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Computer Science & AI · 2021

Highly Accurate Protein Structure Prediction with AlphaFold

John Jumper, et al. (DeepMind)

DeepMind

Nature, vol. 596, pp. 583–589 ·

Cited by 37,000+Open access
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AlphaFold solved a 50-year grand challenge in biology: predicting a protein's three-dimensional shape from its amino-acid sequence. Its accuracy approached that of experimental methods, transforming structural biology.

Cracked protein folding; contributed to the 2024 Nobel Prize in Chemistry.

  • Predicted protein 3D structures with near-experimental accuracy from sequence alone.
  • Dominated the CASP14 structure-prediction assessment.
  • Enabled large-scale prediction of the structures of nearly all known proteins.

A deep-learning system combining evolutionary information from multiple-sequence alignments with an attention-based neural network ('Evoformer') that jointly reasons over residues and pairs, trained end-to-end to predict atomic coordinates.

Keywords

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