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High-throughput diversification of protein-ligand surfaces to discover chemical inducers of proximity

GSE278582 Homo sapiens Expression profiling by high throughput sequencing 9 samples Submitted 2025/07/31 Platform GPL18573
Summary
Chemical inducers of proximity (CIPs) stabilize biomolecular interactions, often causing a privileged rewiring of cellular biochemistry. While rational design strategies can expedite the discovery of heterobifunctional CIPs, molecular glues have predominantly been discovered by serendipity. Envisioning a prospective approach to discover molecular glues for a pre-selected target, we hypothesized that pre-existing ligands could be systematically decorated with chemical modifications to discover protein-ligand surfaces that are tuned to cooperatively engage another protein interface. Using high-throughput chemical synthesis to diversify a ligand for the transcriptional coactivator ENL with 3,163 structurally diverse chemical building blocks, we discovered a compound dHTC1 that elicits potent, selective, and stereochemistry-dependent degradation of ENL by induced binding to CRL4CRBN. Unlike prior CRBN-based degraders, dHTC1 binds the ligase with high affinity only after forming the ENL:dHTC1 complex, relying on a hybrid interface of protein-protein and protein-ligand contacts. Altogether, this study points toward an expanded chemical space for co-opting the therapeutically important substrate receptor, CRBN, and a second proof-of-concept extending this approach to BRD4 further validates high-throughput chemistry as a facile tool to discover new degraders
Published in
High-throughput diversification of protein-ligand surfaces to discover chemical inducers of proximity
Shaum JB, Muñoz I Ordoño M, Steen EA et al. · bioRxiv : the preprint server for biology 2025 · PMID 40950085 · doi:10.1101/2024.09.30.615685
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Direct links to NCBI, no account and no request form: the whole study as GSE278582_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 9 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA1167869 and SRA study SRP536127. Searching any of these in the dataset finder brings you back here.

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