Models like ChatGPT and DALL-E2 generate text and images in response to a text prompt. Despite different data and goals, how can generative models be useful for protein engineering?
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
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$209.00 per year
only $17.42 per issue
Buy this article
- Purchase on Springer Link
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
References
Madani, A. et al. Nat. Biotechnol. 41, 1099–1106 (2023).
Watson, J. L. et al. Nature 620, 1089–1100 (2023).
Wang, J. et al. Science 377, 387–394 (2022).
Krishna, R. et al. Preprint at bioRxiv https://doi.org/10.1101/2023.10.09.561603 (2023).
Ingraham, J. et al. Nature 623, 1070–1078 (2023).
Eguchi, R. R., Choe, C. A. & Huang, P. S. PLOS Comput. Biol. 18, e1010271 (2022).
Ingraham, J., Garg, V., Barzilay, R. & Jaakkola, T. In Advances in Neural Information Processing Systems Vol. 32 (2019).
Dauparas, J. et al. Science 378, 49–56 (2022).
Hsu, C. et al. In Intl Conf. Machine Learning 8946–8970 (PMLR, 2022).
Anand, N. & Achim, T. Preprint at arXiv https://doi.org/10.48550/arXiv.2205.15019 (2022).
Acknowledgements
We thank A. Busia, H. Jiang, M. Lukarska, H. Nisonoff, Y. Song and J. Xiong for discussions and feedback.
Author information
Authors and Affiliations
Corresponding authors
Ethics declarations
Competing interests
J.L. consults for Fable Tx and Inscripta. C.H. is a cofounder of Escalante Bio. The remaining authors declare no competing interests.
Peer review
Peer review information
Nature Biotechnology thanks the anonymous reviewers for their contribution to the peer review of this work.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Hsu, C., Fannjiang, C. & Listgarten, J. Generative models for protein structures and sequences. Nat Biotechnol 42, 196–199 (2024). https://doi.org/10.1038/s41587-023-02115-w
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41587-023-02115-w
This article is cited by
-
Spotlight on protein structure design
Nature Biotechnology (2024)
