Combinatorial deep mutational scanning uncovers protein superbinders and molecular determinants of epistasis.
Abstract
Traditional deep mutational scanning (DMS) encodes every single amino-acid substitution from a wild-type sequence. We hypothesize that combinatorial DMS (CDMS) libraries, incorporating all mutations in all combinations, can enable the discovery of high-affinity protein (super)binders by capturing epistatic, non-linear amino-acid interactions. Here, we introduce origin-independent and context-exhaustive high-throughput integration of combinatorial DMS libraries (ORCHID), which systematically maps regions of wild-type-independent epistasis across all mutational contexts and trajectories. For benchmarking, we build a high-throughput peptide display assay measuring PIN1WW-domain affinity for a CDMS peptide library containing phosphoserine via amber codon suppression. ORCHID raises prediction accuracy by 45% over non-epistatic models. We identify and structurally characterize two epistatic superbinders, SPY-tide and LYR-tide, binding 3- to 5-fold tighter than current optimal PIN1WW-domain binders through "fold-and-turn" and register-shifted conformational changes. We also identify two molecular determinants of epistasis, PIN1F25 and PIN1R14, that natively encode non-linear binding and, when mutated, abolish it. Hence, natural proteins recognize peptides non-linearly, offering opportunities for improved binder design.
