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Updated: Jul 11, 2025
16:41
A Protocol for Computer-Based Protein Structure and Function Prediction
Published on: November 3, 2011
68.7K
AlphaFold Protein Structure Database in 2024: providing structure coverage for over 214 million protein sequences
Mihaly Varadi1, Damian Bertoni1, Paulyna Magana1
1European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK.
Nucleic Acids Research
|November 7, 2023
Summary
The AlphaFold Database now provides over 214 million predicted protein structures, significantly expanding structural biology resources. Enhancements include new datasets, improved data access, and upgraded visualization tools.
Area of Science:
- Structural Biology
- Bioinformatics
- Artificial Intelligence in Biology
Background:
- The AlphaFold Database (AlphaFold DB) has revolutionized structural biology with AI-driven protein structure predictions.
- Initial release in 2021 contained 300,000 structures; now exceeds 214 million.
- AlphaFold DB predictions are integrated into major biological databases like UniProt and PDB.
Purpose of the Study:
- To detail the expansion and enhancements of the AlphaFold Database.
- To describe new data releases, access methods, and improved services.
- To highlight the growing impact of AI-predicted protein structures.
Main Methods:
- Archiving of successive AlphaFold DB releases, including model organisms and global health proteomes.
- Integration of curated protein datasets and Swiss-Prot.
- Development of diverse data access mechanisms: FTP, Google Cloud Public Datasets, and programmatic endpoints.
Main Results:
- Expansion to over 214 million predicted protein structures.
- Inclusion of diverse datasets such as model organisms, global health proteomes, and Swiss-Prot.
- Enhanced data access and improved user tools, including the Predicted Aligned Error viewer and 3D viewer.
Conclusions:
- The AlphaFold Database has become an indispensable resource for structural biology research.
- Continuous updates and service improvements enhance data accessibility and utility.
- The database demonstrates the transformative power of AI in biological discovery.
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