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  • Open Access

Editorial: Machine Learning for Structural Biology

Gabriele Corso, Gina El Nesr, and Hannah K. Wayment-Steele

  • Guest Editors of the Collection [in alphabetic order]

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PRX Life 2, 040001 – Published 21 November, 2024

DOI: https://doi.org/10.1103/PRXLife.2.040001

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References (18)

  1. J. Jumper et al., Highly accurate protein structure prediction with AlphaFold, Nature (London) 596, 583 (2021).
  2. J. Watson et al., De novo design of protein structure and function with RFdiffusion, Nature (London) 620, 1089 (2023).
  3. J. Ingraham et al., Illuminating protein space with a programmable generative model, Nature (London) 623, 1070 (2023).
  4. A. E. Chu et al., An all-atom protein generative model, Proc. Natl. Acad. Sci. (USA) 121, e2311500121 (2024).
  5. D. Alamo et al., Sampling alternative conformational states of transporters and receptors with AlphaFold2, eLife 11, e75751 (2022).
  6. H. Wayment-Steele et al., Predicting multiple conformations via sequence clustering and AlphaFold2, Nature (London) 625, 832 (2024).
  7. S. Zheng et al., Predicting equilibrium distributions for molecular systems with deep learning, Nat. Mach. Intell. 6, 558 (2024).
  8. R. J. L. Townshend et al., Geometric deep learning of RNA structure, Science 373, 1047 (2021).
  9. I. Igashov et al., Equivariant 3D-conditional diffusion model for molecular linker design, Nat. Mach. Intell. 6, 417 (2024).
  10. P. Gainza et al., De novo design of protein interactions with learned surface fingerprints, Nature (London) 617, 176 (2023).
  11. N. F. Polizzi and W. F. DeGrado, A defined structural unit enables de novo design of small-molecule–binding proteins, Science 369, 1227 (2020).
  12. A. Punjani and D. Fleet, 3DFlex: determining structure and motion of flexible proteins from cryo-EM, Nat. Methods 20, 860 (2023).
  13. E. Zhong et al., CryoDRGN: reconstruction of heterogeneous cryo-EM structures using neural networks, Nat. Methods 18, 176 (2021).
  14. M. Bileschi et al., Using deep learning to annotate the protein universe, Nat. Biotechnol. 40, 932 (2022).
  15. PLINDER and PINDER, https://www.plinder.sh/, https://www.pinder.sh/.
  16. Molecular Dynamics Data Bank, https://mddbr.eu/.
  17. K. Tsuboyama et al., Mega-scale experimental analysis of protein folding stability in biology and design, Nature (London) 620, 434 (2023).
  18. C. J. Markin et al., Revealing enzyme functional architecture via high-throughput microfluidic enzyme kinetics, Science 373, eabf8761 (2021).

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PRX Life 2, 040001– Published 21 November, 2024
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    Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

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