AI Insight
Researchers developed a high-throughput screening platform in human cells to identify AI-designed peptide-guided protein degraders called ubiquibodies (uAbs). These genetically encodable degraders combine peptides generated by protein language models with an E3 ligase domain to selectively target and eliminate specific proteins. The team validated their approach by successfully degrading multiple disease-relevant proteins including β-catenin, GFAP in glioblastoma cells, and the EWS::FLI1 fusion protein in Ewing sarcoma, demonstrating functional therapeutic effects such as reduced cancer cell viability and increased apoptosis.
Why it matters
This technology provides a new approach to eliminate disease-causing proteins that cannot be targeted by traditional drug inhibitors, potentially opening treatment options for previously undruggable targets in cancer and other diseases. The platform's scalability and ability to perform functional selection directly in human cells could accelerate the discovery of novel therapeutic protein degraders.
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⚠️ Preprint – Noch nicht peer-reviewed
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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.
Source: A Mammalian High-Throughput Screen for AI-Designed Peptide-Guided Protein Degraders