化学
选择性
效力
小脑
计算生物学
分子模型
组合化学
药物发现
药理学
立体化学
DNA连接酶
配体效率
分子药理学
三元络合物
小分子
结构-活动关系
配体(生物化学)
肽序列
血浆蛋白结合
药物开发
氨基酸
机制(生物学)
生物化学
药品
体外
泛素连接酶
作者
Guilian Luchini,Shuang Liu,Hannah L. Powers,Emily C. Cherney,J. Zhu,Kristina Danga,Joel W. Thompson,Lihong Shi,Barbra Pagarigan,Wei Dong,Peter J. Park,Andrew P. Degnan,Christoph W. Zapf,Jennifer R. Riggs,S.A. Johnson,Thomas J. Cummins
标识
DOI:10.1021/acs.jmedchem.5c01919
摘要
Cullin-RING Ligase 4 Cereblon (CRL4CRBN) (CRBN) E3 ligase modulatory drugs (CELMoDsTM) make up a successful class of compounds targeting neosubstrates for proteasome-dependent degradation. Early immunomodulatory drugs (IMiDsTM) target Ikaros and Aiolos degradation. In addition, there are ongoing clinical trials targeting the degradation of biologically relevant proteins such as GSPT1, CK1α, and Helios with CRBN-based molecular glues. To date, most advanced preclinical and clinical CRBN-based molecular glues recruit their neosubstrates through canonical G-motifs, secondary protein features that are structurally similar but have significantly different amino acid sequence identities. Analogous to the development of kinase inhibitors, optimizing both neosubstrate recruitment and degradation selectivity is important to minimize potential off-target activity. Here, we describe a computational structure-based approach to analyze and predict putative ligand interactions important in the neosubstrate ternary complex. This approach provides valuable insights for enhanced designs toward the development of more selective and efficacious CRBN-based molecular glues.
科研通智能强力驱动
Strongly Powered by AbleSci AI