AlphaFold: Difference between revisions
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==AlphaFold Database of Predictions== | ==AlphaFold Database of Predictions== | ||
In July, 2021, DeepMind made available over 300,000 structure predictions from amino acid sequences in their free [https://alphafold.ebi.ac.uk/ AlphaFold DB]<ref name="deepminddb">[https://deepmind.com/research/case-studies/alphafold#a_treasure_trove We’ve made AlphaFold predictions freely available to anyone in the scientific community] at DeepMind.com (date of release not specified, approximately July 2021).</ref><ref name="afdbebi">[https://www.ebi.ac.uk/pdbe/about/news/alphafold%E2%80%99s-protein-structure-predictions-now-available-explore AlphaFold’s protein structure predictions now available to explore] at the European Bioinformatics Institute, July 23, 2021.</ref><ref name="impacts">[https://www.embl.org/news/science/alphafold-potential-impacts/ Great expectations – the potential impacts of AlphaFold DB] at the European Bioinformatics Institute, July 22, 2021</ref><ref name="human">[https://www.embl.org/news/science/alphafold-database-launch/ DeepMind and EMBL release the most complete database of predicted 3D structures of human proteins] at the European Bioinformatics Institute, July 22, 2021.</ref>. These predictions include nearly all ~20,000 proteins in the human proteome, 36% with very high confidence, and another 22% with high confidence<ref name="human" /><ref name="human-nature">PMID: 34293799</ref>. Also included are ''E. coli'', fruit fly, mouse, zebrafish, malaria parasite and tuberculosis bacteria<ref name="human" />. Limitations of these predictions were enumerated<ref name="impacts" />, including: | In July, 2021, DeepMind made available over 300,000 structure predictions from amino acid sequences in their free [https://alphafold.ebi.ac.uk/ AlphaFold DB]<ref name="deepminddb">[https://deepmind.com/research/case-studies/alphafold#a_treasure_trove We’ve made AlphaFold predictions freely available to anyone in the scientific community] at DeepMind.com (date of release not specified, approximately July 2021).</ref><ref name="afdbebi">[https://www.ebi.ac.uk/pdbe/about/news/alphafold%E2%80%99s-protein-structure-predictions-now-available-explore AlphaFold’s protein structure predictions now available to explore] at the European Bioinformatics Institute, July 23, 2021.</ref><ref name="impacts">[https://www.embl.org/news/science/alphafold-potential-impacts/ Great expectations – the potential impacts of AlphaFold DB] at the European Bioinformatics Institute, July 22, 2021</ref><ref name="human">[https://www.embl.org/news/science/alphafold-database-launch/ DeepMind and EMBL release the most complete database of predicted 3D structures of human proteins] at the European Bioinformatics Institute, July 22, 2021.</ref>. These predictions include nearly all ~20,000 proteins in the human proteome, 36% with very high confidence, and another 22% with high confidence<ref name="human" /><ref name="human-nature">PMID: 34293799</ref>. Also included are ''E. coli'', fruit fly, mouse, zebrafish, malaria parasite and tuberculosis bacteria<ref name="human" />. Limitations of these predictions were enumerated<ref name="impacts" /><ref name="perils" />, including: | ||
* Inability to predict protein-protein or protein-DNA/RNA/ligand complexes. [[#RoseTTAFold]] and AlphaFold both claim progress on predicting protein-protein complexes. | * Inability to predict protein-protein or protein-DNA/RNA/ligand complexes. [[#RoseTTAFold]] and AlphaFold both claim progress on predicting protein-protein complexes. | ||
* Does not predict ligands, cofactors, metals, ions, glycosylation, etc. | * Does not predict ligands, cofactors, metals, ions, glycosylation, etc. | ||