Researchers at the Institute for Protein Design have developed a new AI-driven molecular design tool that generates completely novel bioactive peptides. The ability to create such molecules by computation alone may accelerate drug development.
RFpeptides builds upon the success of RFdiffusion and introduces key innovations tailored for the specific challenges of macrocyclic peptide design. Pioneered at the IPD, both tools draw inspiration from popular AI image generators that use diffusion models to synthesize new images based on user prompts. With RFdiffusion, a diffusion model sculpts clouds of disconnected amino acids into plausible biochemical structures. To create RFpeptides, the team modified the open-source tool to ensure the first and last amino acids in a designed molecule could form a chemical bond.

“By expanding the structure modeling capabilities of RoseTTAFold2 and harnessing ProteinMPNN for sequence design, we’ve created a peptide design pipeline that’s both computationally efficient and incredibly accurate,” said associate professor of biochemistry Frank DiMaio.