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Welcome to SNOSite

SNOSite is an effective web-based tool for identifying S-NitrOsylation Site on cysteine.

  • Biological Importance of S-Nitrosylation

    S-nitrosylation is a reversible post-translational modification (PTM) by covalent modification on the thiol group of cysteine (Cys) residues by nitric oxide (NO). Emerging evidences suggest that S-nitrosylation plays an important role in NO-related and redox pathway, especially in immune, cardiovascular, neuronal, and plant systems. Moreover, different S-nitrosylation level and targets modulate the protein activity, localization, and stability and further regulate the pathophysiological events, such neurodegenerative diseases and cancers.

  • Investigation of S-Nitrosylation Sites

    Based on a total of 586 experimentally identified S-nitrosylation sites from SNAP/L-cysteine-stimulated mouse endothelial cells, this work presents an informatics investigation on S-nitrosylation sites including structural factors such as the flanking amino acids composition, the accessible surface area (ASA) and physicochemical properties, i.e. positive charge and side chain interaction parameter. Due to the difficulty to obtain the conserved motifs by conventional motif analysis, maximal dependence decomposition (MDD) has been applied to obtain statistically significant conserved motifs.

  • Predictive Performance of SNOSite

    Support vector machine (SVM) is applied to generate predictive model for each MDD-clustered motif. According to five-fold cross-validation, the MDD-clustered SVMs could achieve an accuracy of 0.902, and provides a promising performance in an independent test set.

  • Case Study
    Case Study 1 DDAH1_BOVIN, N(G),N(G)-dimethylarginine dimethylaminohydrolase 1
    Case Study 2 HBB_HUMAN, Hemoglobin subunit beta

Citing SNOSite

Lee TY, Chen YJ, Lu TC, Huang HD, Chen YJ. (2011) "SNOSite: exploiting maximal dependence decomposition to identify cysteine S-nitrosylation with substrate site specificity." PLoS One, Vol. 6(7), e21849. [PubMed]
Dept. of Computer Science & Engineering, Yuan Ze University, Chungli 320, Taiwan.
Contact Tzong-Yi Lee with questions or comments.
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