Improved De Novo Peptide Binder Design with Target-Conditioned Inverse Folding
Layne, E.; Kanawaty, A. K.; Broom, A.; Kitaygorodsky, A.; Nivedha, A. K.; Vora, P.; Woffindale, C.; Hailstone, S.; Sachouli, E.; Halcrow, E.; Donachie, G.; Adsett, M.; Butterfoss, G. L.; Fingerhuth, M.
Show abstract
Inverse protein folding methods have become central to the computational design of de novo proteins, but existing models struggle when tasked with generating high-affinity peptide binders. By combining peptide-specific finetuning with a novel decoding order strategy, we enhance pocket conditioning and enable more accurate sequence design for peptide-binding interfaces. Our approach delivers gains in computational metrics, increasing sequence recovery and improving in silico binder design success rate by 16% 30%. In vitro validation finds that our method greatly improves the success rate of designing novel peptide agonists of the OPRM1 receptor, generating at least twice as many top-ranking agonists as the prevailing standard method ProteinMPNN.
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