Fan Angela T, Gadbois Gillian E, Huang Hai-Tsang, Chaudhry Charu, Jiang Jiewei, Sigua Logan H, Smith Emily R, Wu Sitong, Poirier Grace J, Dunne-Dombrink Kara, Goyal Pavitra, Tao Andrew J, Sellers William R, Fischer Eric S, Donovan Katherine A, Ferguson Fleur M
Department of Chemistry and Biochemistry, University of California, San Diego.
The Broad Institute of Harvard and MIT.
Angew Chem Int Ed Engl. 2025 Jan 27;64(5):e202417272. doi: 10.1002/anie.202417272. Epub 2024 Dec 16.
Bifunctional molecules such as targeted protein degraders induce proximity to promote gain-of-function pharmacology. These powerful approaches have gained broad traction across academia and the pharmaceutical industry, leading to an intensive focus on strategies that can accelerate their identification and optimization. We and others have previously used chemical proteomics to map degradable target space, and these datasets have been used to develop and train multiparameter models to extend degradability predictions across the proteome. In this study, we now turn our attention to develop generalizable chemistry strategies to accelerate the development of new bifunctional degraders. We implement lysine-targeted reversible-covalent chemistry to rationally tune the binding kinetics at the protein-of-interest across a set of 25 targets. We define an unbiased workflow consisting of global proteomics analysis, IP/MS of ternary complexes and the E-STUB assay, to mechanistically characterize the effects of ligand residence time on targeted protein degradation and formulate hypotheses about the rate-limiting step of degradation for each target. Our key finding is that target residence time is a major determinant of degrader activity, and this can be rapidly and rationally tuned through the synthesis of a minimal number of analogues to accelerate early degrader discovery and optimization.
双功能分子,如靶向蛋白降解剂,可诱导分子接近以促进功能获得药理学。这些强大的方法在学术界和制药行业得到了广泛应用,促使人们密集关注能够加速其识别和优化的策略。我们和其他人之前使用化学蛋白质组学来绘制可降解靶点空间,这些数据集已被用于开发和训练多参数模型,以扩展对整个蛋白质组的降解性预测。在本研究中,我们现在将注意力转向开发可推广的化学策略,以加速新型双功能降解剂的开发。我们实施赖氨酸靶向的可逆共价化学,以合理调节一组25个靶点上目标蛋白的结合动力学。我们定义了一个无偏工作流程,包括全局蛋白质组学分析、三元复合物的免疫沉淀/质谱分析和E-STUB分析,以从机制上表征配体驻留时间对靶向蛋白降解的影响,并针对每个靶点的降解限速步骤提出假设。我们的关键发现是,靶点驻留时间是降解剂活性的主要决定因素,并且可以通过合成最少数量的类似物来快速合理地调节,以加速早期降解剂的发现和优化。