AlphaFold Database Offers Free Access to 200 Million Predicted Protein Structures
A collaborative database from Google DeepMind and EMBL-EBI provides open access to over 200 million AI-generated protein structure predictions. This massive resource accelerates biological research by delivering highly accurate 3D models that rival experimental methods.
The AlphaFold Protein Structure Database provides open access to over 200 million protein structure predictions, dramatically accelerating scientific research worldwide. Developed by Google DeepMind in partnership with EMBL-EBI, this groundbreaking resource uses artificial intelligence to predict a protein's 3D structure directly from its amino acid sequence.
This massive database achieves accuracy that competes directly with traditional experimental methods, offering broad coverage of the standard UniProt repository. Researchers freely access individual downloads for the human proteome, the manually curated Swiss-Prot subset, and the proteomes of 47 other key organisms relevant to global health.
Scientists use these detailed structural predictions to advance biological research, from understanding malaria parasite defenses to studying potential plant disease resistance proteins. For research needs outside the current database, users generate their own customized predictions using the openly available AlphaFold source code.