dbOGAP - an integrated bioinformatics resource for protein O-GlcNAcylation

Area of Science:

• Biochemistry
• Bioinformatics
• Proteomics

Background:

• Protein O-GlcNAcylation is a crucial post-translational modification analogous to phosphorylation, regulating diverse biological processes.
• Limited data and scarce database annotations hinder comprehensive research on O-GlcNAcylation.
• A dedicated bioinformatics resource and prediction tool for O-GlcNAcylation are urgently needed.

Purpose of the Study:

• To develop dbOGAP, a comprehensive database of O-GlcNAcylated proteins and sites.
• To create OGlcNAcScan, a predictive tool for identifying O-GlcNAcylation sites.
• To facilitate systematic access to O-GlcNAcylation data and enhance proteomic identification.

Main Methods:

• dbOGAP was curated from literature since 1984, containing ~800 proteins with experimental O-GlcNAcylation data, including ~400 identified sites.
• OGlcNAcScan was developed using a Support Vector Machine model trained on known O-GlcNAcylation sites from dbOGAP.
• A website was created for database searching, browsing, downloading, and accessing the OGlcNAcScan prediction tool.

Main Results:

• dbOGAP includes ~800 proteins with experimental O-GlcNAcylation data, ~61% human, and ~400 identified sites across 172 proteins.
• O-GlcNAcylated proteins are primarily nucleocytoplasmic, involved in transcriptional regulation, transport, and cell growth.
• OGlcNAcScan achieved an AUC of 74.3% in five-fold cross-validation for O-GlcNAcylation site prediction.

Conclusions:

• dbOGAP is the first public resource for systematic access to O-GlcNAcylated proteins, functional information, and bibliography.
• The integrated OGlcNAcScan tool provides a valuable method for predicting O-GlcNAcylation sites.
• This resource will significantly facilitate research and proteomic identification of O-GlcNAcylation.