Sign in
Synthetic BiologybioRxiv
Preprint

High-throughput protein binder discovery by rapid in vivo selection

Matthew J. StylesiD, Joshua A. PixleyiD, Tongyao WeiiD, Christopher BasileiD, Shannon S. LuiD, Bryan C. DickinsoniD

Abstract

Proteins that selectively bind to a target of interest are foundational components of research pipelines1,2, diagnostics3, and therapeutics4. Current immunization-based5,6, display-based7-14, and computational approaches15-17,18 for discovering binders are laborious and time-consuming - taking months or more, suffer from high false positives - necessitating extensive secondary screening, and have a high failure rate, especially for disordered proteins and other challenging target classes. Here we establish Phage-Assisted Non-Continuous Selection of Protein Binders (PANCS-binders), an in vivo selection platform that links the life cycle of M13 phage to target protein binding though customized proximity-dependent split RNA polymerase biosensors, allowing for complete and comprehensive high-throughput screening of billion-plus member protein variant libraries with high signal-to-noise. We showcase the utility of PANCS-Binders by screening multiple protein libraries each against a panel of 95 separate therapeutically relevant targets, thereby individually assessing over 1011 protein-protein interaction pairs, completed in two days. These selections yielded large, high-quality datasets and hundreds of novel binders, which we showed can be affinity matured or directly used in mammalian cells to inhibit or degrade targets. PANCS-Binders dramatically accelerates and simplifies the binder discovery process, the democratization of which will help unlock new creative potential in proteome-targeting with engineered binder-based biotechnologies.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISPixley '26Styles '26Keyser '24Egloff '18Chen '19Lu '25
75% semantic matchSynthetic Biology
Joshua A. Pixley, Matthew J. Styles, Kanokpol Aphicho+5 more·Proceedings of the National Academy of Sciences·Jun 2, 2026· 3 citations