Integrated proteomic screening reveals design principles of CRBN molecular glue degraders

Abstract Cereblon (CRBN)-based molecular glue degraders (MGDs) induce the degradation of diverse disease-relevant proteins, underscoring their broad therapeutic potential. Here we systematically expand the CRBN neosubstrate landscape using a target-agnostic discovery approach. By integrating deep proteomic and ubiquitinomic profiling of a 960-compound library, we identify compound-induced ubiquitination and depletion of over 230 endogenous proteins. Among these, 124 represent previously unreported CRBN neosubstrates, with over half lacking a predicted G-loop degron. We provide this dataset via an interactive resource, NeosubstratesDB . Complementary cellular and biochemical assays mechanistically define the interaction domain of IRAK1 and establish G-loop-dependent degradation for BCL6. Interpretable machine learning (iML) integrating proteomic profiles with chemical structures highlights key molecular fingerprints driving neosubstrate selectivity for targets such as CSNK1A1, ZFP91 and WEE1. Together, these findings significantly expand the repertoire of CRBN neosubstrates and provide a framework for rational design of next-generation MGDs.