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Protein structure predictions to atomic accuracy with AlphaFold

AlphaFold is a neural-network-based approach to predicting protein structures with high accuracy. We describe how it works in general terms and discuss some anticipated impacts on the field of structural biology.

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Fig. 1: AlphaFold as an amplifier of sparse experimental data.


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We thank K. Tunyasuvunakool for helping with the figure; R. Bates, M. Figurnov, T. Green and Z. Wu for their suggestions and comments; and C. Meyer for helping to prepare the manuscript.

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Correspondence to John Jumper or Demis Hassabis.

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The authors have filed patent applications in the name of DeepMind Technologies Limited relating to machine learning for protein structure prediction.

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Jumper, J., Hassabis, D. Protein structure predictions to atomic accuracy with AlphaFold. Nat Methods 19, 11–12 (2022).

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