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  "documentTitle": "2021 Air Street Capital The State of AI Report 2021",
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  "authorName": "Air Street Capital",
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  "notes": "The chart shows CASP14 performance metrics comparing AlphaFold (G427) against other participants.",
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      "text": "The AlphaFold DB plans to deliver a >2,000-fold increase in the number of structures for known protein sequences and a >700-fold increase in total number of structures by the end of 2021.",
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      "kind": "chart",
      "text": "Median RMSD95-Ca in Å for CASP14 participants",
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      "text": "In our 2020 Report we predicted: “DeepMind makes a major breakthrough in structural biology and drug discovery beyond AlphaFold.”\nDeepMind returned to CASP14 (2020) with a new system, AlphaFold 2 (AF2), two years winning CASP13 (2018) with AF1.\nAF1 used convolutional layers to predict a distance map between pairs of amino acids in order to generate a 3D structure.\nAF2 uses a spatial graph representation of amino acids. Residues are the nodes and edges connect the residues in close proximity.\nNext, an attention-based model is trained end-to-end to interpret the structure of this graph along with evolutionarily related sequences, multiple sequence alignment (MSA), and amino acid residue pair representation to iteratively refine this graph from which 3D protein structure coordinates are generated.\nThe AlphaFold DB plans to deliver a >2,000-fold increase in the number of structures for known protein sequences and a >700-fold increase in total number of structures by the end of 2021.",
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      "kind": "title",
      "text": "2020 Prediction: AlphaFold 2",
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