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AlphaFold Protein Structure Database
webalphafold.ebi.ac.uk·alphafold.ebi.ac.uk/
AlphaFold is frequently cited in AI safety contexts as a prominent example of transformative AI capability emerging rapidly; relevant to discussions of capability jumps, beneficial AI, and the dual-use nature of advanced AI systems.
Metadata
Importance: 42/100tool pagetool
Summary
AlphaFold DB, developed by Google DeepMind and EMBL-EBI, provides open access to over 200 million AI-predicted protein 3D structures derived from amino acid sequences. It represents a landmark achievement in AI applied to scientific discovery, achieving accuracy competitive with experimental methods. The database covers nearly the entire UniProt protein sequence repository and is freely available to the global research community.
Key Points
- •Contains over 200 million protein structure predictions, covering broad swaths of the known protein universe via UniProt integration.
- •AlphaFold AI system achieves structure prediction accuracy competitive with experimental methods like X-ray crystallography.
- •Ranked top in CASP14 (the critical assessment of protein structure prediction) by a large margin, validating its scientific impact.
- •Demonstrates transformative real-world capability of deep learning, relevant to AI safety discussions about rapid capability jumps.
- •Open-access database and open-source code represent a case study in responsible deployment of powerful AI systems in science.
Cited by 2 pages
| Page | Type | Quality |
|---|---|---|
| Scientific Research Capabilities | Capability | 68.0 |
| Google DeepMind | Organization | 37.0 |
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AlphaFold Protein Structure Database
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AlphaFold Protein Structure Database
AlphaFold Protein Structure Database
AlphaFold Protein Structure Database
Developed by Google DeepMind and EMBL-EBI
Search Search Examples: MENFQKVEKIGEGTYGV... Free fatty acid receptor 2 At1g58602 Q9I1F6 E. coli See search help Go to online course See our updates – March 2026 AlphaFold DB provides open access to over 200 million protein structure predictions to accelerate scientific research. Background
AlphaFold is an AI system developed by Google DeepMind that predicts a protein’s 3D structure from its amino acid sequence. It regularly achieves accuracy competitive with experiment.
Google DeepMind and EMBL’s European Bioinformatics Institute ( EMBL-EBI ) have partnered to create AlphaFold DB to make these predictions freely available to the scientific community. The latest database release contains over 200 million entries, providing broad coverage of UniProt (the standard repository of protein sequences and annotations). We provide individual downloads for the human proteome and for the proteomes of 47 other key organisms important in research and global health. We also provide a download for the manually curated subset of UniProt ( Swiss-Prot ).
Q8I3H7: May protect the malaria parasite against attack by the immune system. Mean pLDDT 85.57.
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In CASP14 , AlphaFold was the top-ranked protein structure prediction method by a large margin, producing predictions with high accuracy . While the system still has some limitations , the CASP results suggest AlphaFold has immediate potential to help us understand the structure of proteins and advance biological research.
Let us know how the AlphaFold Protein Structure Database has been useful in your research, or if you have questions not answered in the FAQs, at alphafold@deepmind.com .
If your use case isn't covered by the database, you can generate your own AlphaFold predictions using this open source code , which also supports multimer prediction.
Q8W3K0: A potential plant disease resistance protein. Mean pLDDT 82.24.
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Find out more
Methodology Human proteome predictions Downloads Online training course About AlphaFold DB Google DeepMind EMBL-EBI What’s new?
Protein complexes - March 2026
A new collaboration between EMBL’s European Bioinformatics Institute (EMBL-EBI), Google DeepMind, NVIDIA, and Seoul National University has made millions of AI-predicted protein complex structures openly available through the AlphaFold Database. This is the largest dataset of protein complex predictions currently available.
To maximise global health impact, the dataset prioritises proteins important for understanding human health and disease, focusing on 20 of the most studied species, including humans, as well as the World Health Organization’s priority p
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