Highly accurate protein structure prediction for the human proteome

Abstract Protein structures can provide invaluable information, both for reasoning about biological processes and for enabling interventions such as structure-based drug development or targeted mutagenesis. Finally, we provide some case studies to illustrate how high-quality predictions could be used to generate biological hypotheses.

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• 1 After decades of effort, 17% of the total residues in human protein sequences are covered by an experimentally determined structure 1 .
• 2 Here we markedly expand the structural coverage of the proteome by applying the advanced machine learning method, AlphaFold 2 , at a scale that covers almost the entire human proteome (98.5% of human proteins).
• 3 The resulting dataset covers 58% of residues with a confident prediction, of which a subset (36% of all residues) have very high confidence.

This work deepens our understanding of the fundamental laws governing the universe, from subatomic particles to cosmic structures.

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