標題: | dbSNO: a database of cysteine S-nitrosylation |
作者: | Lee, Tzong-Yi Chen, Yi-Ju Lu, Cheng-Tsung Ching, Wei-Chieh Teng, Yu-Chuan Huang, Hsien-Da Chen, Yu-Ju 生物科技學系 生物資訊及系統生物研究所 Department of Biological Science and Technology Institude of Bioinformatics and Systems Biology |
公開日期: | 1-Sep-2012 |
摘要: | 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 http://hdl.handle.net/11536/16880 |
ISSN: | 1367-4803 |
DOI: | 10.1093/bioinformatics/bts436 |
期刊: | BIOINFORMATICS |
Volume: | 28 |
Issue: | 17 |
起始頁: | 2293 |
結束頁: | 2295 |
Appears in Collections: | Articles |
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