# glycoengineering

A skill for working through N- and O-glycosylation sites in protein sequences: motif scanning, mutation planning and predictor prep.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 1800 installs · ★ 54652
- Author: K-Dense-AI
- License: not stated · policy=link-only · description only; the file stays with the author
- Source: https://github.com/K-Dense-AI/scientific-agent-skills/tree/HEAD/skills/glycoengineering/SKILL.md
- Updated: 2026-10-19
- HTML: https://affpapa.org/en/nevibecode/skills/glycoengineering

## What it does

The skill walks through glycosylation analysis for eukaryotic secretory-pathway proteins. It starts by recording the accession, isoform, exact sequence, expression host and signal peptide topology. Canonical N-X-[S/T] candidates are then scanned with X not proline, and overlapping hits are kept: in `NNST` a candidate begins at position 1 and another at position 2. S/T-rich stretches get a separate pass for mucin-type O-GalNAc, though density there is a descriptive feature only, not a probability of glycosylation.

A local helper ships as `scripts/glycoengineering_tools.py` and uses the Python standard library. It takes sequences of the 20 canonical amino acids, normalizes case and whitespace, and rejects FASTA headers, gaps and unknown residues. The functions `find_n_glycosylation_sequons`, `eliminate_glycosite`, `add_glycosite` and `find_st_rich_sites` report 1-based coordinates against the sequence you submitted. Put the `scripts/` directory on `PYTHONPATH`, or run Python from inside it.

Predictions go through the official web forms for NetNGlyc 1.0 and NetOGlyc 4.0. There is no stable submission API or job-polling endpoint here, so keep input, output and service version together. The local helpers need Python 3.10+. GlyTouCan lookup uses `requests` and network access. Structural glycan shielding calls for a separate GlycoSHIELD install with glycan libraries and GROMACS for SASA analysis; without those the step will not run.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add K-Dense-AI/scientific-agent-skills --skill glycoengineering -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/glycoengineering/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/glycoengineering/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add K-Dense-AI/scientific-agent-skills --skill glycoengineering -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/glycoengineering/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add K-Dense-AI/scientific-agent-skills --skill glycoengineering -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/glycoengineering/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install K-Dense-AI/scientific-agent-skills glycoengineering
```

2. **Manually: put the files in place**
- File: `.github/skills/glycoengineering/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add K-Dense-AI/scientific-agent-skills --skill glycoengineering -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/K-Dense-AI/scientific-agent-skills --path skills/glycoengineering
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/glycoengineering/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add K-Dense-AI/scientific-agent-skills --skill glycoengineering -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/K-Dense-AI/scientific-agent-skills/tree/HEAD/skills/glycoengineering/SKILL.md

## When to use it
- scan a protein sequence for canonical N-glycosylation sites
- knock out one glycosylation site with a point substitution
- introduce a new N-X-[S/T] site and list every residue changed
- flag S/T-rich regions before O-GalNAc triage
- compare antibody glycoforms by site occupancy

## Example prompts
- Scan this sequence for canonical N-glycosylation sites and list their positions
- Remove the site at position 1 with a Q substitution and check for overlapping motifs
- Find S/T-rich regions in this sequence and tell me what to check next

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From the same set: [k-dense-ai/scientific-agent-skills](https://affpapa.org/en/nevibecode/by/k-dense-ai/scientific-agent-skills.md) — 159 cards

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