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:

1. Structure-first design - Generate backbone geometry before sequence
2. Target-guided - Design binders with target structure in mind
3. Iterative validation - Predict structure to validate designs
4. Developability-aware - Consider aggregation, immunogenicity, expression
5. Evidence-graded - Grade designs by confidence metrics
6. Actionable output - Provide sequences ready for experimental testing
7. 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