The core problem the researchers set out to solve is a bottleneck familiar to anyone working in targeted protein degradation. Proteomics-based approaches can, in principle, reveal every protein whose abundance changes when a compound is applied, but they are expensive and slow, making them impractical as a first-pass screen for large chemical libraries. Target-based biochemical assays such as AlphaLISA or TR-FRET require purified proteins and, crucially, prior knowledge of which target-E3 pair to test—an assumption that defeats the purpose of hunting for glues against unknown or classically undruggable substrates like transcription factors and scaffold proteins. Phenotypic screens, meanwhile, are biologically rich but cannot easily distinguish a true degrader from an ordinary inhibitor, forcing laborious downstream mechanistic deconvolution. What the field needed was a cheap, fast, and mechanistically informative primary readout.

The team’s answer was to make the transcriptome itself the universal readout. Gene expression signatures are high-dimensional proxies for cellular state, a principle demonstrated at scale by the L1000 platform and made affordable by DRUG-seq, which skips RNA purification and uses direct cell lysis with multiplexed library preparation. The researchers employed an optimized version, DRUG-seq2, which they report offers superior sensitivity for low-abundance regulatory transcripts—a critical feature when the signals of interest come from immature, weak molecular glues. In their workflow, Hep3B liver cancer cells were seeded in 96-well plates, treated with compounds at a uniform concentration of 1 micromolar for 24 hours, and processed through the miniaturized sequencing protocol. The library comprised 117 compounds: 11 commercial molecular glues serving as validated benchmarks and 106 in-house candidates synthesized by two collaborative research groups, all rationally designed to modulate the cereblon (CRBN) E3 ligase.

A deceptively simple but essential innovation lies in how the baseline is defined. Because DRUG-seq2 relies on direct lysis, technical noise can swamp the subtle transcriptional ripples produced by nascent glues. Before any analysis, the team performed systematic pairwise Pearson correlation analysis across all DMSO vehicle wells on each plate, excluding any replicate with a correlation coefficient below 0.95. By constructing the reference transcriptome solely from high-consensus control wells, they established a robust, self-consistent zero-point that maximizes statistical power to resolve low-magnitude perturbations. Downstream, differential expression analysis with DESeq2—flagging genes with absolute log2 fold change greater than 1 and adjusted p-value below 0.05—was paired with gene set enrichment analysis (GSEA) built from six curated collections, including Hallmark, Reactome, KEGG, Gene Ontology Biological Process, C6, and the C3 transcription factor target set. This two-layer design means even compounds with few or zero individual differentially expressed genes can still betray coordinated pathway-level activity.

The mechanistic heart of the platform is a genetic benchmark: an isogenic pair of Hep3B cell lines, one wild-type and one in which CRBN has been knocked out via CRISPR-Cas9. The researchers established a stable Cas9-expressing parent line, introduced single-guide RNAs targeting CRBN, and isolated single-cell clones. Clone 3 emerged as the definitive knockout after rigorous validation. Treatment with CC-90009, a clinical molecular glue that degrades the translation termination factor GSPT1, provided the proof: in wild-type cells the drug rapidly and almost completely eliminated GSPT1 protein, while in the knockout the effect vanished entirely, along with the drug’s cytotoxic potency, which showed a pronounced right-shift in the IC50 curve. Any compound whose transcriptional signature collapses in the knockout is therefore flagged as CRBN-dependent—a hallmark of a genuine glue—whereas signals that persist likely reflect off-target toxicity, conventional inhibition, or hijacking of a different E3 ligase such as VHL or DCAF16.

Screening the full library revealed a strikingly polarized activity spectrum. Roughly 20 percent of the compounds were transcriptionally inert, producing zero differentially expressed genes under the test conditions. At the other extreme, the high-activity cluster was dominated by known glues: SJ3149, which targets CK1α, elicited the most profound response, followed by lenalidomide, BMS-986397, and a MYC degrader. For most of these, transcriptional activity was almost completely abolished in the CRBN knockout, exactly as expected for classic glues. Encouragingly, one in-house compound, LC-02-047-P1, landed among the potent performers, marking it as a promising novel candidate. Conversely, compounds such as LC-02-105 and LC-02-033 displayed a paradoxical knockout-amplified phenotype, indicating CRBN-independent mechanisms and allowing the team to filter out molecules whose intrinsic scaffold toxicity overwhelmed any degradation function.

The pathway-level analysis added mechanistic texture that raw gene counts alone could not provide. Potent GSPT1 degraders such as CC-90009 upregulated regulators of the integrated stress response—DDIT3 (CHOP), GDF15, TRIB3, DDIT4, and PPP1R15A—consistent with the biology of translation termination failure: ribosomes stall at stop codons, collide, and trigger the ZAKα-mediated ribotoxic stress response, which in turn activates ATF4 and suppresses the translational apparatus to mitigate proteotoxic stress. GSEA of CC-90009 confirmed enrichment of integrated stress response, proteasome, and apoptosis pathways alongside downregulation of translation machinery. LC-02-047-P1, by contrast, showed metabolic rather than stress-related regulatory characteristics, hinting that its degraded target might be an upstream switch governing multiple metabolic pathways. The enrichment layer also rescued latent hits: LC-02-051 performed modestly in the differential expression analysis but ranked near the top in pathway enrichment, and its signal was completely blocked by CRBN knockout—suggesting a genuine but weak glue worth optimizing. Even CC-92480 yielded an instructive anomaly, showing slightly expanded enrichment in knockout cells, which the authors attribute to the absence of its high-affinity target IKZF1 in Hep3B, pushing the compound toward non-canonical substrates or generic xenobiotic stress.

To translate these multidimensional data into decisions, the researchers built a scatterplot integrating transcriptional potency (differential gene counts) with functional breadth (enriched pathway counts) across both wild-type and knockout conditions, then stratified the library into four tiers. Tier one comprises potent glues with high wild-type activity that nearly vanishes upon CRBN loss—the highest priorities for optimization. Tier two captures intermediate and latent leads whose coordinated functional signals suggest seed scaffolds needing structural refinement. Tier three contains active but E3-independent perturbators, likely conventional inhibitors, and tier four collects inert compounds. The spatial logic is intuitive: strong glues such as SJ3149, lenalidomide, CC-90009, and LC-02-047-P1 occupy the upper-right quadrant and collapse toward the origin in the knockout, while pharmacologically inert molecules cluster near the origin in both conditions and target-independent agents stubbornly refuse to move. The thresholds, the authors note, can be customized for different libraries.

Proteomic cross-validation demonstrated that the transcriptomic tiers predict real degradation events. Tandem mass tag quantitative proteomics of LC-02-047-P1-treated Hep3B cells revealed marked downregulation of CSNK1A1 (CK1α), and western blotting across Hep3B, Huh7, and HepG2 hepatocellular carcinoma lines confirmed near-complete, selective CK1α degradation with no effect on GSPT1. A decisive control sealed the case: cells engineered to express a non-degradable GSPT1 mutant abolished CC-90009’s activity but left LC-02-047-P1’s CK1α degradation untouched, proving the candidate acts entirely independently of GSPT1. The weaker tier-two compound LC-02-051 produced only minor proteomic perturbation, with TPM3 changes failing statistical validation—consistent with its latent classification. On scalability, the economics are compelling: the platform costs less than 100 RMB (roughly 14 US dollars) per sample, about 2 percent of standard TMT proteomics, with an end-to-end turnaround of three to four weeks even beyond 1,000 compounds.

The authors are candid about limitations. The single 24-hour window captures an integrated cellular state—primary degradation consequences blended with secondary cascades and stress responses—rather than the immediate transcriptional footprints of neosubstrate depletion, and future iterations will incorporate time-resolved profiling. Transcriptomic signatures also remain an indirect proxy for protein-level events, so candidate leads must ultimately be confirmed by quantitative proteomics and structural biology demonstrating direct ternary complex formation. The choice of screening cell line matters too, since E3 and substrate abundance dictate sensitivity; the authors suggest abundance-matched models, such as VHL-high or DCAF15-high backgrounds, for targeted campaigns. Even so, the GPS platform fills a genuine gap, bridging high-volume chemical screening and low-throughput mechanistic validation, and offering the field a practical roadmap for converting molecular glue discovery from a lucky accident into an engineering discipline.

Subject of Research: High-throughput transcriptomic screening for the discovery of CRBN-dependent molecular glue degraders

Article Title: A scalable, high-throughput glue perturbation screening platform for molecular glue discovery

Article References: Huang, D., Shuang, Z., Chen, L., Ouyang, H., Yang, P., Huang, L., Lu, W., Shi, M., Ding, X., Jiang, B., & Wu, W. (2026). A scalable, high-throughput glue perturbation screening platform for molecular glue discovery. iScience, 29(10), Article 117600. https://doi.org/10.1016/j.isci.2026.117600

Image Credits: AI Generated

DOI: 10.1016/j.isci.2026.117600

Keywords: molecular glue degraders, targeted protein degradation, CRBN, DRUG-seq2, transcriptomics, gene set enrichment analysis, CRISPR knockout, E3 ubiquitin ligase, proteomics, drug discovery, GSPT1, CK1α