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Protein Geometry Database: a Flexible Engine to Explore Backbone Conformations and Their Relationships to Covalent Geometry

Overview
Specialty Biochemistry
Date 2009 Nov 13
PMID 19906726
Citations 20
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Abstract

The backbone bond lengths, bond angles, and planarity of a protein are influenced by the backbone conformation (varphi,Psi), but no tool exists to explore these relationships, leaving this area as a reservoir of untapped information about protein structure and function. The Protein Geometry Database (PGD) enables biologists to easily and flexibly query information about the conformation alone, the backbone geometry alone, and the relationships between them. The capabilities the PGD provides are valuable for assessing the uniqueness of observed conformational or geometric features in protein structure as well as discovering novel features and principles of protein structure. The PGD server is available at http://pgd.science.oregonstate.edu/ and the data and code underlying it are freely available to use and extend.

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References
1.
Antonyuk S, Strange R, Sawers G, Eady R, Hasnain S . Atomic resolution structures of resting-state, substrate- and product-complexed Cu-nitrite reductase provide insight into catalytic mechanism. Proc Natl Acad Sci U S A. 2005; 102(34):12041-6. PMC: 1189323. DOI: 10.1073/pnas.0504207102. View

2.
Cock P, Antao T, Chang J, Chapman B, Cox C, Dalke A . Biopython: freely available Python tools for computational molecular biology and bioinformatics. Bioinformatics. 2009; 25(11):1422-3. PMC: 2682512. DOI: 10.1093/bioinformatics/btp163. View

3.
Davis I, Leaver-Fay A, Chen V, Block J, Kapral G, Wang X . MolProbity: all-atom contacts and structure validation for proteins and nucleic acids. Nucleic Acids Res. 2007; 35(Web Server issue):W375-83. PMC: 1933162. DOI: 10.1093/nar/gkm216. View

4.
Lovell S, Davis I, Arendall 3rd W, de Bakker P, Word J, Prisant M . Structure validation by Calpha geometry: phi,psi and Cbeta deviation. Proteins. 2003; 50(3):437-50. DOI: 10.1002/prot.10286. View

5.
Lawson C . An atomic view of the L-tryptophan binding site of trp repressor. Nat Struct Biol. 1996; 3(12):986-7. DOI: 10.1038/nsb1296-986. View