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Generative models for protein structures and sequences

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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?

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Fig. 1: Overview of generative models for protein engineering.

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Acknowledgements

We thank A. Busia, H. Jiang, M. Lukarska, H. Nisonoff, Y. Song and J. Xiong for discussions and feedback.

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Authors and Affiliations

  1. University of California, Berkeley, Berkeley, CA, USA

    Chloe Hsu, Clara Fannjiang & Jennifer Listgarten

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  1. Chloe Hsu
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  2. Clara Fannjiang
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  3. Jennifer Listgarten
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Correspondence to Chloe Hsu or Jennifer Listgarten.

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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.

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Nature Biotechnology thanks the anonymous reviewers for their contribution to the peer review of this work.

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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

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