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k-dense-ai/drug-discovery-agent-skills

v1.3.0MIT

Agent Skills for small-molecule and protein therapeutics: target validation and human genetics, bioactivity and chemical space, generative design and retrosynthesis, docking, free energy and dynamics, ADMET and PK translation, protein, antibody, degrader and oligonucleotide design, and the clinical and regulatory record.

glycoengineering

Analyze and engineer protein glycosylation. Scan sequences for canonical N-glycosylation sequons (N-X-S/T with X not proline, including overlapping sites), predict O-GalNAc hotspots, read glycan notation, and reach the curated external tooling (NetNGlyc, NetOGlyc, GlycoShield, GlycoWorkbench, GlyTouCan, GlyConnect). Use this skill for therapeutic antibody glycoengineering and afucosylation for ADCC, Fc glycan control, glycan shielding in vaccine immunogen design, sequon removal or insertion, and half-life engineering through sialylation. Also trigger on N-glycosylation, sequon, NXS/NXT, O-glycosylation, glycoform heterogeneity, afucosylation, high-mannose, GlyTouCan, or WURCS.

Version
1.2
License
MIT
Compatibility
Requires Python 3.10+. The bundled sequon and notation analysis is standard library only. Optional extras — pandas and requests for the database lookups, glycoshield for ensemble modelling. The external predictors (NetNGlyc, NetOGlyc) are DTU web services requiring manual submission and, for some, an academic licence; there is no public REST API.
Read SKILL.md at the source

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Pre-approved tools experimental

Experimental field. Support varies between clients, so this list is what the author declared, not what your client will enforce.

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