In reply to James, BLAST will align sequences but your premise is that
the function of the 'unknown' sequence/structure is the same as that of
the 'known'. The lipocalin family is one which has a wide distribution
and the functions vary considerably from involvement with embryo
implantation to colouration of the lobster carapace to brain-related
enzyme activity. Each easily predicatable from the other? Possibly, but
knowing what ligand binds doesn't necessarily give thephysiological
function!
Lindsay
On 12/11/2020 3:54 PM, James Holton wrote:
Well, that problem was solved a long time ago. An excellent
function-from-sequence predictor is here:
https://blast.ncbi.nlm.nih.gov/Blast.cgi
AlphaFold2 is doing rather much the same thing. Just with a 3D output
rather than 1D, and an underlying model with a LOT more fittable
parameters.
-James Holton
MAD Scientist
On 12/11/2020 4:42 AM, Phil Evans wrote:
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 <[email protected]> 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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--
Lindsay Sawyer
Emeritus Professor of Structural Biochemistry
Institute of Structural & Molecular Biology
School of Biological Sciences
Roger Land Building, King's Buildings
Mayfield Road
Edinburgh EH9 3JR, Scotland
Tel: 00-44-(0)131-650-7062
Fax: 00-44-(0)131-650-7055
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The University of Edinburgh is a charitable body, registered in
Scotland, with registration number SC005336
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