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

“AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models” (2021), by Mihály Váradi et al. Genetics and Biochemistry research paper. Original abstract below, unchanged. No free PDF was found.

- Authors: Mihály Váradi, Stephen Anyango, Mandar Deshpande, Sreenath Sasidharan Nair, Cindy Natassia, Galabina Yordanova, David Yu Yuan, Oana Stroe, Gemma Wood, Agata Laydon et al.
- Published: October 19, 2021
- Field: Genetics and Biochemistry
- DOI: https://doi.org/10.1093/nar/gkab1061
- Source: https://doi.org/10.1093/nar/gkab1061

## 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.

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