Evidence record 5696 · automatically gathered

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

Record details

Published: 18 April 2026
Source: arXiv
Category: Research
Topics: Agents & autonomy · Biotech
Retrieved: 14 July 2026

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ethics.ai (18 April 2026), “ProtoCycle: Reflective Tool-Augmented Planning for Text-Guided Protein Design,” evidence record 5696, https://ethics.ai/record/5696 (originally published by arXiv).

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