De novo protein design: what are we learning?

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Learning inverse folding from millions of predicted structures (2022, background): “Structure-based protein sequence design Early work on design of protein sequences studied the packing of amino acid side chains to fill the interior space of predetermined backbone structures, either for a fixed backbone conformation (Street & Mayo, 1999; Dahiyat & Mayo, 1997; DeGrado et al., 1991),”
Masked Inverse Folding with Sequence Transfer for Protein Representation Learning (2023, methodology): “Outside of deep-learning based methods, researchers use packing algorithms (Dahiyat & Mayo, 1997; Street & Mayo, 1999; DeGrado et al., 1991; Harbury et al., 1998), physics-based energy functions (Alford et al., 2017), or match structural motifs to sequence motifs (Zhou et al., 2020).”