 11.12.20 13:12, Tristan Croll 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 <[email protected]> on behalf of
Leonid Sazanov <[email protected]>
*Sent:* 11 December 2020 10:36
*To:* [email protected] <[email protected]>
*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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