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dbSNO: a database of cysteine S-nitrosylation

dc.citation.epage2295en_US
dc.citation.issue17en_US
dc.citation.spage2293en_US
dc.citation.volume28en_US
dc.citation.woscount21
dc.contributor.authorLee, Tzong-Yien_US
dc.contributor.authorChen, Yi-Juen_US
dc.contributor.authorLu, Cheng-Tsungen_US
dc.contributor.authorChing, Wei-Chiehen_US
dc.contributor.authorTeng, Yu-Chuanen_US
dc.contributor.authorHuang, Hsien-Daen_US
dc.contributor.authorChen, Yu-Juen_US
dc.contributor.department生物科技學系zh_TW
dc.contributor.department生物資訊及系統生物研究所zh_TW
dc.contributor.departmentDepartment of Biological Science and Technologyen_US
dc.contributor.departmentInstitude of Bioinformatics and Systems Biologyen_US
dc.date.accessioned2014-12-08T15:24:17Z
dc.date.available2014-12-08T15:24:17Z
dc.date.issued2012-09-01en_US
dc.description.abstractSUMMARY: 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.en_US
dc.identifier.doi10.1093/bioinformatics/bts436en_US
dc.identifier.issn1367-4803en_US
dc.identifier.journalBIOINFORMATICSen_US
dc.identifier.urihttp://dx.doi.org/10.1093/bioinformatics/bts436en_US
dc.identifier.urihttps://ir.lib.nycu.edu.tw/handle/11536/16880
dc.identifier.wosnumberWOS:000308019200019
dc.language.isoen_USen_US
dc.titledbSNO: a database of cysteine S-nitrosylationen_US
dc.typeArticleen_US

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