SKPDB: A structural database of shikimate pathway enzymes

Carregando...
Imagem de Miniatura

Data

2010-01-07

Autores

Arcuri, Helen A. [UNESP]
Zafalon, Geraldo F.D. [UNESP]
Marucci, Evandro A. [UNESP]
Bonalumi, Carlos E. [UNESP]
da Silveira, Nelson J.F.
Machado, José M. [UNESP]
de Azevedo Jr, Walter F.
Palma, Mario Sergio [UNESP]

Título da Revista

ISSN da Revista

Título de Volume

Editor

Resumo

Background: The functional and structural characterisation of enzymes that belong to microbial metabolic pathways is very important for structure-based drug design. The main interest in studying shikimate pathway enzymes involves the fact that they are essential for bacteria but do not occur in humans, making them selective targets for design of drugs that do not directly impact humans.Description: The ShiKimate Pathway DataBase (SKPDB) is a relational database applied to the study of shikimate pathway enzymes in microorganisms and plants. The current database is updated regularly with the addition of new data; there are currently 8902 enzymes of the shikimate pathway from different sources. The database contains extensive information on each enzyme, including detailed descriptions about sequence, references, and structural and functional studies. All files (primary sequence, atomic coordinates and quality scores) are available for downloading. The modeled structures can be viewed using the Jmol program.Conclusions: The SKPDB provides a large number of structural models to be used in docking simulations, virtual screening initiatives and drug design. It is freely accessible at http://lsbzix.rc.unesp.br/skpdb/. © 2010 Arcuri et al; licensee BioMed Central Ltd.

Descrição

Palavras-chave

Bacteria (microorganisms), enzyme, shikimic acid, amino acid sequence, biology, chemistry, computer program, metabolism, protein conformation, protein database, sequence analysis, Amino Acid Sequence, Computational Biology, Databases, Protein, Enzymes, Protein Conformation, Sequence Analysis, Protein, Shikimic Acid, Software

Como citar

BMC Bioinformatics, v. 11.