ProtoCycle: Reflective Tool-Augmented Planning for Text-Guided Protein Design
Designing proteins that satisfy natural language functional requirements is a central goal in protein engineering. A straightforward baseline is to fine-tune generic instruction-tuned LLMs as direct text-to-sequence generators, but this is data- and compute-hungry. With limited supervision, LLMs can produce coherent plans in text yet fail to reliably realize them as sequences. This plan-execute gap motivates ProtoCycle, an agentic framework for protein design that uses LLMs primarily to drive a multi-round, feedback-driven decision cycle. ProtoCycle couples an LLM planner with a lightweight tool environment designed to emulate the iterative workflow of human protein engineering and uses L...
| Authors | Yutang Ge, Guojiang Zhao, Sihang Li et al. |
|---|---|
| Primary category | q-bio.QM |
| Published | 18 April 2026 |
| Last updated at source | 18 April 2026 |
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