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Joseph L. Watson, David Juergens, Nathaniel R. Bennett, Brian L. Trippe, Jason Yim, Helen E. Eisenach, Woody Ahern, Andrew J. Borst, Robert J. Ragotte, Lukas F. Milles and 18 more
There has been considerable recent progress in designing new proteins using deep-learning methods 1–9 . Despite this progress, a general deep-learning framework for protein design that enables solution of a wide range of design challenges, including de novo binder design and design of higher-order symmetric architectures, has yet to be described. Diffusion models 10,11 have had considerable success in image and language generative modelling but limited success when applied to protein modelling, probably due to the complexity of protein backbone geometry and sequence–structure relationships. Here we show that by fine-tuning the RoseTTAFold structure prediction network on protein structure denoising tasks, we obtain a generative model of protein backbones that achieves outstanding performance on unconditional and topology-constrained protein monomer design, protein binder design, symmetric oligomer design, enzyme active site scaffolding and symmetric motif scaffolding for therapeutic and metal-binding protein design. We demonstrate the power and generality of the method, called RoseTTAFold diffusion (RFdiffusion), by experimentally characterizing the structures and functions of hundreds of designed symmetric assemblies, metal-binding proteins and protein binders. The accuracy of RFdiffusion is confirmed by the cryogenic electron microscopy structure of a designed binder in complex with influenza haemagglutinin that is nearly identical to the design model. In a manner analogous to networks that produce images from user-specified inputs, RFdiffusion enables the design of diverse functional proteins from simple molecular specifications.
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Watson, J. L., Juergens, D., Bennett, N. R., Trippe, B. L., Yim, J., Eisenach, H. E., Ahern, W., Borst, A. J., Ragotte, R. J., Milles, L. F., Wicky, B. I. M., Hanikel, N., Pellock, S. J., Courbet, A., Sheffler, W., Wang, J., Venkatesh, P., Sappington, I., Torres, S. V., … Baker, D. A. (2023). De novo design of protein structure and function with RFdiffusion. Nature, 620(7976), 1089–1100. https://doi.org/10.1038/s41586-023-06415-8
Watson, Joseph L., et al. "De novo design of protein structure and function with RFdiffusion." Nature, vol. 620, no. 7976, 2023, pp. 1089–1100, https://doi.org/10.1038/s41586-023-06415-8.
Watson, Joseph L., David Juergens, Nathaniel R. Bennett, Brian L. Trippe, Jason Yim, Helen E. Eisenach, Woody Ahern, et al. "De novo design of protein structure and function with RFdiffusion." Nature 620, no. 7976 (2023): 1089–1100. https://doi.org/10.1038/s41586-023-06415-8.
Watson J. L., Juergens D., Bennett N. R. [и др.] De novo design of protein structure and function with RFdiffusion // Nature. — 2023. — Vol. 620, № 7976. — P. 1089–1100. — URL: https://doi.org/10.1038/s41586-023-06415-8
@article{watson2023novo,
title = {{De novo design of protein structure and function with RFdiffusion}},
author = {Joseph L. Watson and David Juergens and Nathaniel R. Bennett and Brian L. Trippe and Jason Yim and Helen E. Eisenach and Woody Ahern and Andrew J. Borst and Robert J. Ragotte and Lukas F. Milles and Basile I. M. Wicky and Nikita Hanikel and Samuel J. Pellock and Alexis Courbet and William Sheffler and Jue Wang and Preetham Venkatesh and Isaac Sappington and Susana Vázquez Torres and Anna Lauko and Valentin De Bortoli and Émile Mathieu and Sergey Ovchinnikov and Regina Barzilay and Tommi Jaakkola and Frank DiMaio and Minkyung Baek and David A. Baker},
journal = {Nature},
year = {2023},
volume = {620},
number = {7976},
pages = {1089--1100},
doi = {10.1038/s41586-023-06415-8},
url = {https://doi.org/10.1038/s41586-023-06415-8}
}TY - JOUR AU - Watson, Joseph L. AU - Juergens, David AU - Bennett, Nathaniel R. AU - Trippe, Brian L. AU - Yim, Jason AU - Eisenach, Helen E. AU - Ahern, Woody AU - Borst, Andrew J. AU - Ragotte, Robert J. AU - Milles, Lukas F. AU - Wicky, Basile I. M. AU - Hanikel, Nikita AU - Pellock, Samuel J. AU - Courbet, Alexis AU - Sheffler, William AU - Wang, Jue AU - Venkatesh, Preetham AU - Sappington, Isaac AU - Torres, Susana Vázquez AU - Lauko, Anna AU - Bortoli, Valentin De AU - Mathieu, Émile AU - Ovchinnikov, Sergey AU - Barzilay, Regina AU - Jaakkola, Tommi AU - DiMaio, Frank AU - Baek, Minkyung AU - Baker, David A. TI - De novo design of protein structure and function with RFdiffusion JO - Nature VL - 620 IS - 7976 SP - 1089 EP - 1100 PY - 2023 DA - 2023/07/11 DO - 10.1038/s41586-023-06415-8 UR - https://doi.org/10.1038/s41586-023-06415-8 ER -
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