Database Commons
Database Commons

a catalog of worldwide biological databases

Database Profile

AlphaFold DB

General information

URL: https://alphafold.ebi.ac.uk/
Full name: AlphaFold Protein Structure Database
Description: AlphaFold DB provides open access to AlphaFold protein structure predictions for the human proteome and other key organisms to accelerate scientific research.
Year founded: 2022
Last update: 2021
Version:
Accessibility:
Accessible
Country/Region: United Kingdom

Classification & Tag

Data type:
Data object:
Database category:
Major species:
Keywords:

Contact information

University/Institution: European Bioinformatics Institute
Address: EMBL-EBI, Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK. +44 (0)1223 49 44 44
City: Hinxton
Province/State: Cambridgeshire
Country/Region: United Kingdom
Contact name (PI/Team): Sameer Velankar
Contact email (PI/Helpdesk): afdbhelp@ebi.ac.uk

Publications

40133787
AlphaFold Protein Structure Database and 3D-Beacons: New Data and Capabilities. [PMID: 40133787]
Jennifer Fleming, Paulyna Magana, Sreenath Nair, Maxim Tsenkov, Damian Bertoni, Ivanna Pidruchna, Marcelo Querino Lima Afonso, Adam Midlik, Urmila Paramval, Augustin Žídek, Agata Laydon, Oleg Kovalevskiy, Joshua Pan, Jun Cheng, Žiga Avsec, Clare Bycroft, Lai Hong Wong, Meera Last, Milot Mirdita, Martin Steinegger, Pushmeet Kohli, Mihály Váradi, Sameer Velankar

The AlphaFold Protein Structure Database (https://alphafold.ebi.ac.uk/) has made significant strides in enhancing its utility and accessibility for the life science research community. The recent integration of AlphaMissense predictions enables access to the pathogenicity of human protein missense variants, with an innovative and interactive heatmap and 3D visualisation that display variant data at the residue level. Users can now toggle between structure model quality (pLDDT) and average pathogenicity scores, providing insights into the implications of specific residue changes. The Foldseek integration offers a rapid and accurate method for protein structure searches and comparisons. Bulk data download options further facilitate comprehensive data analysis and integration with other computational tools. The 3D-Beacons framework (https://www.ebi.ac.uk/pdbe/pdbe-kb/3dbeacons/) has also been enhanced with detailed annotation endpoints (such as AlphaMissense data) and integrates LevyLab's dataset of homomeric AlphaFold 2 models. These advancements significantly improve the functionality and accessibility of these resources, enabling discoveries using structure data.

J Mol Biol. 2025:437(15) | 17 Citations (from Europe PMC, 2025-12-13)
37933859
AlphaFold Protein Structure Database in 2024: providing structure coverage for over 214 million protein sequences. [PMID: 37933859]
Mihaly Varadi, Damian Bertoni, Paulyna Magana, Urmila Paramval, Ivanna Pidruchna, Malarvizhi Radhakrishnan, Maxim Tsenkov, Sreenath Nair, Milot Mirdita, Jingi Yeo, Oleg Kovalevskiy, Kathryn Tunyasuvunakool, Agata Laydon, Augustin Žídek, Hamish Tomlinson, Dhavanthi Hariharan, Josh Abrahamson, Tim Green, John Jumper, Ewan Birney, Martin Steinegger, Demis Hassabis, Sameer Velankar

The AlphaFold Database Protein Structure Database (AlphaFold DB, https://alphafold.ebi.ac.uk) has significantly impacted structural biology by amassing over 214 million predicted protein structures, expanding from the initial 300k structures released in 2021. Enabled by the groundbreaking AlphaFold2 artificial intelligence (AI) system, the predictions archived in AlphaFold DB have been integrated into primary data resources such as PDB, UniProt, Ensembl, InterPro and MobiDB. Our manuscript details subsequent enhancements in data archiving, covering successive releases encompassing model organisms, global health proteomes, Swiss-Prot integration, and a host of curated protein datasets. We detail the data access mechanisms of AlphaFold DB, from direct file access via FTP to advanced queries using Google Cloud Public Datasets and the programmatic access endpoints of the database. We also discuss the improvements and services added since its initial release, including enhancements to the Predicted Aligned Error viewer, customisation options for the 3D viewer, and improvements in the search engine of AlphaFold DB.

Nucleic Acids Res. 2024:52(D1) | 983 Citations (from Europe PMC, 2025-12-13)
34791371
AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models. [PMID: 34791371]
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

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.

Nucleic Acids Res. 2022:50(D1) | 5310 Citations (from Europe PMC, 2025-12-13)

Ranking

All databases:
3/6895 (99.971%)
Structure:
1/967 (100%)
3
Total Rank
5,737
Citations
1,912.33
z-index

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Record metadata

Created on: 2021-10-19
Curated by:
shaosen zhang [2025-06-29]
shaosen zhang [2024-08-23]
zheng luo [2024-07-16]
Lina Ma [2022-06-20]
Alex Bateman [2022-06-20]
Pei Liu [2022-04-24]
Dong Zou [2021-10-19]