Hiring in life sciences? Share your open positions with our professional community. Read more Close

Advertisement

A Mammalian High-Throughput Screen for AI-Designed Peptide-Guided Protein Degraders

Created on 27 Aug 2026

Authors

Zhao, L., Mattix, A., Pal, A., Chen, T., Vincoff, S., Hong, L., Renteria, D., Sase, S., Vanderver, A. L., Matson, D. R., Chatterjee, P.

Abstract

Targeted protein degradation (TPD) offers a route to eliminate disease-driving proteins that remain inaccessible to conventional inhibitors. However, degrader discovery remains low-throughput, labor-intensive, and dependent on randomized libraries or non-human display systems, limiting functional selection in mammalian cells. Here, we present a high-throughput, human cell-based platform for screening peptide-guided ubiquibodies (uAbs). These genetically encodable, doxycycline-inducible degraders fuse peptide guides generated by protein language models to the CHIP{Delta}TPR E3 ligase domain, creating a modular, CRISPR-like system for programmable TPD. For each target, we introduce a pooled uAb library into the corresponding fluorescent reporter cell line, isolate cells with reduced target abundance by FACS, and recover enriched peptide guides by sequencing. For {beta}-catenin, enriched uAbs reduced endogenous {beta}-catenin abundance and Wnt signaling in DLD1 cells. GFAP-directed uAbs reduced endogenous GFAP abundance and cell viability in U251 glioblastoma cells, while EWS::FLI1-directed uAbs reduced fusion oncoprotein abundance, suppressed EWSAT1 expression, and increased apoptosis in Ewing sarcoma models. Finally, a screen using endogenously tagged GATA2 further identified uAbs that reduced GATA2 under native genomic regulation. Overall, our platform connects generative peptide design to functional mammalian selection and establishes a scalable strategy for CRISPR-like proteome perturbation.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 27 Aug 2026.

Advertisement

Stats

  • Community rating n/a 0 votes
  • Your rating

1-terrible, 9-excellent. How would you rate this preprint? Sign in in to submit your rating.

  • Recommendations n/a n/a positive of 0 vote(s)
  • Views 26
  • Comments 0

Recommended by

  • No recommendations yet.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.

Advertisement