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Hi Jing,<br>
<br>
so then it looks like the problem solved! Perhaps that's the
simplest way though may not be most efficient as phenix.molprobity
calculates a lot more that you don't use. More efficient would be to
write your own Python script to loop over files and get that number
directly in the script..<br>
<br>
Pavel<br>
<br>
<div class="moz-cite-prefix">On 5/18/20 16:26, Jing Liu wrote:<br>
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Hi Pavel, <br>
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Thank you. I am actually only interested in getting the
MolProbity score. So I ran the phenix.molprobity and it generate
a file with the summary table that the MolProbity score is the
last line of the file. I guess I will have to extract that line
from the output files for comparison. I am not sure whether
there is a simpler way to get the information.
<br>
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<br>
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Best. <br>
</div>
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<br>
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Jing<br>
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<div id="divRplyFwdMsg" dir="ltr"><font style="font-size:11pt"
face="Calibri, sans-serif" color="#000000"><b>From:</b> Pavel
Afonine <a class="moz-txt-link-rfc2396E" href="mailto:pafonine@lbl.gov"><pafonine@lbl.gov></a><br>
<b>Sent:</b> Friday, May 15, 2020 12:08 PM<br>
<b>To:</b> Jing Liu <a class="moz-txt-link-rfc2396E" href="mailto:jliu321@stanford.edu"><jliu321@stanford.edu></a>;
<a class="moz-txt-link-abbreviated" href="mailto:phenixbb@phenix-online.org">phenixbb@phenix-online.org</a> <a class="moz-txt-link-rfc2396E" href="mailto:phenixbb@phenix-online.org"><phenixbb@phenix-online.org></a><br>
<b>Subject:</b> Re: [phenixbb] Is there a way to evaluate
batch pdb models with Malprobity in phenix?</font>
<div>�</div>
</div>
<div>Hi Jing,<br>
<br>
it depends what exactly� statistics you want to get. Running<br>
<br>
phenix.model_statistics model.pdb<br>
<br>
will likely get you most you want to see, a sample output looks
like:<br>
<br>
<tt>Deviations from Ideal Values.</tt><tt><br>
</tt><tt>� Bond����� :� 0.008�� 0.054��� 992</tt><tt><br>
</tt><tt>� Angle���� :� 1.071�� 6.317�� 1346</tt><tt><br>
</tt><tt>� Chirality :� 0.063�� 0.191��� 143</tt><tt><br>
</tt><tt>� Planarity :� 0.007�� 0.050��� 177</tt><tt><br>
</tt><tt>� Dihedral� : 27.365 179.733��� 369</tt><tt><br>
</tt><tt>� Min Nonbonded Distance : 2.116</tt><tt><br>
</tt><tt><br>
</tt><tt>Molprobity Statistics.</tt><tt><br>
</tt><tt>� All-atom Clashscore : 2.62</tt><tt><br>
</tt><tt>� Ramachandran Plot:</tt><tt><br>
</tt><tt>��� Outliers :� 0.81 %</tt><tt><br>
</tt><tt>��� Allowed� :� 6.50 %</tt><tt><br>
</tt><tt>��� Favored� : 92.68 %</tt><tt><br>
</tt><tt>� Rotamer Outliers :� 2.91 %</tt><tt><br>
</tt><tt>� Cbeta Deviations :� 0.00 %</tt><tt><br>
</tt><tt>� Peptide Plane:</tt><tt><br>
</tt><tt>��� Cis-proline���� : 0.00 %</tt><tt><br>
</tt><tt>��� Cis-general���� : 0.00 %</tt><tt><br>
</tt><tt>��� Twisted Proline : 0.00 %</tt><tt><br>
</tt><tt>��� Twisted General : 0.00 %</tt><tt><br>
</tt><tt><br>
</tt><tt>Rama-Z (Ramachandran plot Z-score):</tt><tt><br>
</tt><tt>Interpretation: bad |Rama-Z| > 3; suspicious 2 <
|Rama-Z| < 3; good |Rama-Z| < 2.</tt><tt><br>
</tt><tt>Scores for whole/helix/sheet/loop are scaled
independently;</tt><tt><br>
</tt><tt>therefore, the values are not related in a simple
manner.</tt><tt><br>
</tt><tt>� whole: -1.36 (0.65), residues: 123</tt><tt><br>
</tt><tt>� helix: -1.04 (0.99), residues: 10</tt><tt><br>
</tt><tt>� sheet:� 0.56 (1.03), residues: 21</tt><tt><br>
</tt><tt>� loop : -1.34 (0.57), residues: 92</tt><tt><br>
</tt><br>
In expect way you can put together a Python script and that
would loop over models, get an object-container from calling
model_statistics and programmatically parse that object to
extract information you need.<br>
<br>
Pavel<br>
<br>
<div class="x_moz-cite-prefix">On 5/15/20 11:54, Jing Liu wrote:<br>
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Hi, <br>
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<br>
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I had generate a batch of pdb models (40-100) in rosetta and
am wondering whether there is a way to evaluate these models
in batch with Molprobity. For example, can I use phenix
command line to do it and how? Or should I download the
Molprobity and do it on my local computer? Really appreciate
if anyone can share their experience.</div>
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<br>
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<div style="font-family:Calibri,Arial,Helvetica,sans-serif;
font-size:12pt; color:rgb(0,0,0)">
Jing Liu, PhD <br>
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<div style="font-family:Calibri,Arial,Helvetica,sans-serif;
font-size:12pt; color:rgb(0,0,0)">
Ted Jardetzky lab <br>
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<div style="font-family:Calibri,Arial,Helvetica,sans-serif;
font-size:12pt; color:rgb(0,0,0)">
Department of Structural Biology <br>
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font-size:12pt; color:rgb(0,0,0)">
Stanford University <br>
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