Paper
AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models
Abstract 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.
Authors: Mihaly Varadi · Stephen Anyango · Mandar Deshpande · Sreenath Nair · Cindy Natassia · Galabina Yordanova · David Yuan · Oana Stroe · Gemma Wood · Agata Laydon · Augustin Žídek · Tim Green · Kathryn Tunyasuvunakool · Stig Petersen · John Jumper · Ellen Clancy · Richard Green · Ankur Vora · Mira Lutfi · Michael Figurnov · Andrew Cowie · Nicole Hobbs · Pushmeet Kohli · Gerard Kleywegt · Ewan Birney · Demis Hassabis · Sameer Velankar