AlphaFold

7 entries between December 2018 and October 2024, 2 turning points.

Turning points

  1. DeepMind and EMBL-EBI publish the AlphaFold protein database

    DeepMind and EMBL’s European Bioinformatics Institute opened the AlphaFold Protein Structure Database on 22 July 2021, with more than 350,000 predicted structures covering the roughly 20,000 proteins of the human proteome and 20 other organisms used in research.

  2. AlphaFold 2 nears laboratory accuracy at CASP14

    Organizers of the fourteenth Critical Assessment of protein Structure Prediction said on 30 November 2020 that DeepMind’s AlphaFold 2 had predicted about two-thirds of the competition’s target proteins to an accuracy comparable to laboratory methods.

Every entry

  1. Nobel chemistry prize honors AlphaFold and David Baker

    The Royal Swedish Academy of Sciences gave half of the 2024 Nobel Prize in Chemistry to Demis Hassabis and John Jumper of Google DeepMind for protein structure prediction with AlphaFold, and half to David Baker of the University of Washington for computational protein design.

  2. DeepMind and Isomorphic Labs unveil AlphaFold 3

    Google DeepMind and Isomorphic Labs announced AlphaFold 3 on 8 May 2024, extending the protein-structure predictor to complexes of proteins with DNA, RNA, small-molecule ligands, and ions. The Nature paper reported at least a 50% accuracy gain over prior methods.

  3. AlphaFold database expands to over 200 million structures

    DeepMind and EMBL’s European Bioinformatics Institute expanded the AlphaFold Protein Structure Database on 28 July 2022, from roughly 1 million predicted protein structures to more than 200 million, covering nearly every sequence catalogued in UniProt.

  4. DeepMind and EMBL-EBI publish the AlphaFold protein database

    DeepMind and EMBL’s European Bioinformatics Institute opened the AlphaFold Protein Structure Database on 22 July 2021, with more than 350,000 predicted structures covering the roughly 20,000 proteins of the human proteome and 20 other organisms used in research.

  5. AlphaFold 2 nears laboratory accuracy at CASP14

    Organizers of the fourteenth Critical Assessment of protein Structure Prediction said on 30 November 2020 that DeepMind’s AlphaFold 2 had predicted about two-thirds of the competition’s target proteins to an accuracy comparable to laboratory methods.

  6. DeepMind releases AlphaFold predictions for coronavirus proteins

    DeepMind used AlphaFold to predict the shapes of several under-studied SARS-CoV-2 proteins, among them the membrane protein, Nsp2, Nsp4, Nsp6 and the papain-like proteinase, and released them under an open license as computational predictions rather than verified structures.

  7. AlphaFold wins the CASP13 protein-structure contest

    DeepMind’s AlphaFold placed first among entrants at the thirteenth Critical Assessment of protein Structure Prediction in December 2018, a blind test of methods for predicting how a protein folds. It did best on the hardest category, targets with no similar known structure.