Re: [ccp4bb] a postdoctoral fellow position at Dana-Farber Cancer Institute and Harvard Medical School

[Tan, Kemin]

Dear all,


The Reinherz lab at Dana-Farber Cancer Institute and Harvard Medical School is 
recruiting a postdoctoral fellow to study HIV-1 vaccine development. The 
successful candidate will enjoy working in a dynamic and collaborative research 
environment focused on structural/molecular mechanism of broadly neutralizing 
antibodies specific to MPER segment of the gp41 subunit in membrane 
environments, its implication to immunogen design and immunogenicity. The 
laboratory provides a rich training environment and access to cutting-edge 
techniques.



Highly-motivated candidates with a recent PhD or MD/PhD in biomedical sciences 
and significant experience in molecular biology and biochemistry are encouraged 
to apply. Skills in molecular biology, biochemistry and extensive biomolecular 
NMR experience are essential.  Candidates should have a documented publication 
record in peer-reviewed journals. We are seeking a candidate with excellent 
writing and communication skills, able to work independently but also 
effectively and collaboratively with other lab members. Applicants should 
include a short statement of research goals, CV and three references with their 
application.


Responsibilities: The postdoctoral fellow will perform structural analysis of 
MPER-containing transmembrane domain  incorporated into nanodisc and its 
interaction with  broadly neutralizing antibodies. Molecular cloning, protein 
expression in E.Coli, protein purification and reconstitution of the membrane 
protein segment are key tasks.

If you are interested, please send information to:

Ellis L. Reinherz MD
Professor of Medicine
Harvard Medical School
Chief, Laboratory of Immunobiology
Dana Farber Cancer Institute
Jimmy Fund Building, Room 520
35 Binney Street
Boston, Mass. USA 02115
Phone 617-632-3412
Fax   617-632-3351
E-mail : 
ellis_reinh...@dfci.harvard.edu





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Re: [ccp4bb] AW: [ccp4bb] Problem in finding a MR solution

[Eleanor Dodson]

I guess you did test P3 P31 and P32?
E

On Fri, 11 Dec 2020 at 17:19, Schreuder, Herman /DE <
herman.schreu...@sanofi.com> wrote:

> Hi Suraj,
>
>
>
> It is strange that the P3 crystals do not produce a MR solution. Since
> they all came from the same crystallization condition, you may want to
> check that no proteolytic cleavage of your protein has taken place and that
> your crystals only contain a fragment of your protein. You may also want to
> check that at least one complete molecule would fit into the asymmetric
> unit of your P3 crystals.
>
> Your R and Rfree values for your C2 data set may be artificially low due
> to the detwinning procedure, but as Eleanor mentions, they are not bad.
>
>
>
> What I would do in any case is to rebuild and refine the structure of your
> C2 crystals as well as possible. In the worst case that could be the only
> structure you get, but there are worse things. Most crystals structures in
> the PDB have been solved from a single crystal form. You can then use your
> rebuilt and refined model to run again MR with your P3 data. Maybe you are
> lucky and get a solution this time.
>
>
>
> Best,
>
> Herman
>
>
>
>
>
> *Von:* CCP4 bulletin board  *Im Auftrag von *Eleanor
> Dodson
> *Gesendet:* Freitag, 11. Dezember 2020 15:37
> *An:* CCP4BB@JISCMAIL.AC.UK
> *Betreff:* Re: [ccp4bb] Problem in finding a MR solution
>
>
>
> Well - C2 is a sub cell for P3 so that isnt surprising, but a cell
> difference of 202 to 212 means it isnt isomorphous..
>
> But an
>
> Rw Rf/ of 26/31 isnt bad for such low resolution data?
>
> Eleanor
>
>
>
> On Fri, 11 Dec 2020 at 12:01, Suraj Kumar mandal 
> wrote:
>
> Dear Sir,
>
>
>
> Yes, we have checked handedness also. We are using the same MR solution
> with other data.
>
>
>
>
>
> With best regards
>
> Suraj
>
>
>
>
>
>
>
> On Fri, Dec 11, 2020 at 4:56 PM srajan kapoor 
> wrote:
>
> Have you checked for handedness to solve this problem?.
>
> You can also try to use the structure that you have solved for molecular
> Replacement of the other crystals.
>
> I have only two things in mind currently. I hope it will work for you.
>
>
>
> On Fri, Dec 11, 2020, 4:48 PM Suraj Kumar mandal 
> wrote:
>
> Dear All,
>
>
>
> We are trying to solve a structure of a protein, for which we have
> collected five different home source data at 3.2-3.5 Ang resolution. We are
> processing the data using iMOSFLM and the program suggests P3 (and related)
> space groups for all the data. We are able to get a solution with one data
> (twinned) in C2 space group with Rw/Rf of 26/28%. However, the same
> solution can not be obtained using other four data. Interestingly, one of
> these four data is not twinned. The only common thing in these four data, I
> find, is that they are crystallized in the same crystallization condition,
> whereas, the data which gives solution is crystallized in another condition.
>
>
>
> The template has 69% sequence identity with the target protein.
>
>
>
> Any suggestion to troubleshoot this would be appreciated.
>
>
>
> With best regards,
>
> Suraj
>
>
>
> --
>
> *Suraj Kr. Mandal*
>
> Research Scholar
>
> Structural and Computational Biology Lab
>
> Department of Biosciences and Bioengineering
>
> Indian Institute of Technology (IIT), Guwahati
>
> Guwahati, Assam 781039
>
> Ph.: 09678244566
>
> E.mail: tuoamicosu...@gmail.com
>
>surajkrman...@iitg.ernet.in
>
>
> --
>
> To unsubscribe from the CCP4BB list, click the following link:
> https://www.jiscmail.ac.uk/cgi-bin/WA-JISC.exe?SUBED1=CCP4BB=1
> 
>
>
>
>
> --
>
> *Suraj Kr. Mandal*
>
> Research Scholar
>
> Structural and Computational Biology Lab
>
> Department of Biosciences and Bioengineering
>
> Indian Institute of Technology (IIT), Guwahati
>
> Guwahati, Assam 781039
>
> Ph.: 09678244566
>
> E.mail: tuoamicosu...@gmail.com
>
>surajkrman...@iitg.ernet.in
>
>
> --
>
> To unsubscribe from the CCP4BB list, click the following link:
> https://www.jiscmail.ac.uk/cgi-bin/WA-JISC.exe?SUBED1=CCP4BB=1
> 
>
>
> --
>
> To unsubscribe from the CCP4BB list, click 

[ccp4bb] ccp4.ac.uk offline

[Ballard, Charles (STFC,RAL,SC)]

Dear All

we are currently off line.  The water cooling is undergoing maintenance where 
our servers sit.  We had hoped to continue to run downloads,etc, but it looks 
like the front-end machine has gone down.  Planned return to normal is 9 am 
GMT, this is if the front-end shutdown was a planned event, otherwise we will 
be back as soon as possible after then.

Sorry for any inconvenience

Charles and the CCP4 Core Team

This email and any attachments are intended solely for the use of the named 
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[ccp4bb] AW: [ccp4bb] Problem in finding a MR solution

[Schreuder, Herman /DE]

Hi Suraj,

It is strange that the P3 crystals do not produce a MR solution. Since they all 
came from the same crystallization condition, you may want to check that no 
proteolytic cleavage of your protein has taken place and that your crystals 
only contain a fragment of your protein. You may also want to check that at 
least one complete molecule would fit into the asymmetric unit of your P3 
crystals.
Your R and Rfree values for your C2 data set may be artificially low due to the 
detwinning procedure, but as Eleanor mentions, they are not bad.

What I would do in any case is to rebuild and refine the structure of your C2 
crystals as well as possible. In the worst case that could be the only 
structure you get, but there are worse things. Most crystals structures in the 
PDB have been solved from a single crystal form. You can then use your rebuilt 
and refined model to run again MR with your P3 data. Maybe you are lucky and 
get a solution this time.

Best,
Herman


Von: CCP4 bulletin board  Im Auftrag von Eleanor Dodson
Gesendet: Freitag, 11. Dezember 2020 15:37
An: CCP4BB@JISCMAIL.AC.UK
Betreff: Re: [ccp4bb] Problem in finding a MR solution

Well - C2 is a sub cell for P3 so that isnt surprising, but a cell difference 
of 202 to 212 means it isnt isomorphous..
But an
Rw Rf/ of 26/31 isnt bad for such low resolution data?
Eleanor

On Fri, 11 Dec 2020 at 12:01, Suraj Kumar mandal 
mailto:tuoamicosu...@gmail.com>> wrote:
Dear Sir,

Yes, we have checked handedness also. We are using the same MR solution with 
other data.


With best regards
Suraj



On Fri, Dec 11, 2020 at 4:56 PM srajan kapoor 
mailto:kapoorsra...@gmail.com>> wrote:
Have you checked for handedness to solve this problem?.
You can also try to use the structure that you have solved for molecular 
Replacement of the other crystals.
I have only two things in mind currently. I hope it will work for you.

On Fri, Dec 11, 2020, 4:48 PM Suraj Kumar mandal 
mailto:tuoamicosu...@gmail.com>> wrote:
Dear All,

We are trying to solve a structure of a protein, for which we have collected 
five different home source data at 3.2-3.5 Ang resolution. We are processing 
the data using iMOSFLM and the program suggests P3 (and related) space groups 
for all the data. We are able to get a solution with one data (twinned) in C2 
space group with Rw/Rf of 26/28%. However, the same solution can not be 
obtained using other four data. Interestingly, one of these four data is not 
twinned. The only common thing in these four data, I find, is that they are 
crystallized in the same crystallization condition, whereas, the data which 
gives solution is crystallized in another condition.

The template has 69% sequence identity with the target protein.

Any suggestion to troubleshoot this would be appreciated.

With best regards,
Suraj

--
Suraj Kr. Mandal
Research Scholar
Structural and Computational Biology Lab
Department of Biosciences and Bioengineering
Indian Institute of Technology (IIT), Guwahati
Guwahati, Assam 781039
Ph.: 09678244566
E.mail: tuoamicosu...@gmail.com
   surajkrman...@iitg.ernet.in



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https://www.jiscmail.ac.uk/cgi-bin/WA-JISC.exe?SUBED1=CCP4BB=1


--
Suraj Kr. Mandal
Research Scholar
Structural and Computational Biology Lab
Department of Biosciences and Bioengineering
Indian Institute of Technology (IIT), Guwahati
Guwahati, Assam 781039
Ph.: 09678244566
E.mail: tuoamicosu...@gmail.com
   surajkrman...@iitg.ernet.in



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Re: [ccp4bb] External: Re: [ccp4bb] AlphaFold: more thinking and less pipetting (?)

[Lindsay Sawyer]

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  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  on behalf of 
Leonid Sazanov 

Sent: 11 December 2020 10:36
To: 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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Re: [ccp4bb] External: Re: [ccp4bb] AlphaFold: more thinking and less pipetting (?)

[James Holton]

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  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  on behalf of Leonid Sazanov 

Sent: 11 December 2020 10:36
To: 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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[ccp4bb] Job posting: Scientist-I (Structural Biology) position at Frederick National Laboratory for Cancer Research

[Dhirendra K Simanshu]

Hello everyone,


The NCI RAS Initiative at Frederick National Laboratory for Cancer Research
is looking for a Scientist with experience in biophysics and structural
biology. The candidate will join my group and be responsible for the
structural characterization of protein-protein and protein-small molecule
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optimization.


For detailed information and to apply for this position, please use this
link:

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Best regards

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--

Dhirendra Simanshu

Principal Scientist, Group Leader - RAS Structural Biology

NCI RAS Initiative

Frederick National Laboratory for Cancer Research

Leidos Biomedical Research, Inc.

*Office/Courier*: 8560 Progress Drive, C1012, Frederick, MD 21701

*USPS mail*: Post Office Box B, ATRF-C1012, Frederick, MD 21702

dhirendra.siman...@fnlcr.nih.gov 



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Re: [ccp4bb] External: Re: [ccp4bb] AlphaFold: more thinking and less pipetting (?)

[Leonid Sazanov]

Thanks, I will try this.

Also, on CASP website there are such scores as RMS_ALL (can be seen in 
tables) and GDC_SC (for side-chains, not visible in tables for some reason).


RMS_ALL presumably includes side-chains and seems good for AlphaFold2 
models, between 1 to 2 Angstrom (apart from the same outliers as 
RMS_CA), although that is not quite at the experimental level.


Were any scores including side-chains included in ranking/evaluation (as 
we hear mostly about GDT_TS)?


If not, how can "experimental level" precision be claimed?


Thanks,

Leonid



On 11.12.20 13:56, Tristan Croll wrote:

I agree the website can be quite cryptic!

You can get all the targets as a tarball from 
https://predictioncenter.org/download_area/CASP14/targets/ 
. For the 
predictions, you can either get them as PDB files on a case-by-case 
basis from the results section, or tarballs of all predictions for a 
given target from 
https://predictioncenter.org/download_area/CASP14/predictions_trimmed_to_domains/ 
. 
In the latter case, each file is essentially a PDB file without the 
.pdb extension, except with 4 lines added to the front looking 
something like:


PFRMAT TS
TARGET T1049
MODEL 2
PARENT N/A

Depending on your choice of viewer, you may need to remove these lines 
before attempting to open it.


The GDT_TS score only considers alpha carbons, so in principle it /is/ 
possible to get a high score on it while still having a model that's 
rubbish in every other respect. It's certainly worth complementing it 
with other scores - e.g. good old MolProbity, or SphereGrinder. The 
latter is quite good in principle - essentially, it places a 6 A 
radius sphere at each CA atom of the target, finds all heavy atoms in 
the sphere, and measures their RMSD to the corresponding atoms in the 
prediction. The actual implementation for CASP is a bit broad-brush, 
though - the score is just the fraction of spheres whose RMSD is under 
2 A.


In the last CASP round I pushed for the need to start adding metrics 
that directly compared the models in torsion space - far from the 
first time that's been suggested, but it's arguably only in the past 
few rounds that models have gotten good enough for this to be a useful 
discriminating measure. It doesn't appear that this has been added to 
the standard measures for CASP14, but if it had I can see that 
AlphaFold2 would have done extremely well - I only showed the ribbon 
representation for T1049 in my last email, but the sidechains in the 
core show pretty amazing agreement with the target.


Best regards,

Tristan

*From:* Leonid Sazanov 
*Sent:* 11 December 2020 12:32
*To:* Tristan Croll ; CCP4BB@JISCMAIL.AC.UK 

*Subject:* Re: [ccp4bb] External: Re: [ccp4bb] AlphaFold: more 
thinking and less pipetting (?)


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  
 on behalf of Leonid Sazanov 
 

*Sent:* 11 December 2020 10:36
*To:* 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 

Re: [ccp4bb] Problem in finding a MR solution

[Jon Cooper]

Hello, have you tried the 'pointless' option to use one of the 
structures/datasets as a reference, then there should not be a need to do MR on 
the others, since they will all be indexed consistently. Sorry if that is what 
you meant below. Cheers, Jon Cooper.

Sent from ProtonMail mobile

 Original Message 
On 11 Dec 2020, 12:01, Suraj Kumar mandal wrote:

> Dear Sir,
>
> Yes, we have checked handedness also. We are using the same MR solution with 
> other data.
>
> With best regards
> Suraj
>
> On Fri, Dec 11, 2020 at 4:56 PM srajan kapoor  wrote:
>
>> Have you checked for handedness to solve this problem?.
>> You can also try to use the structure that you have solved for molecular 
>> Replacement of the other crystals.
>> I have only two things in mind currently. I hope it will work for you.
>>
>> On Fri, Dec 11, 2020, 4:48 PM Suraj Kumar mandal  
>> wrote:
>>
>>> Dear All,
>>>
>>> We are trying to solve a structure of a protein, for which we have 
>>> collected five different home source data at 3.2-3.5 Ang resolution. We are 
>>> processing the data using iMOSFLM and the program suggests P3 (and related) 
>>> space groups for all the data. We are able to get a solution with one data 
>>> (twinned) in C2 space group with Rw/Rf of 26/28%. However, the same 
>>> solution can not be obtained using other four data. Interestingly, one of 
>>> these four data is not twinned. The only common thing in these four data, I 
>>> find, is that they are crystallized in the same crystallization condition, 
>>> whereas, the data which gives solution is crystallized in another condition.
>>>
>>> The template has 69% sequence identity with the target protein.
>>>
>>> Any suggestion to troubleshoot this would be appreciated.
>>>
>>> With best regards,
>>> Suraj
>>>
>>> --
>>>
>>> Suraj Kr. Mandal
>>> Research Scholar
>>> Structural and Computational Biology Lab
>>> Department of Biosciences and Bioengineering
>>> Indian Institute of Technology (IIT), Guwahati
>>> Guwahati, Assam 781039
>>> Ph.: 09678244566
>>> E.mail: tuoamicosu...@gmail.com surajkrman...@iitg.ernet.in
>>>
>>> ---
>>>
>>> To unsubscribe from the CCP4BB list, click the following link:
>>> https://www.jiscmail.ac.uk/cgi-bin/WA-JISC.exe?SUBED1=CCP4BB=1
>
> --
>
> Suraj Kr. Mandal
> Research Scholar
> Structural and Computational Biology Lab
> Department of Biosciences and Bioengineering
> Indian Institute of Technology (IIT), Guwahati
> Guwahati, Assam 781039
> Ph.: 09678244566
> E.mail: tuoamicosu...@gmail.com surajkrman...@iitg.ernet.in
>
> ---
>
> To unsubscribe from the CCP4BB list, click the following link:
> https://www.jiscmail.ac.uk/cgi-bin/WA-JISC.exe?SUBED1=CCP4BB=1



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Re: [ccp4bb] Problem in finding a MR solution

[Eleanor Dodson]

Well - C2 is a sub cell for P3 so that isnt surprising, but a cell
difference of 202 to 212 means it isnt isomorphous..
But an
Rw Rf/ of 26/31 isnt bad for such low resolution data?
Eleanor

On Fri, 11 Dec 2020 at 12:01, Suraj Kumar mandal 
wrote:

> Dear Sir,
>
> Yes, we have checked handedness also. We are using the same MR solution
> with other data.
>
>
> With best regards
> Suraj
>
>
>
> On Fri, Dec 11, 2020 at 4:56 PM srajan kapoor 
> wrote:
>
>> Have you checked for handedness to solve this problem?.
>> You can also try to use the structure that you have solved for molecular
>> Replacement of the other crystals.
>> I have only two things in mind currently. I hope it will work for you.
>>
>> On Fri, Dec 11, 2020, 4:48 PM Suraj Kumar mandal 
>> wrote:
>>
>>> Dear All,
>>>
>>> We are trying to solve a structure of a protein, for which we have
>>> collected five different home source data at 3.2-3.5 Ang resolution. We are
>>> processing the data using iMOSFLM and the program suggests P3 (and related)
>>> space groups for all the data. We are able to get a solution with one data
>>> (twinned) in C2 space group with Rw/Rf of 26/28%. However, the same
>>> solution can not be obtained using other four data. Interestingly, one of
>>> these four data is not twinned. The only common thing in these four data, I
>>> find, is that they are crystallized in the same crystallization condition,
>>> whereas, the data which gives solution is crystallized in another condition.
>>>
>>> The template has 69% sequence identity with the target protein.
>>>
>>> Any suggestion to troubleshoot this would be appreciated.
>>>
>>> With best regards,
>>> Suraj
>>>
>>> --
>>> *Suraj Kr. Mandal*
>>> Research Scholar
>>> Structural and Computational Biology Lab
>>> Department of Biosciences and Bioengineering
>>> Indian Institute of Technology (IIT), Guwahati
>>> Guwahati, Assam 781039
>>> Ph.: 09678244566
>>> E.mail: tuoamicosu...@gmail.com
>>>surajkrman...@iitg.ernet.in
>>>
>>> --
>>>
>>> To unsubscribe from the CCP4BB list, click the following link:
>>> https://www.jiscmail.ac.uk/cgi-bin/WA-JISC.exe?SUBED1=CCP4BB=1
>>>
>>
>
> --
> *Suraj Kr. Mandal*
> Research Scholar
> Structural and Computational Biology Lab
> Department of Biosciences and Bioengineering
> Indian Institute of Technology (IIT), Guwahati
> Guwahati, Assam 781039
> Ph.: 09678244566
> E.mail: tuoamicosu...@gmail.com
>surajkrman...@iitg.ernet.in
>
> --
>
> To unsubscribe from the CCP4BB list, click the following link:
> https://www.jiscmail.ac.uk/cgi-bin/WA-JISC.exe?SUBED1=CCP4BB=1
>



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Re: [ccp4bb] External: Re: [ccp4bb] AlphaFold: more thinking and less pipetting (?)

[Brandstetter Johann]

Eventually computational methods (like AlphaFold) should provide reliable 
information on the spectrum of metastable conformational substates that a 
protein can adopt, i.e. its dynamics. This information will be valuable to 
answer the question of a protein's function, and also of its crystallization - 
and if it is only: difficult!

Best,
Hans

-Original Message-
From: CCP4 bulletin board  On Behalf Of Bryan Lepore
Sent: Freitag, 11. Dezember 2020 15:03
To: CCP4BB@JISCMAIL.AC.UK
Subject: Re: [ccp4bb] External: Re: [ccp4bb] AlphaFold: more thinking and less 
pipetting (?)

> On Dec 11, 2020, at 07:42, Phil Evans  wrote:
> 
> But I’ve always thought the more interesting question is “this is the 
> structure, what does it do?”

It sounds compelling though, that methods of the sort implemented in the CASP 
work are perfectly poised to make progress on the question:

“how might this protein crystallize?”

-Bryan W. Lepore


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Re: [ccp4bb] External: Re: [ccp4bb] AlphaFold: more thinking and less pipetting (?)

[Bryan Lepore]

> On Dec 11, 2020, at 07:42, Phil Evans  wrote:
> 
> But I’ve always thought the more interesting question is “this is the 
> structure, what does it do?”

It sounds compelling though, that methods of the sort implemented in the CASP 
work are perfectly poised to make progress on the question:

“how might this protein crystallize?”

-Bryan W. Lepore


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Re: [ccp4bb] External: Re: [ccp4bb] AlphaFold: more thinking and less pipetting (?)

[Panne, Daniel (Prof.)]

I agree with Phil!

Yes, it is nice to be able to obtain better models but interesting biological 
function resides usually in the most variable and least predictable features of 
a protein, how it associates with other proteins etc. Even when a fold can 
predicted, such folds alone frequently fail to predict function (which doomed 
structural genomics from the outset).

Daniel




On 11 Dec 2020, at 12:42, Phil Evans 
mailto:p...@mrc-lmb.cam.ac.uk>> 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 
mailto: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 mailto:CCP4BB@JISCMAIL.AC.UK>> 
on behalf of Leonid Sazanov mailto:saza...@ist.ac.at>>
Sent: 11 December 2020 10:36
To: CCP4BB@JISCMAIL.AC.UK 
mailto: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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Re: [ccp4bb] Coming July 29: Improved Carbohydrate Data at the PDB -- N-glycans are now separate chains if more than one residue

[Marcin Wojdyr]

Dear Jasmine,

I fully agree with this recommendation:

> To use the wwPDB-assigned chain ID in publications,
> _atom_site.auth_seq_id _atom_site.auth_comp_id, and
> _atom_site.auth_asym_id can be used for the residue number, residue ID,
> and chain ID, respectively.

It would help a lot if the same was recommended in the mmCIF documentation.
Currently, these IDs are described as non-mandatory, alternative IDs,
which suggests (to those few software developers that read the
documentation) that they shouldn't be relied upon.

It'd also be good if the IDs that are recommended for use in
publications weren't changed afterwards as it happened in this
remediation.
Carbohydrate remediation was indeed consulted with the community over
a long time, but perhaps this particular change wasn't made clear. I
always assumed that only the primary (wwPDB internal) IDs are to be
changed, not the ones that were used in publications.

Best regards,
Marcin



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Re: [ccp4bb] External: Re: [ccp4bb] AlphaFold: more thinking and less pipetting (?)

[Phil Evans]

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  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  on behalf of Leonid Sazanov 
> 
> Sent: 11 December 2020 10:36
> To: 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
> 
> 
> 
> To unsubscribe from the CCP4BB list, click the following link:
> https://www.jiscmail.ac.uk/cgi-bin/WA-JISC.exe?SUBED1=CCP4BB=1
> 
> This message was issued to members of www.jiscmail.ac.uk/CCP4BB, a mailing 
> list hosted by www.jiscmail.ac.uk, terms & conditions are available at 
> https://www.jiscmail.ac.uk/policyandsecurity/
> 
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> 



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Re: [ccp4bb] External: Re: [ccp4bb] AlphaFold: more thinking and less pipetting (?)

[Leonid Sazanov]

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  on behalf of 
Leonid Sazanov 

*Sent:* 11 December 2020 10:36
*To:* 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



To unsubscribe from the CCP4BB list, click the following link:
https://www.jiscmail.ac.uk/cgi-bin/WA-JISC.exe?SUBED1=CCP4BB=1 



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, a mailing list hosted by 
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--
Prof. Leonid Sazanov FRS
IST Austria
Am Campus 1
A-3400 Klosterneuburg
Austria

Phone: +43 2243 9000 3026
E-mail: saza...@ist.ac.at




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Re: [ccp4bb] External: Re: [ccp4bb] AlphaFold: more thinking and less pipetting (?)

[Tristan Croll]

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  on behalf of Leonid Sazanov 

Sent: 11 December 2020 10:36
To: 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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Re: [ccp4bb] Problem in finding a MR solution

[Suraj Kumar mandal]

Dear Sir,

Yes, we have checked handedness also. We are using the same MR solution
with other data.


With best regards
Suraj



On Fri, Dec 11, 2020 at 4:56 PM srajan kapoor 
wrote:

> Have you checked for handedness to solve this problem?.
> You can also try to use the structure that you have solved for molecular
> Replacement of the other crystals.
> I have only two things in mind currently. I hope it will work for you.
>
> On Fri, Dec 11, 2020, 4:48 PM Suraj Kumar mandal 
> wrote:
>
>> Dear All,
>>
>> We are trying to solve a structure of a protein, for which we have
>> collected five different home source data at 3.2-3.5 Ang resolution. We are
>> processing the data using iMOSFLM and the program suggests P3 (and related)
>> space groups for all the data. We are able to get a solution with one data
>> (twinned) in C2 space group with Rw/Rf of 26/28%. However, the same
>> solution can not be obtained using other four data. Interestingly, one of
>> these four data is not twinned. The only common thing in these four data, I
>> find, is that they are crystallized in the same crystallization condition,
>> whereas, the data which gives solution is crystallized in another condition.
>>
>> The template has 69% sequence identity with the target protein.
>>
>> Any suggestion to troubleshoot this would be appreciated.
>>
>> With best regards,
>> Suraj
>>
>> --
>> *Suraj Kr. Mandal*
>> Research Scholar
>> Structural and Computational Biology Lab
>> Department of Biosciences and Bioengineering
>> Indian Institute of Technology (IIT), Guwahati
>> Guwahati, Assam 781039
>> Ph.: 09678244566
>> E.mail: tuoamicosu...@gmail.com
>>surajkrman...@iitg.ernet.in
>>
>> --
>>
>> To unsubscribe from the CCP4BB list, click the following link:
>> https://www.jiscmail.ac.uk/cgi-bin/WA-JISC.exe?SUBED1=CCP4BB=1
>>
>

-- 
*Suraj Kr. Mandal*
Research Scholar
Structural and Computational Biology Lab
Department of Biosciences and Bioengineering
Indian Institute of Technology (IIT), Guwahati
Guwahati, Assam 781039
Ph.: 09678244566
E.mail: tuoamicosu...@gmail.com
   surajkrman...@iitg.ernet.in



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Re: [ccp4bb] Problem in finding a MR solution

[Suraj Kumar mandal]

Dear Madam,

All the data set have the similar cell dimensions. The only difference I
observe is that the data which gives solution in C2 space group has the
cell dimensions as a=140, b=80, *c=202*, alpha=beta=gamma=90.

We tried processing other data in C2 space group (forcefully) with cell
dimensions as a=140, b=80, *c=212*, alpha=beta=gamma=90.However, we do not
find solution with these data, including the one with no twinning.

We do find solution in P3 ( a=b=80, c=212, alpha=beta=90 and gamma=120)
with Rw/Rf with 26/31, but it can not be refined further.

Please let me know if you need any other information in this regard.

Thanking you.

With best regards,
Suraj

On Fri, Dec 11, 2020 at 5:08 PM Eleanor Dodson 
wrote:

> Do all data sets have similar cell dimensions.
> P3i can be indexed in a variety of ways, (h k l ) (k,h,-l) etc - refer to
> documentation on reindexing..
>
>-
>All *P3i* and *R3*:
>(h,k,l) *not* equivalent to (-h,-k,l) *or* (k,h,-l) or (-k,-h,-l) so
>we need to check all 4 possibilities:
>
> So can you merge the data sets? The data processing task can do that I
> think.
> Check index conventions then treat each data set as a "run" and see how
> well they ageee.
> Eleanor
>
> On Fri, 11 Dec 2020 at 11:18, Suraj Kumar mandal 
> wrote:
>
>> Dear All,
>>
>> We are trying to solve a structure of a protein, for which we have
>> collected five different home source data at 3.2-3.5 Ang resolution. We are
>> processing the data using iMOSFLM and the program suggests P3 (and related)
>> space groups for all the data. We are able to get a solution with one data
>> (twinned) in C2 space group with Rw/Rf of 26/28%. However, the same
>> solution can not be obtained using other four data. Interestingly, one of
>> these four data is not twinned. The only common thing in these four data, I
>> find, is that they are crystallized in the same crystallization condition,
>> whereas, the data which gives solution is crystallized in another condition.
>>
>> The template has 69% sequence identity with the target protein.
>>
>> Any suggestion to troubleshoot this would be appreciated.
>>
>> With best regards,
>> Suraj
>>
>> --
>> *Suraj Kr. Mandal*
>> Research Scholar
>> Structural and Computational Biology Lab
>> Department of Biosciences and Bioengineering
>> Indian Institute of Technology (IIT), Guwahati
>> Guwahati, Assam 781039
>> Ph.: 09678244566
>> E.mail: tuoamicosu...@gmail.com
>>surajkrman...@iitg.ernet.in
>>
>> --
>>
>> To unsubscribe from the CCP4BB list, click the following link:
>> https://www.jiscmail.ac.uk/cgi-bin/WA-JISC.exe?SUBED1=CCP4BB=1
>>
>

-- 
*Suraj Kr. Mandal*
Research Scholar
Structural and Computational Biology Lab
Department of Biosciences and Bioengineering
Indian Institute of Technology (IIT), Guwahati
Guwahati, Assam 781039
Ph.: 09678244566
E.mail: tuoamicosu...@gmail.com
   surajkrman...@iitg.ernet.in



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Re: [ccp4bb] Problem in finding a MR solution

[Eleanor Dodson]

Do all data sets have similar cell dimensions.
P3i can be indexed in a variety of ways, (h k l ) (k,h,-l) etc - refer to
documentation on reindexing..

   -
   All *P3i* and *R3*:
   (h,k,l) *not* equivalent to (-h,-k,l) *or* (k,h,-l) or (-k,-h,-l) so we
   need to check all 4 possibilities:

So can you merge the data sets? The data processing task can do that I
think.
Check index conventions then treat each data set as a "run" and see how
well they ageee.
Eleanor

On Fri, 11 Dec 2020 at 11:18, Suraj Kumar mandal 
wrote:

> Dear All,
>
> We are trying to solve a structure of a protein, for which we have
> collected five different home source data at 3.2-3.5 Ang resolution. We are
> processing the data using iMOSFLM and the program suggests P3 (and related)
> space groups for all the data. We are able to get a solution with one data
> (twinned) in C2 space group with Rw/Rf of 26/28%. However, the same
> solution can not be obtained using other four data. Interestingly, one of
> these four data is not twinned. The only common thing in these four data, I
> find, is that they are crystallized in the same crystallization condition,
> whereas, the data which gives solution is crystallized in another condition.
>
> The template has 69% sequence identity with the target protein.
>
> Any suggestion to troubleshoot this would be appreciated.
>
> With best regards,
> Suraj
>
> --
> *Suraj Kr. Mandal*
> Research Scholar
> Structural and Computational Biology Lab
> Department of Biosciences and Bioengineering
> Indian Institute of Technology (IIT), Guwahati
> Guwahati, Assam 781039
> Ph.: 09678244566
> E.mail: tuoamicosu...@gmail.com
>surajkrman...@iitg.ernet.in
>
> --
>
> To unsubscribe from the CCP4BB list, click the following link:
> https://www.jiscmail.ac.uk/cgi-bin/WA-JISC.exe?SUBED1=CCP4BB=1
>



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[ccp4bb] Problem in finding a MR solution

[Suraj Kumar mandal]

Dear All,

We are trying to solve a structure of a protein, for which we have
collected five different home source data at 3.2-3.5 Ang resolution. We are
processing the data using iMOSFLM and the program suggests P3 (and related)
space groups for all the data. We are able to get a solution with one data
(twinned) in C2 space group with Rw/Rf of 26/28%. However, the same
solution can not be obtained using other four data. Interestingly, one of
these four data is not twinned. The only common thing in these four data, I
find, is that they are crystallized in the same crystallization condition,
whereas, the data which gives solution is crystallized in another condition.

The template has 69% sequence identity with the target protein.

Any suggestion to troubleshoot this would be appreciated.

With best regards,
Suraj

-- 
*Suraj Kr. Mandal*
Research Scholar
Structural and Computational Biology Lab
Department of Biosciences and Bioengineering
Indian Institute of Technology (IIT), Guwahati
Guwahati, Assam 781039
Ph.: 09678244566
E.mail: tuoamicosu...@gmail.com
   surajkrman...@iitg.ernet.in



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Re: [ccp4bb] External: Re: [ccp4bb] AlphaFold: more thinking and less pipetting (?)

[Leonid Sazanov]

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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