
AlphaFold
AI system predicting protein structures to accelerate biological research.
Open access database of protein structure predictions to accelerate scientific research.

The AlphaFold Protein Structure Database, developed by Google DeepMind and EMBL-EBI, provides open access to over 200 million protein structure predictions, covering a broad range of organisms. It uses an AI system that predicts a protein's 3D structure from its amino acid sequence with high accuracy. The database includes individual downloads for the human proteome and other key organisms. It aims to accelerate scientific research by providing structural insights to researchers worldwide. The data is available for academic and commercial use under a CC-BY-4.0 license.
The AlphaFold Protein Structure Database, developed by Google DeepMind and EMBL-EBI, provides open access to over 200 million protein structure predictions, covering a broad range of organisms.
Explore all tools that specialize in predict 3d protein structure from sequence. This domain focus ensures AlphaFold Protein Structure Database delivers optimized results for this specific requirement.
Explore all tools that specialize in download individual proteomes. This domain focus ensures AlphaFold Protein Structure Database delivers optimized results for this specific requirement.
Explore all tools that specialize in search for predicted structures by protein identifier. This domain focus ensures AlphaFold Protein Structure Database delivers optimized results for this specific requirement.
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Utilizes a deep learning AI system trained on experimental data to predict protein structures with accuracy competitive with experimental methods.
Covers over 200 million protein structures, including the human proteome and proteomes of other key organisms.
Accepts large-scale datasets from scientific communities, incorporating specialized structural knowledge.
Provides a programmatic API for automated data retrieval and integration into existing workflows.
Includes prediction confidence scores (pLDDT) for each residue, allowing users to assess the reliability of the predictions.
Supports prediction of protein complexes using the open-source code.
Continuously updated with new protein sequences and improved features based on user feedback.
Access the database through the website.
Search for proteins using sequence or UniProt ID.
Download structure predictions in PDB format.
Utilize the API for automated data retrieval.
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“Generally positive, with researchers praising the database's accuracy and coverage.”
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