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dbSNO 2.0:一个用于探索蛋白质S-亚硝基化的结构环境、功能及疾病关联和调控网络的资源库。

dbSNO 2.0: a resource for exploring structural environment, functional and disease association and regulatory network of protein S-nitrosylation.

作者信息

Chen Yi-Ju, Lu Cheng-Tsung, Su Min-Gang, Huang Kai-Yao, Ching Wei-Chieh, Yang Hsiao-Hsiang, Liao Yen-Chen, Chen Yu-Ju, Lee Tzong-Yi

机构信息

Institute of Chemistry, Academia Sinica, Taipei 115, Taiwan.

Department of Computer Science and Engineering, Yuan Ze University, Taoyuan 320, Taiwan.

出版信息

Nucleic Acids Res. 2015 Jan;43(Database issue):D503-11. doi: 10.1093/nar/gku1176. Epub 2014 Nov 15.

Abstract

Given the increasing number of proteins reported to be regulated by S-nitrosylation (SNO), it is considered to act, in a manner analogous to phosphorylation, as a pleiotropic regulator that elicits dual effects to regulate diverse pathophysiological processes by altering protein function, stability, and conformation change in various cancers and human disorders. Due to its importance in regulating protein functions and cell signaling, dbSNO (http://dbSNO.mbc.nctu.edu.tw) is extended as a resource for exploring structural environment of SNO substrate sites and regulatory networks of S-nitrosylated proteins. An increasing interest in the structural environment of PTM substrate sites motivated us to map all manually curated SNO peptides (4165 SNO sites within 2277 proteins) to PDB protein entries by sequence identity, which provides the information of spatial amino acid composition, solvent-accessible surface area, spatially neighboring amino acids, and side chain orientation for 298 substrate cysteine residues. Additionally, the annotations of protein molecular functions, biological processes, functional domains and human diseases are integrated to explore the functional and disease associations for S-nitrosoproteome. In this update, users are allowed to search a group of interested proteins/genes and the system reconstructs the SNO regulatory network based on the information of metabolic pathways and protein-protein interactions. Most importantly, an endogenous yet pathophysiological S-nitrosoproteomic dataset from colorectal cancer patients was adopted to demonstrate that dbSNO could discover potential SNO proteins involving in the regulation of NO signaling for cancer pathways.

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/efbe/4383970/c26f115aa12a/gku1176fig1.jpg

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