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Hi Christopher,<br>
<br>
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cite="mid:CAAhO6Ehyd02sKkSvv=CiTVvst8w5HUENf7m-1pp58dTjhAtHXA@mail.gmail.com">
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<div>[I forgot to copy my reply to the bulletin board, so here
it is, reproduced for the record.]</div>
<div><br>
</div>
<div>The official publication for CaBLAM is the 2017 Molprobity
paper in Protein Science, here: <a
class="gmail-m_502587855306421605epub-doi"
href="https://doi.org/10.1002/pro.3330" target="_blank"
moz-do-not-send="true">https://doi.org/10.1002/pro.3330</a>
Further technical documentation on CaBLAM can be found in
Phenix's Computational Crystallography Newsletter, here: <a
href="https://www.phenix-online.org/newsletter/CCN_2018_07.pdf#page=7"
target="_blank" moz-do-not-send="true">https://www.phenix-online.org/newsletter/CCN_2018_07.pdf#page=7</a>
I recommend the newsletter article as a fast read.<br>
</div>
<div><br>
</div>
<div>To identify outliers, CaBLAM looks at a structure's CA
trace, which is generally well-modeled. For each residue, it
compares the local peptide plane orientations of the model to
the observed distribution of peptide plane orientations for
high quality residues with matching CA trace geometry. The
CaBLAM score is a percentile score that rates how well the
model matches with the expected distribution. The lower the
score, the rarer the observed conformation is in our database
of quality structures. A conformation falling in the bottom
5% of observed behavior is potentially suspicious
("Disfavored") and a conformation falling in the bottom 1% is
considered an outlier.</div>
<div><br>
</div>
<div>This percentile-based scoring is fundamentally the same
scoring used in MolProbity's description of Ramachandran and
rotamer outliers, though of course CaBLAM puts its cutoffs in
different places.</div>
<div><br>
</div>
<div>As a matter of interpretation, loop/coil regions tend to be
highly varied. CaBLAM "Disfavored" conformations in loops can
largely be ignored. However, disfavored conformations in
regions expected to by highly regular (repeating secondary
structure) should be taken seriously. CaBLAM outliers should
be inspected wherever they occur.</div>
<div><br>
</div>
<div>The CA geometry score looks at just the CA trace, and takes
the CA virtual angle into account (defined by CAi-1, CAi,
CAi+1). Outliers in this space reflect some sort of severe
problem with CA geometry, often involving an over-extended or
over-compressed CA virtual angle.</div>
<div><br>
</div>
<div>The secondary structure scores are based on how well a
residue's local CA trace matches the expected CA trace of each
major secondary structure type, alpha, 3-10, and beta. You
can see the contours used for this assessment in Figure 3 of
the newsletter article. Each residue receives individual
secondary structure scores. Then regions of residues that all
pass a scoring threshold are assembled into probable secondary
structure elements. This is where the "try beta sheet"
recommendations come from. That recommendation indicates that
the residue in question <i>and its neighboring residues</i>
all have CA traces that look like beta sheet.<br>
</div>
<div><br>
</div>
<div>I wish I had a simple recommendation for you, but fixing
CaBLAM outliers systematically has proven to be a challenge.
Take a look at your structure and see if you believe that the
outlier residues really are intended to be part of beta
sheets. If so, beta sheets have distinctive hydrogen bonding
patterns that tend to be disrupted by the kind of problems
that CaBLAM identifies. Ideally, you will be able to use
Coot's tools to restore the proper hydrogen bonding. Then,
applying hydrogen bonding restraints during refinement may
help keep your work in place.</div>
<div><br>
</div>
<div>If you have large regions of outliers, it may instead be
more practical to strip out the existing model and replace it
with idealized beta sheet structure, then rerefine. Again,
hydrogen bonding restraints may be helpful.</div>
<div><br>
</div>
<div>As a general rule, CaBLAM outliers usually indicate a
problem with the orientations for one or more peptide planes.
Look for a way to reorient the peptide either to remove
clashes or establish hydrogen bonds. Make sure you build good
regular secondary structure, don't sweat about the loops too
much, and trust your judgement and experience to identify the
real and justified outliers.<br>
</div>
</div>
</blockquote>
<br>
this is a great summary, thanks! <br>
Personally, I have a lot of trouble interpreting CaBLAM output. I've
seen many CaBLAM outliers and disfavored that looked to me just fine
leaving me confused as to what I should do. Misplaced carbonyl
groups are among rare cases where a fix is obvious by rotating the
group to satisfy H bonding. So.. I'd say a set of concrete and clear
fixing instructions would be very helpful to have. And if these
instructions can be encoded in software -- that's even better!<br>
<br>
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<div>We of the Richardson Lab generally dislike torsion-based
Ramachandran restraints/secondary structure restraints. </div>
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</blockquote>
<br>
I can see your point. But the matter of fact is: to make
low-resolution refinement possible these restraints are absolutely
necessary to use. Showing unfolding helix in 5A resolution map as
result of refinement without these restraints is among my favorite
examples that I've been showing for years not at workshops.<br>
Key point here is that one should not use these restraints to fix
outliers (because of limited convergence radius of refinement) but
only to keep a good model good during refinement.<br>
And, surely, we count on validation to stay on the safe side!<br>
<br>
All the best,<br>
Pavel<br>
<br>
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