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About glycoengineering
glycoengineering
Analyzes and engineers protein glycosylation
glycoengineering is an agent skill for analysing and engineering protein glycosylation. It scans for canonical N-glycosylation sequons, which are the motifs where sugars attach to proteins, describes serine and threonine rich regions, checks curated glycan evidence, and helps with antibody glycoform comparison and structural glycan shielding. It also triages candidate mucin-type O-GalNAc sites. The skill insists that four kinds of result are kept separate: a sequence motif, a prediction, experimentally supported occupancy, and a glycan structure or composition. None of these alone establishes the others. The workflow focuses on N-glycosylation in the eukaryotic secretory pathway and on mucin-type O-GalNAc. Other O-linked modifications, such as O-GlcNAc, O-mannose and O-fucose, need appropriate evidence and predictors, and enrichment of serine and threonine residues does not show which type is present. Use it when you are looking at candidate glycosylation sites in a protein, comparing antibody glycoforms, or considering how glycans might shield a surface. It is part of the k-dense-ai scientific agent skills repository on GitHub, which has about 49,600 stars.
- Price
- Free
- Made by
- k-dense-ai
- Category
- AI Skills
- Website
- github.com/k-dense-ai/scientific-agent-skills/glycoengineering