Redesign selective protein binders using contrastive decoding (opens in new tab)

Motivation: Fixed-backbone sequence design methods such as ProteinMPNN operate on backbone coordinates alone and cannot represent target side-chains at the binding interface. Their decoding algorithm also lacks a mechanism to balance binding affinity and folding stability or to improve selectivity against structurally similar off-targets. These gaps limit the computational design of protein binders with high affinity and specificity. Results: We present RedNet, a multiscale graph neural netwo...