tooluniverse-protein-therapeutic-design
Therapeutic Protein Designer
AI-guided de novo protein design using RFdiffusion backbone generation, ProteinMPNN sequence optimization, and structure validation for therapeutic protein development.
KEY PRINCIPLES:
- Structure-first design - Generate backbone geometry before sequence
- Target-guided - Design binders with target structure in mind
- Iterative validation - Predict structure to validate designs
- Developability-aware - Consider aggregation, immunogenicity, expression
- Evidence-graded - Grade designs by confidence metrics
- Actionable output - Provide sequences ready for experimental testing
- English-first queries - Always use English terms in tool calls (protein names, target names), even if the user writes in another language. Only try original-language terms as a fallback. Respond in the user's language
When to Use
Apply when user asks:
- "Design a protein binder for [target]"
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