SGGly: a web server for whole-protein, structure-guided analysis of candidate N-linked glycosylation sites.

N-linked glycosylation is critical for protein function and stability, yet identifying glycosylated sites remains challenging because glycosylation depends on sequence motifs and structural context. Many available computational approaches focus on motif-centred sequence windows and provide limited support for whole-protein inspection of candidate sites. SGGly is a freely accessible web server for structure-guided analysis of candidate N-linked glycosylation sites across full-length proteins. The server uses ProtBERT transformer-based embeddings with sequon and structure-derived residue descriptors to generate residue-level candidate-site predictions and returns downloadable residue-level predictions together with interactive 3D visualisation. Using a dual evaluation framework, SGGly achieved a Matthews correlation coefficient of 0.888 and receiver operating characteristic area under the curve of 0.987 under a strict, publication-supported regime. On the independent N-GlyDE benchmark, SGGly demonstrated strong generalisability, achieving the strongest specificity (0.941), sensitivity (0.993), and accuracy (0.946) among compared methods. SGGly provides a practical web resource for whole-protein glycosylation candidate mapping, structural inspection, and prioritisation of sites for follow-up analysis, guiding experimental design and interpreting glycoproteomic observations. SGGly is available at https://biosig.lab.uq.edu.au/sggly/. This website is free and open to all users, and there is no login requirement.