Small-molecule binding and sensing with a designed protein family

Lee, G. R.; Pellock, S. J.; Norn, C.; Tischer, D.; Dauparas, J.; Anishchenko, I.; Mercer, J. A. M.; Kang, A.; Bera, A.; Nguyen, H.; Goreshnik, I.; Vafeados, D.; Roullier, N.; Han, H. L.; Coventry, B.; Haddox, H. K.; Liu, D. R.; Yeh, A. H.-W.; Baker, D.

doi:10.1101/2023.11.01.565201

bioRxiv · 10.1101/2023.11.01.565201

Small-molecule binding and sensing with a designed protein family

Lee, G. R.·Pellock, S. J.·Norn, C.·Tischer, D.·Dauparas, J.·Anishchenko, I.·Mercer, J. A. M.·Kang, A.·Bera, A.·Nguyen, H.·Goreshnik, I.·Vafeados, D.·Roullier, N.·Han, H. L.·Coventry, B.·Haddox, H. K.·Liu, D. R.·Yeh, A. H.-W.·Baker, D.

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Abstract

Despite transformative advances in protein design with deep learning, the design of small-molecule-binding proteins and sensors for arbitrary ligands remains a grand challenge. Here we combine deep learning and physics-based methods to generate a family of proteins with diverse and designable pocket geometries, which we employ to computationally design binders for six chemically and structurally distinct small-molecule targets. Biophysical characterization of the designed binders revealed nanomolar to low micromolar binding affinities and atomic-level design accuracy. The bound ligands are exposed at one edge of the binding pocket, enabling the de novo design of chemically induced dimerization (CID) systems; we take advantage of this to create a biosensor with nanomolar sensitivity for cortisol. Our approach provides a general method to design proteins that bind and sense small molecules for a wide range of analytical, environmental, and biomedical applications.

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Lee, G. R., Pellock, S. J., Norn, C., Tischer, D., Dauparas, J., Anishchenko, I., Mercer, J. A. M., Kang, A., Bera, A., Nguyen, H., Goreshnik, I., Vafeados, D., Roullier, N., Han, H. L., Coventry, B., Haddox, H. K., Liu, D. R., Yeh, A. H.-W., Baker, D.. 2023-11-02. Small-molecule binding and sensing with a designed protein family. https://doi.org/10.1101/2023.11.01.565201

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