dbSNO: a database of cysteine S-nitrosylation

Tzong-Yi Lee, Yi-Ju Chen, Tsung-Cheng Lu, Wei-Chieh Ching, Yu-Chuan Teng, Hsien-Da Huang, Yu-Ju Chen

Research output: Contribution to journalArticle

56 Scopus citations

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.
Original languageEnglish
Pages (from-to)2293-2295
Number of pages3
JournalBioinformatics
Volume28
Issue number17
DOIs
StatePublished - Sep 2012

Keywords

  • BIOINFORMATICS RESOURCE; NITRIC-OXIDE; IDENTIFICATION; SITE; PREDICTION; PROTEINS; STRATEGY; MOTIFS; SIGNAL

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  • Cite this

    Lee, T-Y., Chen, Y-J., Lu, T-C., Ching, W-C., Teng, Y-C., Huang, H-D., & Chen, Y-J. (2012). dbSNO: a database of cysteine S-nitrosylation. Bioinformatics, 28(17), 2293-2295. https://doi.org/10.1093/bioinformatics/bts436