Combinatorial Deep Mutational Scanning Uncovers Protein Superbinders and Molecular Determinants of Epistasis

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 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 45% over non-epistatic models. We identify and structurally characterize two epistatic superbinders, SPY-tide and LYR-tide, binding 3–5-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.

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Publication Details

Journal
Apollo
Published
2026-08-20
DOI
https://doi.org/10.17863/cam.133431
Primary Topic
Biochemical and Structural Characterization
Type
article
Field-Weighted Citation Impact
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article

Combinatorial Deep Mutational Scanning Uncovers Protein Superbinders and Molecular Determinants of Epistasis

Mingxuan Jiang, Pau Creixell, Allyson Li, Teresa Augustin et al.
Apollo
Biochemical and Structural Characterization
article

Combinatorial Deep Mutational Scanning Uncovers Protein Superbinders and Molecular Determinants of Epistasis

Mingxuan Jiang, Pau Creixell, Allyson Li, Teresa Augustin, Mihkel Örd, Nuo Cheng, Jesse Rinehart, Neel Shah, Helen Mott, Mohan Sun
article en

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 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 45% over non-epistatic models. We identify and structurally characterize two epistatic superbinders, SPY-tide and LYR-tide, binding 3–5-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.

Apollo
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Biochemical and Structural Characterization
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