AD
数据与复现
Adaptyv
Adaptyv is a cloud laboratory platform that provides automated protein testing and validation services. Submit protein s…
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数据与复现
TO
tooluniverse-antibody-engineering
维护者 FreedomIntelligence · 最近更新 2026年4月1日
Comprehensive antibody engineering and optimization for therapeutic development. Covers humanization, affinity maturation, developability assessment, and immunogenicity prediction. Use when asked to optimize antibodies, humanize sequences, or engineer therapeutic antibodies from lead to clinical candidate.
原始来源
FreedomIntelligence/OpenClaw-Medical-Skills
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/tooluniverse-antibody-engineering
- 维护者
- FreedomIntelligence
- 许可
- MIT
- 最近更新
- 2026年4月1日
技能摘要
来自 SKILL.md 的关键信息
核心说明
- AI-guided antibody optimization pipeline ，面向 preclinical lead to clinical candidate. Covers sequence humanization，structure modeling，affinity optimization，developability assessment，immunogenicity prediction，、 manufacturing feasibility。
- KEY PRINCIPLES：1. Report-first approach - Create optimization report before analysis 2. Evidence-graded humanization - Score based on germline alignment 、 框架 retention 3. Developability-focused - Assess aggregation，stability，PTMs，immunogenicity 4. Structure-guided - Use AlphaFold/PDB structures ，用于 CDR analysis 5. Clinical precedent - Reference approved antibodies ，用于 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。
原始文档
SKILL.md 摘录
When to Use
Apply when user asks:
- "Humanize this mouse antibody sequence"
- "Optimize antibody affinity for [target]"
- "Assess developability of this antibody"
- "Predict immunogenicity risk for [sequence]"
- "Engineer bispecific antibody against [targets]"
- "Reduce aggregation in antibody formulation"
- "Design pH-dependent binding antibody"
- "Analyze CDR sequences and suggest mutations"
1. Report-First Approach (MANDATORY)
-
Create the report file FIRST:
- File name:
antibody_optimization_report.md - Initialize with section headers
- Add placeholder:
[Analyzing...]
- File name:
-
Progressively update as analysis completes
-
Output separate files:
optimized_sequences.fasta- All optimized variantshumanization_comparison.csv- Before/after comparisondevelopability_assessment.csv- Detailed scores
2. Documentation Standards (MANDATORY)
Every optimization MUST include:
适用场景
- 适合在asked to optimize antibodies，humanize sequences，或 engineer therapeutic antibodies ，面向 lead to clinical candidate时使用。
不适用场景
- Do not rely on this catalog entry alone ，用于 installation 或 maintenance details。
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