Polycomb repressive complex 1 (PRC1) is an essential epigenetic regulator that mainly controls histone H2A Lys119 mono‐ubiquitination (H2AK119ub). B cell‐specific Moloney murine leukemia virus Integration site 1 (BMI1) and really interesting new gene 1B (RING1B) are PRC1 core components and play critical roles in the development of various cancers. However, therapeutic agents targeting PRC1 are very limited. In this study, MS147, the first degrader of PRC1 core components, BMI1 and RING1B, is discovered via a novel protein complex degradation strategy that utilizes the target protein's interacting partner protein (embryonic ectoderm development (EED)). MS147, which comprises an EED small‐molecule binder linked to a ligand of the E3 ligase von Hippel‐Lindau (VHL), degrades BMI1/RING1B in an EED‐, VHL‐, ubiquitination‐, and time‐dependent manner. MS147 preferentially degrades BMI1/RING1B over polycomb repressive complex 2 (PRC2) core components. Consequently, MS147 effectively reduces H2AK119ub, but not histone H3 Lys27 tri‐methylation (H3K27me3), which is catalyzed by PRC2. Furthermore, MS147 effectively inhibits the proliferation of cancer cell lines that are insensitive to PRC2 inhibitors/degraders. Overall, this study provides a novel BMI1/RING1B degrader, which is a useful chemical tool to further investigate the roles of PRC1 in cancer, and a novel protein complex degradation strategy, which can potentially expand the degradable human proteome.

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Inappropriate use of prescription drugs is potentially more harmful in fetuses/neonates than in adults. Cytochrome P450 (CYP) 3A subfamily undergoes developmental changes in expression, such as a transition from CYP3A7 to CYP3A4 shortly after birth, which provides a potential way to distinguish medication effects on fetuses/neonates and adults. The purpose of this study was to build first-in-class predictive models for both inhibitors and substrates of CYP3A7/CYP3A4 using chemical structure analysis. Three metrics were used to evaluate model performance: area under the receiver operating characteristic curve (AUC-ROC), balanced accuracy (BA), and Matthews correlation coefficient (MCC). The performance varied for each CYP3A7/CYP3A4 inhibitor/ substrate model depending on the data set type, model type, rebalancing method, and specific feature set. For the active inhibitor/ substrate data set, the optimal models achieved AUC-ROC values ranging from 0.77 ± 0.01 to 0.84 ± 0.01. For the selective inhibitor/substrate data set, the optimal models achieved AUC-ROC values ranging from 0.72 ± 0.02 to 0.79 ± 0.04. The predictive power of the optimal models was validated by compounds with known potencies as CYP3A7/CYP3A4 inhibitors or substrates. In addition, we identified structural features significant for CYP3A7/CYP3A4 selective or common inhibitors and substrates. In summary, the top performing models can be further applied as a tool to rapidly evaluate the safety and efficacy of new drugs separately for fetuses/neonates and adults. The significant structural features could guide the design of new therapeutic drugs as well as aid in the optimization of existing medicine for fetuses/neonates.