McSwiggen David Trombley, Liu Helen, Tan Ruensern, Agramunt Puig Sebastia, Akella Lakshmi B, Berman Russell, Bretan Mason, Chen Hanzhe, Darzacq Xavier, Ford Kelsey, Godbey Ruth, Gonzalez Eric, Hanuka Adi, Heckert Alec, Ho Jaclyn J, Johnson Stephanie L, Kelso Reed, Klammer Aaron, Krishnamurthy Ruchira, Li Jifu, Lin Kevin, Margolin Brian, McNamara Patrick, Meyer Laurence, Pierce Sarah E, Sule Akshay, Stashko Connor, Tang Yangzhong, Anderson Daniel J, Beck Hilary P
Eikon Therapeutics Inc, Hayward, United States.
University of California, Berkeley, Berkeley, United States.
Elife. 2025 Jan 9;12:RP93183. doi: 10.7554/eLife.93183.
The regulation of cell physiology depends largely upon interactions of functionally distinct proteins and cellular components. These interactions may be transient or long-lived, but often affect protein motion. Measurement of protein dynamics within a cellular environment, particularly while perturbing protein function with small molecules, may enable dissection of key interactions and facilitate drug discovery; however, current approaches are limited by throughput with respect to data acquisition and analysis. As a result, studies using super-resolution imaging are typically drawing conclusions from tens of cells and a few experimental conditions tested. We addressed these limitations by developing a high-throughput single-molecule tracking (htSMT) platform for pharmacologic dissection of protein dynamics in living cells at an unprecedented scale (capable of imaging >10 cells/day and screening >10 compounds). We applied htSMT to measure the cellular dynamics of fluorescently tagged estrogen receptor (ER) and screened a diverse library to identify small molecules that perturbed ER function in real time. With this one experimental modality, we determined the potency, pathway selectivity, target engagement, and mechanism of action for identified hits. Kinetic htSMT experiments were capable of distinguishing between on-target and on-pathway modulators of ER signaling. Integrated pathway analysis recapitulated the network of known ER interaction partners and suggested potentially novel, kinase-mediated regulatory mechanisms. The sensitivity of htSMT revealed a new correlation between ER dynamics and the ability of ER antagonists to suppress cancer cell growth. Therefore, measuring protein motion at scale is a powerful method to investigate dynamic interactions among proteins and may facilitate the identification and characterization of novel therapeutics.
细胞生理学的调节很大程度上取决于功能不同的蛋白质和细胞成分之间的相互作用。这些相互作用可能是短暂的或长期的,但通常会影响蛋白质的运动。在细胞环境中测量蛋白质动力学,特别是在用小分子干扰蛋白质功能时,可能有助于剖析关键相互作用并促进药物发现;然而,目前的方法在数据采集和分析的通量方面存在限制。因此,使用超分辨率成像的研究通常是从几十个细胞和少数测试的实验条件中得出结论。我们通过开发一个高通量单分子追踪(htSMT)平台来解决这些限制,该平台以前所未有的规模对活细胞中的蛋白质动力学进行药理学剖析(能够每天成像>10个细胞并筛选>10种化合物)。我们应用htSMT来测量荧光标记的雌激素受体(ER)的细胞动力学,并筛选了一个多样化的文库以识别实时干扰ER功能的小分子。通过这一种实验方式,我们确定了所鉴定命中物的效力、途径选择性、靶点结合和作用机制。动力学htSMT实验能够区分ER信号的靶点调节剂和途径调节剂。综合途径分析概括了已知的ER相互作用伙伴网络,并提出了潜在的新型激酶介导的调节机制。htSMT的灵敏度揭示了ER动力学与ER拮抗剂抑制癌细胞生长能力之间的新关联。因此,大规模测量蛋白质运动是研究蛋白质之间动态相互作用的有力方法,可能有助于新型治疗药物的鉴定和表征。