2020

November

1 events

Editors' summary

AlphaFold2 reads the shape of a protein

On 30 November, DeepMind's AlphaFold2 reached near-experimental accuracy at CASP14, the protein structure prediction contest. The organisers said a fifty-year-old problem had been solved. Knowing the shape of a protein bears on drug design and on understanding disease, and the result was read as touching how biology itself gets done.

Apart from language models, it was the year deep learning showed itself as an instrument of science.

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Record1 events
  1. 30
    ResearchGoogle / John Jumper / Demis Hassabis

    AlphaFold2 is judged to have solved protein folding

    DeepMind's AlphaFold2 won the CASP14 protein structure prediction competition by a wide margin and was recognized by the organizers as a solution to the 50-year-old protein folding problem. It scored 92.4 GDT, with predictions averaging 1.6 angstroms of error — about the width of an atom — three times more accurate than the next best system and comparable to experimental methods. The system used an attention-based network that refined a structure graph using evolutionarily related sequences, multiple sequence alignment, and a representation of amino acid residue pairs. It sits outside the generative AI lineage, but was widely reported at the time as a case of AI actually solving a hard scientific problem. Hassabis and Jumper would receive the 2024 Nobel Prize in Chemistry for the work.