Individual skill
tooluniverse-antibody-engineering
Therapeutic antibody engineering and optimization, lead-to-clinical-candidate. Covers sequence humanization (germline alignment, framework retention), affinity maturation, developability (aggregation, stability, PTMs), structure modeling (AlphaFold/PDB CDR analysis), immunogenicity prediction, and manufacturing feasibility. Use for biologic-drug optimization, mAb design review, biosimilar engineering, and clinical-precedent comparison.
plugins/tooluniverse/skills/tooluniverse-antibody-engineering/SKILL.md
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- Last checked
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- Repository last updated
- Nov 8, 2026
- License
- Apache-2.0
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- agents Repository topic
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.env.templateasset · 499 bytesCHECKLISTS.mddoc · 3,811 bytesEXAMPLES.mddoc · 36,883 bytesMANUFACTURING.mddoc · 4,056 bytesQUICK_START.mddoc · 11,035 bytesREPORT_TEMPLATE.mddoc · 13,036 bytesSKILL.mdcore · 16,387 bytesSKILL.mdcore · 16,387 bytesWORKFLOW_DETAILS.mddoc · 17,367 bytesscripts/developability.pyruns · 6,039 bytes
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# Antibody Engineering & Optimization
AI-guided antibody optimization pipeline from preclinical lead to clinical candidate. Covers sequence humanization, structure modeling, affinity optimization, developability assessment, immunogenicity prediction, and manufacturing feasibility.
**KEY PRINCIPLES**:
1. **Report-first approach** - Create optimization report before analysis
2. **Evidence-graded humanization** - Score based on germline alignment and framework retention
3. **Developability-focused** - Assess aggregation, stability, PTMs, immunogenicity
4. **Structure-guided** - Use AlphaFold/PDB structures for CDR analysis
5. **Clinical precedent** - Reference approved antibodies for validation
6. **Quantitative scoring** - Developability score (0-100) combining multiple factors
7. **English-first queries** - Always use English terms in tool calls, even if user writes in another language. Respond in user's language
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