Intuitive enzyme design with LLM agents

Summary

A collaborative system of large language model agents brings protein engineering closer to natural-language interaction, lowering the barrier between human intent and biomolecular design. This is a preview of subscription content, access via your institution Access options Access Nature and 54 other Nature Portfolio journals Get Nature+, our best-value online-access subscription 27,99 € / 30 days cancel any time Subscribe to this journal Receive 12 digital issues and online access to articles 111,21 € per year only 9,27 € per issue Rent or buy this article Prices vary by article type from$1.95 to$39.95 Prices may be subject to local taxes which are calculated during checkout References - Shao, Q. et al. Nat. Comput. Sci. https://doi.org/10.1038/s43588-026-01049-y (2026). - Wiesinger, J., Marlow, P. & Vuskovic, V. Agents. Kaggle https://www.kaggle.com/whitepaper-agents (2025). - Ma, Z. et al. J. Chem. Inf. Model. 65, 6599–6612 (2025). - Ferruz, N., Schmidt, S. & Höcker, B. Nat. Commun. 13, 4348 (2022). - Nijkamp, E., Ruffolo, J. A., Weinstein, E. N., Naik, N. & Madani, A. Cell Syst. 14, 968–978.E3 (2023). - Ghafarollahi, A. & Buehler, M. J. Digit. Discov. 3, 1389–1409 (2024). - Ponnapati, M. et al. ProteinCrow: a language model agent that can design proteins. In Generative AI for Biology Workshop, Int. Conf. Machine Learning https://icml.cc/virtual/2025/51218 (ICML, 2025). - Durumeric, A. E. P. et al. J. Chem. Inf. Model. 66, 5721–5735 (2026). - Dolorfino, M. et al. Assessing the generalizability of machine learning and physics-based methods with DNA-encoded libraries. Preprint at bioRxiv https://doi.org/10.64898/2026.04.18.719394 (2026). Ethics declarations Competing interests The author declares no competing interests. Rights and permissions About this article Cite this article Sztain, T. Intuitive enzyme design with LLM agents. Nat Comput Sci (2026). https://doi.org/10.1038/s43588-026-01052-3 - Published: - Version of record: - DOI: https://doi.org/10.1038/s43588-026-01052-3