Title: dbSNO: a database of cysteine S-nitrosylation
Authors: Lee, Tzong-Yi
Chen, Yi-Ju
Lu, Cheng-Tsung
Ching, Wei-Chieh
Teng, Yu-Chuan
Huang, Hsien-Da
Chen, Yu-Ju
Department of Biological Science and Technology
Institude of Bioinformatics and Systems Biology
Issue Date: 1-Sep-2012
Abstract: SUMMARY: S-nitrosylation (SNO), a selective and reversible protein post-translational modification that involves the covalent attachment of nitric oxide (NO) to the sulfur atom of cysteine, critically regulates protein activity, localization and stability. Due to its importance in regulating protein functions and cell signaling, a mass spectrometry-based proteomics method rapidly evolved to increase the dataset of experimentally determined SNO sites. However, there is currently no database dedicated to the integration of all experimentally verified S-nitrosylation sites with their structural or functional information. Thus, the dbSNO database is created to integrate all available datasets and to provide their structural analysis. Up to April 15, 2012, the dbSNO has manually accumulated >3000 experimentally verified S-nitrosylated peptides from 219 research articles using a text mining approach. To solve the heterogeneity among the data collected from different sources, the sequence identity of these reported S-nitrosylated peptides are mapped to the UniProtKB protein entries. To delineate the structural correlation and consensus motif of these SNO sites, the dbSNO database also provides structural and functional analyses, including the motifs of substrate sites, solvent accessibility, protein secondary and tertiary structures, protein domains and gene ontology.
URI: http://dx.doi.org/10.1093/bioinformatics/bts436
ISSN: 1367-4803
DOI: 10.1093/bioinformatics/bts436
Volume: 28
Issue: 17
Begin Page: 2293
End Page: 2295
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