High-throughput diversification of protein-ligand surfaces to discover chemical inducers of proximity
Shaum, J. B.; Munoz i Ordono, M.; Steen, E. A.; Wenge, D. V.; Cheong, H.; Hunkeler, M.; Bilotta, E. M.; Rutter, Z.; Barta, P. A.; Thornhill, A. M.; Milosevich, N.; Hargis, L. M.; Janowski, J.; Bishop, T. R.; Carter, T. R.; da Camara, B.; Hinterndorfer, M.; Dada, L.; He, W.-J.; Offensperger, F.; Furihata, H.; Schweber, S. R.; Hatton, C.; Wen, Y.; Cravatt, B. F.; Engle, K. M.; Donovan, K. A.; Melillo, B.; Kitamura, S.; Ciulli, A.; Armstrong, S. A.; Fischer, E. S.; Winter, G. E.; Erb, M. A.
Show abstract
Chemical inducers of proximity (CIPs) stabilize biomolecular interactions, often causing an emergent rewiring of cellular biochemistry1,2. While rational design strategies can expedite the discovery of heterobifunctional CIPs, monovalent, molecular glue-like CIPs have relied predominantly on serendipity3. 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 empirically discover protein-ligand surfaces that are tuned to cooperatively engage another protein interface. Here, we used sulfur(VI)-fluoride exchange (SuFEx)-based high-throughput chemistry (HTC) to install 3,163 structurally diverse chemical building blocks onto ENL and BRD4 ligands and then screened the crude products for degrader activity. This revealed dHTC1, a potent, selective, and stereochemistry-dependent degrader of ENL. It recruits CRL4CRBN to ENL through an extended interface of protein-protein and protein-ligand contacts, but only after pre-forming the ENL:dHTC1 complex. We also characterized two structurally distinct BRD4 degraders, including dHTC3, a molecular glue that selectively dimerizes the first bromodomain of BRD4 to SCFFBXO3, an E3 ligase not previously accessible for chemical rewiring. Altogether, this study introduces HTC as a facile tool to discover new CIPs and actionable cellular effectors of proximity pharmacology.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.