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<div>Hi Pavel,</div>
<div><br>
</div>
<div>I think the scaling issue only occurs with pseudo-centering where a significant number of reflections would be systematically weak, which should not be the case with rotational NCS I suppose. </div>
<div><br>
</div>
<div>Best,</div>
<div>Esko<br>
<br>
Sent from my iPhone</div>
<div><br>
On 3 apr 2015, at 20:58, Pavel Afonine <<a href="mailto:pafonine@lbl.gov">pafonine@lbl.gov</a>> wrote:<br>
<br>
</div>
<blockquote type="cite">
<div>Hi Esko,<br>
<br>
thanks for the paper - very interesting!<br>
<br>
Perhaps accounting for ptNCS matters a lot for structure solution or/and refinement/model building at early stages, however I did not see any problem with refinement in this particular example.
<br>
<br>
Here is what I did:<br>
<br>
1) Get model and data from PDB:<br>
<br>
phenix.fetch_pdb 1yup --mtz<br>
<br>
2) Get initial statistics: R-factors from PDB file header, geometry using command:<br>
<br>
phenix.pdbtools model_stat=true 1yup.pdb<br>
<br>
Rwork=0.235 Rfree=0.311<br>
all-atom clashscore : 8.21<br>
ramachandran plot:<br>
outliers : 1.52 %<br>
allowed : 7.43 %<br>
favored : 91.05 %<br>
rotamer outliers : 14.11 %<br>
cbeta deviations : 3<br>
<br>
3) Then I perturbed the model and refined it with phenix.refine (restrained coordinates and B-factors, water update, weights optimization, local real-space refinement). Here is the statistics for refined model:<br>
<br>
Rwork=0.2380 Rfree=0.2709<br>
all-atom clashscore : 10.61<br>
ramachandran plot:<br>
outliers : 0.80 %<br>
allowed : 5.20 %<br>
favored : 94.00 %<br>
rotamer outliers : 2.38 %<br>
cbeta deviations : 0<br>
<br>
Just to make it clear: I'm *not* saying we shouldn't account for ptNCS in refinement; in fact, we really should especially given that Randy Read et al worked out all the methods for this!<br>
<br>
I will re-visit this once we implement ptNCS in phenix.refine.<br>
<br>
All the best,<br>
Pavel<br>
<br>
<br>
<div class="moz-cite-prefix">On 4/3/15 9:01 AM, Esko Oksanen wrote:<br>
</div>
<blockquote cite="mid:21782C8D-0497-4913-94B4-81545C8AFCFE@esss.se" type="cite"> Hi Mark,
<div><br>
</div>
<div>I believe at least part of the problem arises already in the scaling stage, where the programs assume a unimodal distribution which is not the case in the presence of pseudo-translations. We encountered a similar issue with refinement and pseudo-translation,
where I simply scaled the systematically weak data separately from the strong and did rigid body refinement against the weak data and restrained against the strong. The details can be found in <a moz-do-not-send="true" href="http://scripts.iucr.org/cgi-bin/paper?ea5052">http://scripts.iucr.org/cgi-bin/paper?ea5052</a>.</div>
<div><br>
</div>
<div> Best,</div>
<div> Esko<br>
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<div>On 03 Apr 2015, at 15:59, Mark A Saper <<a moz-do-not-send="true" href="mailto:saper@umich.edu">saper@umich.edu</a>> wrote:</div>
<br class="Apple-interchange-newline">
<blockquote type="cite">I know that Phaser takes account of NCS translation in the likelihood statistics ( Read, Adams, McCoy (2013) Intensity statistics in the presence of translational non crystallographic symmetry�). Has this also been incorporated into
phenix.refine? I have a structure with pseudo NCS translations because of NCS rotational symmetry. One suggestion that I found in the archives, was to explicitly LS target refinement rather than ML. Any comments?<br>
<br>
Mark<br>
_________________________________<br>
Mark A. Saper, Ph.D.<span class="Apple-tab-span" style="white-space:pre"> </span>
<span class="Apple-tab-span" style="white-space:pre"></span><span class="Apple-tab-span" style="white-space:pre"></span><span class="Apple-tab-span" style="white-space:pre"></span><br>
Associate Professor of Biological Chemistry, University of Michigan<br>
Ann Arbor MI 48109-1055 U.S.A.<br>
<a moz-do-not-send="true" href="mailto:saper@umich.edu">saper@umich.edu</a> phone (734) 764-3353 fax (734) 764-3323<br>
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