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AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models.

Mihaly VaradiStephen AnyangoMandar S DeshpandeSreenath NairCindy NatassiaGalabina YordanovaDavid YuanOana StroeGemma WoodAgata LaydonAugustin ŽídekTim GreenKathryn TunyasuvunakoolStig PetersenJohn JumperEllen ClancyRichard GreenAnkur VoraMira LutfiMichael FigurnovAndrew CowieNicole HobbsPushmeet KohliGerard KleywegtEwan BirneyDemis HassabisSameer Velankar
Published in: Nucleic acids research (2021)
The AlphaFold Protein Structure Database (AlphaFold DB, https://alphafold.ebi.ac.uk) is an openly accessible, extensive database of high-accuracy protein-structure predictions. Powered by AlphaFold v2.0 of DeepMind, it has enabled an unprecedented expansion of the structural coverage of the known protein-sequence space. AlphaFold DB provides programmatic access to and interactive visualization of predicted atomic coordinates, per-residue and pairwise model-confidence estimates and predicted aligned errors. The initial release of AlphaFold DB contains over 360,000 predicted structures across 21 model-organism proteomes, which will soon be expanded to cover most of the (over 100 million) representative sequences from the UniRef90 data set.
Keyphrases
  • amino acid
  • protein protein
  • binding protein
  • adverse drug
  • cross sectional
  • small molecule
  • machine learning
  • mass spectrometry
  • artificial intelligence
  • drug induced