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One more item I forgot to mention: if necessary you may want to do
weight optimization.<br>
<br>
Pavel<br>
<br>
<div class="moz-cite-prefix">On 12/19/14 8:38 AM, Pavel Afonine
wrote:<br>
</div>
<blockquote cite="mid:54945471.8060105@lbl.gov" type="cite">
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Hi Derek,<br>
<br>
choosing 5% for free set is not a dogma. I always use 10% and
that's what CNS was doing for years. In your case this will make
200. Not a whole lot but better than 100.<br>
<br>
You can generate several (say 10-50) different test sets and
independently refine the model against each of them (from the very
beginning). Then make a note of differences (in model, R-factors).
Those differences will be uncertainties likely due to different
test sets used.<br>
<br>
I realize it may be tedious to do 10-50 refinements per each model
parametrization and refinement strategy that you want to test. In
this case I would simply reduce choices down to most reasonable
given the resolution and model quality:<br>
<br>
- use individual B-factor refinement. With type of restraints we
have it is ok to do in most cases. Switch to group B refinement
only if you have strong reasons to believe that individual B
refinement isn't good for your case.<br>
- Use torsion NCS;<br>
- Use Ramachandran plot restraints only to keep (preserve) good
conformations during refinement, not to fix bad ones (outliers).
That is: in case of outlier, for it manually first then refine
with Ramachandran restraints so that it does not become outlier
again.<br>
- If you have a higher resolution good model, you can use it as a
reference model, if needed.<br>
<br>
In future we will investigate using ideas recently published in
Acta D that suggest ways to overcome the problem of too small test
sets.<br>
<br>
Pavel<br>
<br>
<br>
<div class="moz-cite-prefix">On 12/19/14 3:18 AM, Derek Logan
wrote:<br>
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<blockquote
cite="mid:6BCD8761-034B-459A-A670-86AB72773171@biochemistry.lu.se"
type="cite">
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Hi everyone,
<div class=""><br class="">
</div>
<div class="">Right now we have one of those very difficult
Rfree situations where it's impossible to generate a single
meaningful Rfree set. Since we're in a bit of a hurry with
this structure it would be good if someone could point me in
the right direction. We have crystals with 1542 non-H atoms in
the asymmetric unit that diffract to only 3.6 � in P65, which
gives us a whopping 2300 reflections in total. 5% of this is
only about 100 reflections. Luckily the protein is only a
single point mutation of a wild type that has been solved to
much better resolution, so we know what it should look like
and I simply want to investigate the effect of different
levels of conservatism in the refinement, e.g. NCS in xyz and
B, group B-factors, reference model, Ramachandran restraints
etc. However since the quality criterion for this is Rfree I'm
not able to do this.</div>
<div class=""><br class="">
</div>
<div class="">I believe the correct approach is k-fold
statistical cross-validation, but can someone remind me of the
correct way to do this? I've done a bit of Googling without
finding anything very helpful.</div>
<div class=""><br class="">
</div>
<div class="">Thanks</div>
<div class="">Derek</div>
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<div class=""><font class="Apple-style-span">________________________________________________________________________<br
class="">
Derek Logan � � � � � � � � � � � � � � � �
� � � � tel: +46 46 222 1443<br class="">
Associate Professor � � � � � � � � � � � �
� � � ��</font>mob: +46 76 8585 707<font
class="Apple-style-span"><br class="">
Dept. of Biochemistry and Structural�Biology
� � � � � � �</font><a
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href="http://www.cmps.lu.se" class="">www.cmps.lu.se</a><font
class="Apple-style-span"><br class="">
Centre for Molecular Protein Science � � � �
� �<a moz-do-not-send="true"
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href="http://www.maxlab.lu.se/crystal">www.maxlab.lu.se/crystal</a></font><font
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Lund University, Box 124, 221 00�Lund,
Sweden � � � � � <a moz-do-not-send="true"
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