Ding Baoli, Hu Jiawen, Zhang Rongtian, Shou Binyan, Chen Mengdie, Jiang Li, Yuan Meng, Yang Bo, He Qiaojun, Cao Ji, Zhu Cheng-Liang
Institute of Pharmacology & Toxicology, Zhejiang Province Key Laboratory of Anti-Cancer Drug Research, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, P.R. China.
Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Hangzhou, 310018, P.R. China.
Angew Chem Int Ed Engl. 2025 Jul 28;64(31):e202424118. doi: 10.1002/anie.202424118. Epub 2025 Jun 4.
Phenotypic screening offers an effective path for discovering protein degraders, particularly targeting proteins that are poorly characterized or lack sufficient ligand-binding information. Nonetheless, phenotypic protein degrader discovery (PPDD) faces practical hurdles, such as synthetic complexity in generating chemically diverse libraries and difficulties in reliably identifying degradation-driven phenotypes in direct-to-biology (D2B) assays. In response to these challenges, we developed an integrated PPDD platform that combines optimized solid-phase parallel synthesis with a robust D2B screening workflow. Leveraging photocleavable linkers and versatile synthetic strategies, this platform facilitates rapid generation of chemically diverse, ready-to-screen bifunctional molecule libraries requiring minimal purification. As a proof of concept, we synthesized and phenotypically screened 130 cereblon-recruiting molecules, leading to several promising protein degradation-dependent hits. Subsequent hit optimization and target identification validated compound 12-60 as a structurally novel GSPT1 degrader with compelling cellular activity. Overall, our integrated platform represents an efficient and practical toolkit for PPDD, establishing a versatile foundation to accelerate future campaigns and expand the degradable proteome.