Integrates LLM agents with the industry-standard Rosetta software to automate physics-based protein design for non-canonical amino acids.
arXiv · March 18, 2026 · 2603.15952
The Takeaway
Bridging the gap between LLMs and specialized scientific software like Rosetta allows non-experts to execute complex heteropolymer design pipelines. It matches human expert performance in areas where standard ML models for protein design currently fail.
From the abstract
Large language models (LLMs) are capable of emulating reasoning and using tools, creating opportunities for autonomous agents that execute complex scientific tasks. Protein design provides a natural testbed: although machine learning (ML) methods achieve strong results, these are largely restricted to canonical amino acids and narrow objectives, leaving unfilled need for a generalist tool for broad design pipelines. We introduce Agent Rosetta, an LLM agent paired with a structured environment fo