tooluniverse-protein-therapeutic-design

To design a protein binder de novo, supply a target structure to generate backbones with RFdiffusion, optimize sequences using ProteinMPNN, and validate the predicted structures with ESMFold or AlphaFold2.

Yes, you can use ProteinMPNN and RFdiffusion together by coupling RFdiffusion backbone generation with ProteinMPNN sequence design, followed by downstream structure validation and developability assessment.

Developability assessment in AI-driven protein design evaluates designed sequences for aggregation, expression, and immunogenicity risks, incorporating these considerations into the final ranked report of validated structures.

Designed protein structures are validated using ESMFold or AlphaFold2 to calculate prediction metrics like pLDDT and pTM, then ranked into a final report based on these scores and developability factors.

Yes, you need NVIDIA NIM tools to access and run RFdiffusion, ProteinMPNN, and ESMFold, as the protein therapeutic design pipeline requires these specific NVIDIA integrations for backbone generation and validation.

The final protein design report includes designed sequences, prediction metrics such as pLDDT and pTM scores from structure validation, and developability rankings for experimental testing.