Also: AlphaFold, RoseTTAFold, protein folding
Deep-learning programs that predict a protein's 3D shape from its amino-acid sequence.
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Jumper and colleagues presented AlphaFold, the first computational method to regularly predict protein structures with atomic accuracy even when no similar structure is known, with accuracy competitive with experiments in most CASP14 cases.
As reported in: Jumper, Evans, Pritzel et al. (2021). Highly accurate protein structure prediction with AlphaFold. Nature. doi:10.1038/s41586-021-03819-2
Baek and colleagues built a three-track neural network whose predictions approach AlphaFold's CASP14 accuracy and that can model protein–protein complexes from sequence alone.
As reported in: Baek, DiMaio, Anishchenko et al. (2021). Accurate prediction of protein structures and interactions using a three-track neural network. Science. doi:10.1126/science.abj8754
Abramson and colleagues described AlphaFold 3, a diffusion-based model that predicts joint structures of proteins with nucleic acids, small molecules, ions and modified residues, with far better protein–ligand accuracy than docking tools.
Publisher update notice: addendum
As reported in: Abramson, Adler, Dunger et al. (2024). Accurate structure prediction of biomolecular interactions with AlphaFold 3. Nature. doi:10.1038/s41586-024-07487-w