[ccp4bb] Off Topic: CCP4MG Help

[Whitley, Matthew J]

Hello all,

Looking for advice from any CCP4MG users.

I am making some structural figures and have run into a problem.  I posted a 
question to the CCP4MG-specific email list quite a while ago but received no 
responses, so I don't know if that list is still active.

Essentially, I want to change the color of a small stretch of residues within 
the larger protein chain.  For example, I want to display a protein running 
from residues 1-100 in gray using the ribbons representation, and I want to 
change only residues 50-60 to red, also in the ribbons representation.

If I try to accomplish this in CCP4MG by creating two different display 
objects, {1-49, 61-100} and {50-60}, I can change the colors as desired, but 
gaps appear at the interfaces between the segments of the ribbons 
representation, i.e. between residues 49 and 50, and then between residues 60 
and 61.  Is there a way to plug those gaps such that the structure is smoothly 
connected from 1-100 in the ribbons representation?  When I display the 
structure using the cylinders representation, everything is smoothly connected 
with the correct colors, but when I change to ribbons representation, the gaps 
appear.  Any ideas?

Alternatively, there's got to be a way simply to change the color of a subset 
of residues within a chain without having to create an individual display 
object for each segment, but if it exists it has escaped me.

Thanks for any advice you can provide.

Matthew

---
Matthew J. Whitley, Ph.D.
Research Instructor
Department of Pharmacology & Chemical Biology
University of Pittsburgh School of Medicine




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Re: [ccp4bb] Micro/Macro crystal seeding experience

[Whitley, Matthew J]

I want to second the recommendation to try microseed matrix screening.  I 
recently had a case of a protein that did not yield any crystals after trying 
more than 500 conditions.  Of those 500, one single condition gave to me what 
appeared to be crystalline material, but not distinct single crystals.  I 
harvested that well, crushed up the material as best I could to make a seed 
stock, and then used the seed stock with the first 48 conditions of I think the 
JCSG+ screen.  Came back the next day, checked the trays under the microscope, 
and was astonished to find at least 10 wells that had gorgeous crystals in 
them.  I harvested a few crystals from different wells, shot them at the 
Advanced Photon Source, and nearly fainted when diffraction to almost 1 Å 
popped up on the monitor for almost all of them.  So, you could say I’m a 
believer in random microseed matrix screening now …

Good luck.

Matthew

---
Matthew J. Whitley, Ph.D.
Research Instructor
Department of Pharmacology & Chemical Biology
University of Pittsburgh School of Medicine

--

Date:Thu, 17 Dec 2020 21:54:15 +
From:David Briggs 
Subject: Re: Micro/Macro crystal seeding experience

Hi Rafael, there are many potential answers to questions such as this.

Here are the first few that spring to mind:


  1.  Did you test room temperature diffraction? Is it your cryo-protectant 
that is causing problems.
  2.  What is your cryo-cooling protocol? Do you just dunk the crystals 
straight in to crystallisation liquor + 30% glycerol, or do you slowly step up 
the cryo-protectant concentration?
  3.  Additive screens are worth a try.
  4.  Modify the construct (trim termini, tags, or disordered loop regions).
  5.  Microseed matrix screening to look for alternative conditions. 
(https://nam12.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.douglas.co.uk%2Fmms.htmdata=04%7C01%7Cmjw100%40PITT.EDU%7C5f603236dfef49d09b5308d8a2d6b188%7C9ef9f489e0a04eeb87cc3a526112fd0d%7C1%7C0%7C637438390278906705%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000sdata=JJ1pHkScwTx8%2FJCZPXY9DYlIzosr9j67alrdsXIseCY%3Dreserved=0)

Good luck!

Dave

--
Dr David C. Briggs
Senior Laboratory Research Scientist
Signalling and Structural Biology Lab
The Francis Crick Institute
London, UK
==
about.me/david_briggs




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Re: [ccp4bb] Hydrogens in PDB File

[Whitley, Matthew J]

Hi Ethan, thanks for your reply.  The correct situation is the former: 
hydrogens added at idealized positions *before* refinement and then subjected 
to refinement along with the rest of the model.

After refinement, MolProbity (the online server) does indeed remove any 
hydrogens in the PDB file and add them back at idealized positions for the 
purpose of its calculations, but I am most definitely *not* talking about 
depositing these post-refinement hydrogens manipulated by MolProbity.

Matthew

---
Matthew J. Whitley, Ph.D.
Research Instructor
Department of Pharmacology & Chemical Biology
University of Pittsburgh School of Medicine

From: Ethan A Merritt<mailto:merr...@uw.edu>
Sent: Thursday, February 27, 2020 6:57 PM
To: Whitley, Matthew J<mailto:mjw...@pitt.edu>
Cc: CCP4BB@jiscmail.ac.uk<mailto:CCP4BB@jiscmail.ac.uk>
Subject: Re: [ccp4bb] Hydrogens in PDB File

On Thursday, 27 February 2020 15:35:05 PST Whitley, Matthew J wrote:
> Hello all,
>
> I am nearly finished refining the structures of two mutant proteins from
> crystals that diffracted to very high resolution, 1 Å and 1.2 Å,
> respectively.  Refinement was conducted in the presence of explicit
> hydrogens on the models.  I am preparing to deposit these models into the
> PDB but am unsure about whether to retain or remove the hydrogens for
> deposition.  On one hand, these hydrogens were explicitly used during
> refinement, so that makes me want to keep them, but on the other hand, they
> were added at theoretical positions by MolProbity’s reduce tool for
> refinement and were not positioned on the basis of experimentally observed
> electron density, so that makes me want to delete them from the
> experimental model.  Which is the preferred option for this situation?

The order of operations you describe is unclear.

If you explicitly refined hydrogens then their final positions are indeed
based on experimentally determined data.
The fact that you initially placed them into ideal geometry is not really
any different from the non-H atoms of individual protein residues in your
model, whose original positions were also based on known stereochemistry.

On the other hand, if you mean that the hydrogens you used for refinement
were deleted and replaced during validation by Molprobity (which I think it
may do by default) that's not good.  You should rather keep the hydrogen
positions from refinement, not the ones from Molprobity.

Assuming (since this is ccp4bb) you refined with refmac...
- If you are at the level of investigating hydrogen positions, you may want
to consider taking the refinement into shelxl.
- If you are not making claims about hydrogens but just want to describe
what you did during refinement, I'd go with taking them out and settling
for the standard record in the resulting PDB file:
  REMARK   3  HYDROGENS HAVE BEEN ADDED IN THE RIDING POSITIONS
which looks like this in the corresponding mmcif file:
  _refine.details   'Hydrogens have been added in their riding positions'

Ethan

>
> Thanks,
> Matthew
>
> ---
> Matthew J. Whitley, Ph.D.
> Research Instructor
> Department of Pharmacology & Chemical Biology
> University of Pittsburgh School of Medicine
>
>
> 
>
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--
Ethan A Merritt
Biomolecular Structure Center,  K-428 Health Sciences Bldg
MS 357742,   University of Washington, Seattle 98195-7742





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[ccp4bb] Hydrogens in PDB File

[Whitley, Matthew J]

Hello all,

I am nearly finished refining the structures of two mutant proteins from 
crystals that diffracted to very high resolution, 1 Å and 1.2 Å, respectively.  
Refinement was conducted in the presence of explicit hydrogens on the models.  
I am preparing to deposit these models into the PDB but am unsure about whether 
to retain or remove the hydrogens for deposition.  On one hand, these hydrogens 
were explicitly used during refinement, so that makes me want to keep them, but 
on the other hand, they were added at theoretical positions by MolProbity’s 
reduce tool for refinement and were not positioned on the basis of 
experimentally observed electron density, so that makes me want to delete them 
from the experimental model.  Which is the preferred option for this situation?

Thanks,
Matthew

---
Matthew J. Whitley, Ph.D.
Research Instructor
Department of Pharmacology & Chemical Biology
University of Pittsburgh School of Medicine




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Re: [ccp4bb] W. Friedrich's thesis title

[Whitley, Matthew J]

In the 2019 book Wilhelm Conrad Röntgen: The Birth of Radiology by Gerd 
Rosenbusch and Annemarie de Knecht-van Eekelen, there is a table of all the 
doctoral and/or habilitation students supervised by Röntgen.


In this table, Walter Friedrich's dissertation is dated 24 July 1911 and 
carries the German title "Räumliche Intensitätsverteilung der X-Strahlen, die 
von einer Platina Antikathode ausgehen."  My own translation would be "Spatial 
distribution of the intensity of x-rays emanating from a platinum target."


The table also mentions that the chief results of the dissertation were 
published in the following article in 1912:   Ann. Physik, volume 344, pages 
377-430.


Hope this helps.


Matthew



---
Matthew J. Whitley, Ph.D.
Research Instructor
Department of Pharmacology & Chemical Biology
University of Pittsburgh School of Medicine



From: CCP4 bulletin board  on behalf of CCP4BB automatic 
digest system 
Sent: Monday, June 10, 2019 7:00 PM
To: CCP4BB@JISCMAIL.AC.UK
Subject: CCP4BB Digest - 9 Jun 2019 to 10 Jun 2019 (#2019-165)

Date:Mon, 10 Jun 2019 11:07:12 +0100
From:Harry Powell 
Subject: W. Friedrich's thesis title

Hi folks

I've been trying to track down the title of Friedrich's (of Friedrich and 
Knipping fame) 1911 thesis at Ludwig-Maximilians Universität, München - all I 
can find is a translation into English. I don't want my personal (or google 
translate or similar) back in to German, so I was wondering if anyone out there 
actually knows what it was?

I've had a search on the LMU library website, but can't find the thesis indexed 
there...

The English translation is "Emission by a platinum target".

Harry
--
Dr Harry Powell




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Re: [ccp4bb] weak anomalous phasing (magic triangle I3C)

[Whitley, Matthew J]

Hi Tiantian,


You say you have a 'co-crystal' of your protein with the magic triangle, but 
how do you really know that I3C is there?  The fact that you put it into the 
crystallization drop doesn't necessarily mean that it made it into the crystal.


In fact, based on the  output of shelxc that you provided in your 
original email, it seems to me that your data have very little anomalous 
signal.   can be taken as a measure of the strength of the anomalous 
signal, and it typically starts at high values in the lowest resolution shells 
and then falls off asymptotically to a value of ~0.8 at high resolution.  
Therefore, 0.8 can be taken as a general indicator of 'no anomalous signal."  
Your  values are relatively constant at about 0.7-1.0 across the 
entire resolution range of your data, and therefore I would say that you have 
little or no anomalous signal in the data.  I therefore wonder whether the I3C 
is actually bound at all.  In my personal experience, I would be very surprised 
indeed if this data set were to give a successful SAD solution.  The lack of 
useful anomalous signal is reflected in the fact that your CCall/CCweak values 
are so low, indicating to me that, unfortunately, the phase problem is not yet 
successfully solved.


Good luck in your future phasing trials!


Matthew


---
Matthew J. Whitley, Ph.D.
Research Instructor
Department of Pharmacology & Chemical Biology
University of Pittsburgh School of Medicine



From: CCP4 bulletin board  on behalf of CCP4BB automatic 
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Sent: Thursday, April 25, 2019 7:01 PM
To: CCP4BB@JISCMAIL.AC.UK
Subject: CCP4BB Digest - 24 Apr 2019 to 25 Apr 2019 (#2019-124)

Date:Thu, 25 Apr 2019 11:05:05 -0400
From:ChenTiantian 
Subject: weak anomalous phasing (magic triangle I3C)

Dear all,

I'm working on a 18kD protein, the secondary structure prediction says most
of the structure is beta sheets, trying to solve the structure with SAD.
Heavy atom soaking gives several datasets with I, W, Au, range from
2.7~3.7A, however, the anomalous signal is pretty weak, I couldn't find a
reasonable solution.
We got a co-crystal dataset with the magic triangle I3C, extends to around
2.5A, this is the best data we got so far.
shelxc gives me the following result:

 Resl.   Inf. 12.59  7.75  5.84  4.77  4.08  3.59  3.22  2.94  2.70  2.51
2.35

 N(data)  79   257   429   635   811  1010  1235  1384  1698  1555  1954

 Chi-sq 0.69  0.63  0.60  0.67  0.61  0.88  1.05  1.02  0.80  0.55  0.42

 79.4  34.1  30.3  32.2  31.8  26.6  21.1  14.6   8.3   3.9   2.4

 %Complete  94.0  98.1  97.5  99.5  99.4  99.0  99.7 100.0  99.9  85.4  96.1

 Multipl.4.0   4.5   3.9   4.5   4.7   4.2   4.4   4.8   5.0   4.3   4.4

 R(pim)%2.27  1.72  2.29  2.05  2.02  2.62  3.51  4.84  7.90 14.43 22.78

 Ranom% 6.49  3.68  5.19  4.29  4.27  6.35  9.50 12.97 20.90 33.58 52.21

0.73  0.80  1.08  0.85  0.95  1.03  1.00  0.91  0.85  0.78  0.70

 CC(1/2) 5.1  41.7  68.8  38.1  42.7  49.9  49.9  25.5  24.9  13.3  -4.7

then I tried shelxd with different heavy atom sites number and resolution
cut, the best CC I got is CC/CCweak: 24.75/7.69,
and I can identify a triangle, (length: 6.5/6.5/5.0A), however, both shelxe
and autosol didn't end up with a promising result.

[image: image.png]
It would be great if anyone can give me some suggestions.

Thank you in advance!
--
Tiantian





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[ccp4bb] Electron scattering factors for SHELXL

[Whitley, Matthew J]

Greetings all,


We have solved a small molecule structure using electron diffraction and would 
like to refine the structure with SHELXL.  Coming from a macromolecular 
background, this is our first experience with SHELXL, and we are not exactly 
sure how to proceed.  The first thing to do seems to be to provide SHELXL the 
appropriate electron scattering factors for 200 keV electrons.  Can someone 
suggest the best way to do this?  Or, alternatively, if anyone has used a 
different program to refine small molecule structures determined by ED, we 
would be happy to hear about that program too.


Thanks in advance for your advice.

Matthew


---
Matthew J. Whitley, Ph.D.
Research Instructor
Department of Pharmacology & Chemical Biology
University of Pittsburgh School of Medicine



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Re: [ccp4bb] Off topic: 'Difficult' Datasets for Processing Practice

[Whitley, Matthew J]

Hi Andrew,


Thanks very much for your reply.


I have taken a look at the example data sets you referred me to, and I am most 
interested in example 7, the case with multiple lattices.  I will process this 
one myself and might include it during my tutorials.  This is for the Cold 
Spring Harbor x-ray course which takes place later this month.


Sincerely,

Matthew


---
Matthew J. Whitley, Ph.D.
Research Instructor
Department of Pharmacology & Chemical Biology
University of Pittsburgh School of Medicine



From: Andrew Leslie 
Sent: Thursday, September 27, 2018 5:41 AM
To: Whitley, Matthew J
Cc: ccp4bb
Subject: Re: [ccp4bb] Off topic: 'Difficult' Datasets for Processing Practice

Dear Matthew,

   I am also late in responding to this, but as part of a 
Nature Protocols paper on iMosflm (Supplementary Information for Nature 
Protocols 12, 1310-1325, 2017) I provided a number of examples of “problem 
datasets”. Some of these are just two images, to show issues in indexing, 
others are complete datasets showing a variety of pathologies.

All the images and a tutorial on how best to process them (with iMosflm) are 
available at the following URL:

www.mrc-lmb.cam.ac.uk/harry/imosflm/examples<https://na01.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.mrc-lmb.cam.ac.uk%2Fharry%2Fimosflm%2Fexamples=02%7C01%7Cmjw100%40PITT.EDU%7Cd146604484cb4dd13f5008d6245d717e%7C9ef9f489e0a04eeb87cc3a526112fd0d%7C1%7C0%7C636736381099125261=EzdbGDpEO126WIYz85Nj9QPvfuDXI31nj14OvyjjHzM%3D=0>


Best wishes,

Andrew


On 26 Sep 2018, at 03:15, Whitley, Matthew J 
mailto:mjw...@pitt.edu>> wrote:

For some reason, the September 19th ccp4bb digest got caught in my spam filter 
and didn't come through until a few minutes ago, so I didn't see several 
responses concerning interesting datasets for processing until just now.

Therefore, thanks also to Kay Diederichs, Eugene Osipov, and David Waterman for 
responding (and also to everyone else who responded if I am still overlooking 
anyone.)

As I mentioned before, I will be happy to compile a list of suggested datasets 
and make it available via this list.

Matthew


---
Matthew J. Whitley, Ph.D.
Research Instructor
Department of Pharmacology & Chemical Biology
University of Pittsburgh School of Medicine



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Re: [ccp4bb] Off topic: 'Difficult' Datasets for Processing Practice

[Whitley, Matthew J]

For some reason, the September 19th ccp4bb digest got caught in my spam filter 
and didn't come through until a few minutes ago, so I didn't see several 
responses concerning interesting datasets for processing until just now.

Therefore, thanks also to Kay Diederichs, Eugene Osipov, and David Waterman for 
responding (and also to everyone else who responded if I am still overlooking 
anyone.)

As I mentioned before, I will be happy to compile a list of suggested datasets 
and make it available via this list.

Matthew


---
Matthew J. Whitley, Ph.D.
Research Instructor
Department of Pharmacology & Chemical Biology
University of Pittsburgh School of Medicine



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Re: [ccp4bb] Off topic: 'Difficult' Datasets for Processing Practice

[Whitley, Matthew J]

Dear colleagues,

I want to thank the following people for providing suggestions and comments 
about ‘difficult’ datasets suitable for teaching data processing:

Tim Craig
Jacob Keller
Graeme Winter
Aleksandar Bijelic
Clemens Vonrhein
Loes Kroon-Batenburg
James Holton

If anyone else has suggestions for good datasets for teaching processing, I 
would still be happy to hear them.

Finally, several people asked me to make available a list of all the dataset 
suggestions I receive.  I am happy to do so, and I will post a message to this 
list when the information is up and available, probably later in the fall.


Sincerely,
Matthew



---
Matthew J. Whitley, Ph.D.
Research Instructor
Department of Pharmacology & Chemical Biology
University of Pittsburgh School of Medicine




On 9/19/2018 5:15 PM, Whitley, Matthew J wrote:
Dear colleagues,

For teaching purposes, I am looking for a small number (< 5) of
macromolecular diffraction datasets (raw images) that might be
considered 'difficult' for a beginning crystallography student to
process.  By 'difficult' I generally mean not able to be processed
automatically by a common processing package (XDS, Mosflm, DIALS, etc)
using default settings, i.e., no black box "click and done" processing.
The datasets I am looking for would have some stumbling block such as
incorrect experimental parameters recorded in the image headers,
multiple lattices that cause indexing to fail, datasets for which
determining the correct space group is tricky, datasets for experiments
in which the crystal slipped or moved in the beam, or anything else you
can think of.  The idea is for these beginning students to examine
several datasets that highlight various phenomena that can lead one
astray during processing.

A good candidate dataset would also ideally comprise a modest number of
images so as to keep integration time to a minimum.  Factors that are
mostly irrelevant for my purpose: resolution (as long as better than
~3.5 Å), source (home vs synchrotron), presence/absence of anomalous
scattering,  presence/absence of ligands, monomeric vs oligomeric
structures, etc.  Also, to be clear, I am not looking for datasets that
have so many pathologies that they would require many long hours of work
for an expert to process correctly.

I have checked public repositories such as 
proteindiffraction.org<http://proteindiffraction.org> and
SBGrid databank, but all of the datasets I acquired from these sources
process satisfactorily with little effort, and in any event I know of no
way to search for 'challenging' datasets.  (I also wonder whether
anybody is in the habit of depositing, shall we say, less-than-pristine
images to public repositories?)

If you know of such a dataset that is already publicly available, or if
you have such a dataset that you are willing to share for solely
educational purposes, I would appreciate hearing from you, either on- or
off-list.

Thank you in advance for your suggestions.

Matthew






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[ccp4bb] Off topic: 'Difficult' Datasets for Processing Practice

[Whitley, Matthew J]

Dear colleagues,

For teaching purposes, I am looking for a small number (< 5) of 
macromolecular diffraction datasets (raw images) that might be 
considered 'difficult' for a beginning crystallography student to 
process.  By 'difficult' I generally mean not able to be processed 
automatically by a common processing package (XDS, Mosflm, DIALS, etc) 
using default settings, i.e., no black box "click and done" processing.  
The datasets I am looking for would have some stumbling block such as 
incorrect experimental parameters recorded in the image headers, 
multiple lattices that cause indexing to fail, datasets for which 
determining the correct space group is tricky, datasets for experiments 
in which the crystal slipped or moved in the beam, or anything else you 
can think of.  The idea is for these beginning students to examine 
several datasets that highlight various phenomena that can lead one 
astray during processing.

A good candidate dataset would also ideally comprise a modest number of 
images so as to keep integration time to a minimum.  Factors that are 
mostly irrelevant for my purpose: resolution (as long as better than 
~3.5 Å), source (home vs synchrotron), presence/absence of anomalous 
scattering,  presence/absence of ligands, monomeric vs oligomeric 
structures, etc.  Also, to be clear, I am not looking for datasets that 
have so many pathologies that they would require many long hours of work 
for an expert to process correctly.

I have checked public repositories such as proteindiffraction.org and 
SBGrid databank, but all of the datasets I acquired from these sources 
process satisfactorily with little effort, and in any event I know of no 
way to search for 'challenging' datasets.  (I also wonder whether 
anybody is in the habit of depositing, shall we say, less-than-pristine 
images to public repositories?)

If you know of such a dataset that is already publicly available, or if 
you have such a dataset that you are willing to share for solely 
educational purposes, I would appreciate hearing from you, either on- or 
off-list.

Thank you in advance for your suggestions.

Matthew

-- 
Matthew J. Whitley, Ph.D.
Department of Pharmacology & Chemical Biology
University of Pittsburgh School of Medicine




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Re: [ccp4bb] Anderson?Evans polyoxotungstate (TEW)

[Whitley, Matthew J.]

I would also be interested in learning whether polyoxotungstate has 
worked wonders for anyone.  At the current price of 387 EUR/gram, it is 
a bit too expensive for us to seriously consider giving it a try.  Yes, 
a gram is a lot of compound and would probably last a long time, but 
there are other things at present that we know would give us more bang 
for our buck euro.  If anyone has any great stories of how it was a game 
changer for them, that would do a lot to motivate us to give it a try.  
Eager to hear about your experiences using the compound.


Thanks,
Matthew

---
Matthew J. Whitley, Ph.D.
Research Instructor
W. Furey Lab
Department of Pharmacology & Chemical Biology
University of Pittsburgh School of Medicine

On 3/30/2018 7:00 PM, CCP4BB automatic digest system wrote:

--
Date:Fri, 30 Mar 2018 20:24:29 +0200
From:Nikolay Dobrev 
Subject: Anderson?Evans polyoxotungstate (TEW)

Dear all,
I apologize for my off-topic question.
I want to ask if anyone has so far used the Anderson-Evans
polyoxotungstate
(https://na01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.jenabioscience.com%2Fcrystallography-cryo-em%2Fscreening%2Fxp-screen%2Fx-tew-anderson-evans-polyoxotungstate=01%7C01%7Cmjw100%40PITT.EDU%7C27d0177bd91c4d421ed508d59692ef9d%7C9ef9f489e0a04eeb87cc3a526112fd0d%7C1=IXVk9RvttYWokRiY2M9H43br5JHo2REjfx9HBML13rI%3D=0).
Did someone see an improvement in crystal quality/diffraction?
Any comments will be highly appreciated.

Nikolay Dobrev



Nikolay Dobrev
PhD Student in AG Sinning & AG Fischer
Biochemie Zentrum
Heidelberg University
Im Neuenheimer Feld 328
69120 Heidelberg
Germany
Phone: +49 6221 54 4796
Email: 

[ccp4bb] CCP4MG error after installation

[Whitley, Matthew J]

Hello all,


After installing ccp4 7.0 and all updates via the package manager on CentOS 6, 
I receive the following error messages upon running ccp4mg:



libpng error: IDAT: invalid distance too far back
QPainter::begin: Paint device returned engine == 0, type: 2
QPainter::end: Painter not active, aborted


The path to the ccp4mg executable on our system is as follows:

/usr/local/ccp4-7.0/ccp4-7.0/bin/ccp4mg



I would appreciate any ideas about the source of the issue and how to resolve 
it.



Sincerely,

Matthew Whitley


---
Matthew J. Whitley, Ph.D.
Research Instructor
W. Furey Lab
Department of Pharmacology & Chemical Biology
University of Pittsburgh School of Medicine

Re: [ccp4bb] Se-Met and Se-Cys double labelling

[Whitley, Matthew J]

I second (or third) the suggestion that others have given to try soaking 
mercury compounds into your crystal.  Mercury absolutely loves free cysteines, 
and if you have 5, you have a great chance of getting binding.  If isomorphism 
is maintained after soaking, the isomorphous differences will be huge, and if 
you can collect data at a synchrotron, then the anomalous signal also opens up 
the possibility of SIRAS phasing.  Everybody seems to have their own favorite 
mercury compound to recommend, and mine is potassium tetraiodomercurate 
(K2HgI4).  Just recently I was able to get mercury binding to three free 
cysteines in my protein with this compound with absolutely no effort 
whatsoever.  I simply dissolved a few grains of compound in an 
acetonitrile/water solution, added a drop to my crystal drop, waited 30 
minutes, and then collected the data.  SHELX was able to locate the sites and 
solve the phases by SIRAS in mere moments.  It couldn't have been easier, and I 
thank the experimental phasing gods for their generosity.  In any event, your 
protein has a large number of free cysteines, so I think you probably have an 
above average chance for some flavor of phasing based on mercury to be 
successful.


Good luck!


Matthew


---
Matthew J. Whitley, Ph.D.
Research Associate
Department of Structural Biology
University of Pittsburgh School of Medicine



From: CCP4 bulletin board  on behalf of CCP4BB automatic 
digest system 
Sent: Wednesday, June 21, 2017 7:01 PM
To: CCP4BB@JISCMAIL.AC.UK
Subject: CCP4BB Digest - 20 Jun 2017 to 21 Jun 2017 (#2017-172)

--

Date:Wed, 21 Jun 2017 17:46:56 +0200
From:Vito Calderone 
Subject: Se-Met and Se-Cys double labelling

I am working on a protein having 360 residues. In its sequence there are 3
Met and 5 free Cys.
I will need MAD to solve the structure since based on the sequence the
closest homologue has 20% identity…I suppose MR would be very unlikely to
work…so I would like to express a selenium derivative to exploit MAD.
Looking in the literature 1 Se-Met every 120 residues seems not to comply
the threshold to get a good anomalous signal. For this reason I would like
to exploit both Met and Cys so I would have 8 seleniums per 360 residues.
Could somenone suggest a reference to a protocol to express the double
mutant protein in NON auxotrophic strains of E. coli which you have
experienced working efficiently?
Thanks

Re: [ccp4bb] CCP4BB Digest - 10 Jan 2017 to 11 Jan 2017 (#2017-12)

[Whitley, Matthew J]

Hi Claire,

Isn’t the simplest answer just that the EDS server is calculating the 
completeness for a different amount of data (high res limit of 1.92 Å), whereas 
in your Depositor data it was only calculated to a high res limit of 2.1 Å?  
This would probably be the result of you measuring reflections out to 1.92 Å 
during data collection but then manually specifying a 2.1 Å high resolution 
cutoff during refinement.  The refinement program will calculate statistics 
based on your input limit of 2.1 Å, but if the MTZ file actually contains some 
measured data out to 1.92 Å, then the EDS would calculate a different, lower 
completeness if its default setting is simply to use all data present in the 
reflections file.  

Does that explain things, or do you actually have something else in mind as to 
the cause of the discrepancy?

Matthew

---
Matthew J. Whitley, Ph.D.
Research Associate
Angela Gronenborn Lab
Department of Structural Biology
University of Pittsburgh School of Medicine


> Date:Wed, 11 Jan 2017 17:31:38 -0500
> From:Claire Smith 
> Subject: PDB validation of structure factors
> 
> Hello,
> 
> I am trying to run the PDB validation report for a structure that I have
> refined in Phenix (data was analyzed with Xtriage). However, the run
> reports a discrepancy on the completeness of data, as follows:
> 
> % Data completeness  97.4 (29.08-2.10)   Depositor
> 
> (in resolution range)87.5 (29.08-1.92)EDS
> 
> 
> Why this discrepancy?
> 
> 
> Thanks so much,
> 
> Claire