AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models. Issue Volume 50:Issue D1(2022) (17th November 2021) - Varadi, Mihaly; Anyango, Stephen; Deshpande, Mandar; Nair, Sreenath; Natassia, Cindy; Yordanova, Galabina; Yuan, David; Stroe, Oana; Wood, Gemma; Laydon, Agata; Žídek, Augustin; Green, Tim; et al.
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. Lay Summary: The AlphaFold Protein Structure Database (AlphaFold DB, https://alphafold.ebi.ac.uk ) is an extensive, public database of highly accurate protein structure models. The models are the products of AlphaFold2, an Artificial Intelligence algorithm developed by DeepMind. AlphaFold enabled scientists to investigate an unprecedented number of protein structures. The database we describe here provides access to these predicted models and information on their accuracy. The first version of AlphaFold DB contains over 360, 000 models of 21 biologically essential species.