Phan Ngan T N, Borrega-Roman Leire, Hoare Bradley L, Harwood Clare R, Geary Natalie, Guba Wolfgang, Han Yongqi, Zenko Vladimirs, Koers Eline J, Rufer Arne C, Grether Uwe, Veprintsev Dmitry B, Sykes David A
Division of Physiology, Pharmacology & Neuroscience, School of Life Sciences, University of Nottingham, Nottingham NG7 2UH, U.K.
Centre of Membrane Proteins and Receptors (COMPARE), University of Nottingham, Midlands, Nottingham NG7 2UH, U.K.
Biochemistry. 2025 Aug 19;64(16):3585-3598. doi: 10.1021/acs.biochem.5c00148. Epub 2025 Aug 7.
Drug discovery is a costly and time-intensive process that is often limited by efficacy issues and unforeseen side effects. GPCR-targeting ligands, which account for one-third of marketed drugs, have been shown to exhibit biased signaling and preferential activation of one signaling pathway over another. While designing biased ligands is a recent advancement, their therapeutic benefits remain uncertain. However, the success of existing drugs raises the following question: do they inherently exhibit signaling bias that enhances efficacy or safety? This study examines the signaling profiles of short- and long-acting βAR agonists (SABAs and LABAs), key treatments for asthma and COPD, using biosensors to measure G protein and β-arrestin coupling. Older SABAs, such as isoprenaline and isoetharine, show minor G protein bias, while newer agents, such as salbutamol, demonstrate significant G protein bias. Among LABAs, salmeterol shows greater G protein bias compared to that of the more balanced formoterol. This shift toward G protein bias over 50 years reflects efforts to improve asthma treatments. The increased bias results from reduced ligand-receptor residence times and weaker receptor-β-arrestin complex formation, contributing to the enhanced efficacy. Despite the potential advantages, a systematic evaluation of signaling bias remains underutilized in drug development. Early-stage, high-throughput tools to assess signaling profiles could improve candidate selection, reduce late-stage failures, and minimize side effects. We advocate for the routine integration of biosensors for quantifying signaling bias, optimizing compound selection, and enhancing therapeutic outcomes.
药物研发是一个成本高昂且耗时的过程,常常受到疗效问题和意外副作用的限制。占已上市药物三分之一的靶向G蛋白偶联受体(GPCR)的配体,已被证明会表现出偏向性信号传导,即优先激活一种信号通路而非另一种。虽然设计偏向性配体是一项近期的进展,但其治疗益处仍不明确。然而,现有药物的成功引发了以下问题:它们是否本质上就表现出能提高疗效或安全性的信号偏向性?本研究使用生物传感器来测量G蛋白和β-抑制蛋白的偶联,从而研究短效和长效β肾上腺素能受体激动剂(SABA和LABA)的信号传导特征,这两种药物是哮喘和慢性阻塞性肺疾病(COPD)的关键治疗药物。较老的SABA,如异丙肾上腺素和异他林,表现出轻微的G蛋白偏向性,而较新的药物,如沙丁胺醇,则表现出显著的G蛋白偏向性。在LABA中,与更为平衡的福莫特罗相比,沙美特罗表现出更大的G蛋白偏向性。50年来向G蛋白偏向性的这种转变反映了改善哮喘治疗的努力。偏向性增加是由于配体-受体停留时间缩短以及受体-β-抑制蛋白复合物形成减弱,从而提高了疗效。尽管有这些潜在优势,但在药物研发中,对信号偏向性的系统评估仍未得到充分利用。用于评估信号传导特征的早期高通量工具可以改善候选药物的选择,减少后期失败,并将副作用降至最低。我们主张常规整合生物传感器以量化信号偏向性、优化化合物选择并提高治疗效果。