Hi,<br> I am also a bit confused about your suspicion. If your Rwork/Rfree 22.7/27.9 for a 2.7 angstrom data, you have probably reached the so called endpoint of your refinement, unless Molprobity shows serious deviation.<br>
What is the basis of your skepticism? Were you expecting this structure to be different from the bacterial model to fit your hypothesis? I would be a bit careful in such situations! <br><br><div class="gmail_quote">On Tue, Nov 22, 2011 at 10:01 PM, Pavel Afonine <span dir="ltr"><<a href="mailto:pafonine@lbl.gov">pafonine@lbl.gov</a>></span> wrote:<br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex;"><u></u>
<div bgcolor="#ffffff" text="#000000">
Hi Rajesh,<br>
<br>
model bias, in a nutshell, is when you see something in the map that
is conveyed by the model (that may not be correct) and not by the
data.<br>
<br>
I am not sure how one can get an idea about model bias looking at
triplet of numbers: Rwork, Rfree and Molprobity percentile. By the
way, your Rwork/Rfree look pretty good (given the 2.7A resolution).<br>
<br>
Anyway, if everything else: bunch of model and data statistics,
local and global model-to-data quality fit all look well (*), and
you are still suspecting something isn't right, then you can invest
from a few days to a week or so into computing an "Iterative Build
OMIT map" as described here:<br>
<br>
Iterative-build OMIT maps: map improvement by iterative model
building and refinement without model bias. T. C. Terwilliger, R. W.
Grosse-Kunstleve, P. V. Afonine, N. W. Moriarty, P. D. Adams, R. J.
Read, P. H. Zwart and L.-W. Hung Acta Cryst. D64, 515-524 (2008)<br>
<br>
This map is supposed to be bias free.<br>
<br>
Pavel<br>
<br>
(*) For more details see here:<br>
<a href="http://www.phenix-online.org/presentations/latest/pavel_validation.pdf" target="_blank">http://www.phenix-online.org/presentations/latest/pavel_validation.pdf</a><div class="im"><br>
<br>
<br>
<blockquote type="cite">
<div dir="ltr"><font face="Tahoma" size="2"></font>
<div style="font-family:Tahoma;font-size:10pt">I have a
structure 2.74 A structure with R/freeR 22.7/27.9%. But the
molprobity score is 50th percentile.</div>
<div><font face="Tahoma" size="2">If I
fix the outliers they wouldn't go away and molprobity score
remains same or get worst. </font></div>
<div><font face="Tahoma" size="2">This
structure was solved by molecular replacement using a
bacterial protein with 38% identity.</font></div>
<div><font face="Tahoma" size="2">I am
wondering if there is an model bias? I have not identified
particular region in model for bias.</font></div>
<div><font face="Tahoma" size="2"><br>
</font></div>
<div><font face="Tahoma" size="2">My
questions are: Am I right in thinking if there is model bias
based on above info?</font></div>
<div><font face="Tahoma" size="2">I
added my .pdb and .mtz and do SA-composit omit map. This is
running from morning and I have feeling that I will get
results after thanksgiving. Is this the correct way of doing
a omit map for the purpose I mentioned? </font></div>
<div><font face="Tahoma" size="2">I saw
lot of discussions on omit map but couldn't grasp everything
and I am sure same questions might have been asked before.</font></div>
<div><font face="Tahoma" size="2">I
have couple of classical papers next to me but I need help.
</font><span style="font-family:Tahoma;font-size:10pt">I would appreciate if you could
help me out either suggesting me how and what to do or
pointing to previous thread over the this BB.</span><br>
</div>
</div>
</blockquote>
<br>
<br>
</div></div>
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