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AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models

📅 October 19, 2021 👤 Mihály Váradi, Stephen Anyango, Mandar Deshpande et al. 📖 Nucleic Acids Research 📊 8,220 citations

🤖 Plain-English Summary

Abstract The AlphaFold Protein Structure Database (AlphaFold DB, https://alphafold.ebi.ac.uk) is an openly accessible, extensive database of high-accuracy protein-structure predictions. AlphaFold DB provides programmatic access to and interactive visualization of predicted atomic coordinates, per-residue and pairwise model-confidence estimates and predicted aligned errors.

🔑 Key Findings

  • Powered by AlphaFold v2.0 of DeepMind, it has enabled an unprecedented expansion of the structural coverage of the known protein-sequence space.
  • AlphaFold DB provides programmatic access to and interactive visualization of predicted atomic coordinates, per-residue and pairwise model-confidence estimates and predicted aligned errors.
  • The initial release of AlphaFold DB contains over 360,000 predicted structures across 21 model-organism proteomes, which will soon be expanded to cover most of the (over 100 million) representative sequences from the UniRef90 data set.

💡 Why This Matters

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

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📋 Article Details

Category 🤖 Artificial Intelligence
Published Oct 19, 2021
Journal Nucleic Acids Research
Authors Mihály Váradi, Stephen Anyango, Mandar Deshpande, Sreenath Nair, Cindy Natassia
DOI 10.1093/nar/gkab1061
Citations 8,220
Source OpenAlex

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