Mining the CRBN Target Space Redefines Rules for Molecular Glue-induced Neosubstrate Recognition
Mining the CRBN Target Space Redefines Rules for Molecular Glue-induced Neosubstrate Recognition
Petzold, G.; Gainza, P.; Annunziato, S.; Lamberto, I.; Trenh, P.; McAllister, L. A.; DeMarco, B.; Schwander, L.; Bunker, R. D.; Zlotosch, M.; SriRamaratnam, R.; Gilberto, S.; Langousis, G.; Donckele, E. J.; Quan, C.; Strande, V.; De Donatis, G. M.; Alabi, S. B.; Alers, J.; Matysik, M.; Staehly, C.; Dubois, A.; Osmont, A.; Garskovas, M.; Lyon, D.; Wiedmer, L.; Oleinikovas, V.; Lieberherr, R.; Rubin, N. T.; Lam, D. T.; Widlund, N. I.; Ritzen, A.; Caceres, R. M.; Vigil, D.; Tsai, J.; Wallace, O.; Peluso, M.; Sadok, A.; Paterson, A.; Zarayskiy, V.; Fasching, B.; Bonenfant, D.; Warmuth, M.; Castle,
AbstractThe CRL4CRBN ubiquitin ligase is leveraged by molecular glue degraders, small molecules that reprogram ligase specificity to induce degradation of clinically relevant neosubstrate proteins. Known CRBN neosubstrates share a generalizable {beta}-hairpin G-loop recognition motif, yet systematic exploration of the CRBN target landscape is still pending. Through computational mining of the human proteome using structure-based approaches, we predict over 1,400 CRBN-compatible {beta}-hairpin G-loop proteins across diverse target classes, identify novel mechanisms of neosubstrate recognition through structurally differentiated helical motifs and molecular surface mimicry, and validate 22 representative neosubstrates with clinical implications. This work broadens the CRBN target space, redefines rules for neosubstrate recognition and establishes a platform for the elimination of challenging drug targets by repurposing CRL4CRBN through next-generation molecular glue degraders.