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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:CCP4BB@JISCMAIL.AC.UK] On Behalf Of Dale Tronrud Sent: > Friday, June 27, 2014 4:27 PM To: CCP4BB@JISCMAIL.AC.UK 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 > -----BEGIN PGP SIGNATURE----- Version: GnuPG v2.0.22 (MingW32) Comment: Using GnuPG with Thunderbird - http://www.enigmail.net/ iEYEARECAAYFAlOxCSgACgkQU5C0gGfAG10LpwCeORx6GGE3mA4HojnlJiIgx9em IQAAn2Hm+FqCTFFx9ui8XM/Q+Kex8smv =0bm1 -----END PGP SIGNATURE-----
