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   The Protein Geometry Database looks at proteins as collections of
bond lengths, angles, and torsion angles.  It is not the place to go
when you want to know how a protein part is related in space to some
other (covalently) distant part.

   Andy tells me that Jacque Fetrow, who was at Wake Forest University,
has a database that might answer your query.  There is a paper at

J Mol Biol. 2003 Nov 28;334(3):387-401.

Structure-based active site profiles for genome analysis and functional
family subclassification.

   Neither one of us has used it.

Hope that helps,
Dale Tronrud

On 6/27/2014 1:49 PM, Keller, Jacob wrote:
> I have wanted for some time to search for catalytic-triad-like
> configurations by defining three Ca-Cb bonds from known catalytic
> triads, then searching the pdb for matches, but have not thought of
> a quick and/or easy way to do this--can your software do this sort
> of thing, or is there some other software which could be used for
> this?
> 
> JPK
> 
> -----Original Message----- From: CCP4 bulletin board
> [mailto:[log in to unmask]] On Behalf Of Dale Tronrud Sent:
> Friday, June 27, 2014 4:27 PM To: [log in to unmask] Subject:
> [ccp4bb] New Version of the Protein Geometry Database Now
> Available
> 
> Protein Geometry Database Server V 1.0 
> http://pgd.science.oregonstate.edu/ Developed by Andy Karplus'
> laboratory at Oregon State University
> 
> We are pleased to announce the availability of an enhanced version
> of the Protein Geometry Database (PGD) web service, originally
> announced in Berkholz et al (2010) Nucleic Acids Research 38,
> D320-5. This server allows you to explore the many backbone and
> side chain conformations that exist in the PDB as well as the
> protein geometry (lengths and angles) that occur in those
> conformations. This service is ideal for finding instances of
> particular conformations or peculiar bond lengths or angles.  It is
> also quite adept at identifying sets of fragments that can then be
> examined for systematic variation in "ideal" geometry. The expanded
> PGD now includes all conformational and covalent geometry
> information not just for the backbone but also for the sidechains.
> 
> There are three basic operations available: selecting a set of
> fragments via a delimited search, analyzing the geometry of those
> fragments, and dumping the results to your computer for more
> specialized analysis.
> 
> To control bias in statistical analyses due to the variable number
> of entries with the same or similar sequence, the database contains
> only the highest quality model in each sequence cluster as
> identified by the Pisces server from Roland Dunbrack's lab.  Two
> settings, 90% and 25% sequence identity, are available.  Currently,
> at the 90% sequence identity level there are 16,000 chains and at
> the 25% level this drops to about 11,000 chains.
> 
> You can filter a search based on the quality of the model as
> indicated by resolution and R values.  A search can also be
> filtered based on DSSP secondary structure, amino acid type, the
> phi/psi/omega angles and bond lengths, angles, and chi angles.  For
> example, you can find all cysteine residues in the center of
> three-residue peptide fragments (i.e. not at a peptide terminus),
> in beta sheet, with both peptide bonds trans, and CB-SG length
> greater than 1.85 A from models with resolution better than 1.5 A.
> By the way, in the "no more than 25% sequence identity" category
> there are 25 of them.
> 
> Once you have a set of results, you can create 2D plots showing the
> relationships of up to three features (i.e. bond lengths, bond
> angles, or conformational angles).  For instance, you can look at
> how a given feature varies with phi and psi using a phi(i)/psi(i)
> plot.  Or, you can just as easily look at the variation with
> psi(i)/phi(i+1), or even the relationships between any selected
> bond angles.  As one example, it is instructive to perform a
> default search and plot NCaCb vs NCaC colored based on CbCaC.  As
> this search is restricted to just the highest resolution models,
> you can see the justification for chiral volume restraints.
> 
> Finally, all of your results can be downloaded for your own
> analysis.
> 
> Development of the PGD continues.  If you have worked with the site
> and have any ideas and suggestions for how to improvement it,
> please drop us a line.
> 
> The publication describing the PGD is:
> 
> Berkholz, D.S., Krenesky, P.B., Davidson, J.R.,  & Karplus, P.A. 
> (2010) Protein Geometry Database: A flexible engine to explore
> backbone conformations and their relationships with covalent
> geometry. Nucleic Acids Res. 38, D320-5.
> 
> Also, some examples of published analyses enabled by earlier
> versions of the PGD are listed here:.
> 
> Berkholz, D.S., Shapovalov, M.V., Dunbrack, R.L.J. & Karplus, P.A. 
> (2009). Conformation dependence of backbone geometry in proteins. 
> Structure 17, 1316-1325.
> 
> Hollingsworth, S.A., Berkholz, D.S. & Karplus, P.A. (2009). On the
> occurrence of linear groups in proteins. Protein Science 18,
> 1321-1325
> 
> Hollingsworth, S.A. & Karplus, P. A. (2010). Review: A fresh look
> at the Ramachandran plot and the occurrence of standard structures
> in proteins. BioMolecular Concepts 1, 271-283.
> 
> Berkholz, D.S., Driggers, C.M., Shapovalov, M.V., Dunbrack, R.L.,
> Jr. & Karplus P.A. (2012) Nonplanar peptide bonds in proteins are
> common and conserved but not biased toward active sites. Proc Natl
> Acad Sci U S A.  109, 449-53.
> 
> Dale Tronrud & P. Andrew Karplus Department of Biochemistry and
> Biophysics Oregon State University

> 
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