细胞外结构域在GLP-1R偏性激动作用中的作用。

IF 2.8 3区 生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY
Linshan Xie , Rong Xu , Huining Liu , Man Na , Qikai Qin , Fei Xu , Raymond C. Stevens , Yan Liu
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引用次数: 0

摘要

胰高血糖素样肽-1受体(glucagon-like peptide-1 receptor, GLP-1R)的偏激作用在治疗2型糖尿病和肥胖症药物的疗效和副作用中起关键作用。尽管其具有治疗潜力,但GLP-1R偏向性激动作用的机制仍然知之甚少。在这项研究中,我们通过七个关键位点的饱和诱变研究了细胞外结构域(ECD)在GLP-1R信号偏置中的作用。我们检查了126个突变,并确定了几个选择性地取消β-阻滞蛋白募集而保留cAMP生产的突变。此外,我们采用大型语言模型(LLM)来解释这些突变的功能影响,揭示序列特征与信号转导结果之间的相关性。这些发现为B1类G蛋白偶联受体(gpcr)的“双域”模型提供了新的见解,突出了ECD在偏向性激动作用中的作用,并为设计更有效和选择性的GLP-1R激动剂提供了新的信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Characterizing the role of extracellular domain in GLP-1R biased agonism
The biased agonism of glucagon-like peptide-1 receptor (GLP-1R) plays a key role in the efficacy and side effects of drugs used to treat type II diabetes mellitus and obesity. Despite its therapeutic potential, the mechanisms underlying GLP-1R biased agonism remain poorly understood. In this study, we investigate the role of the extracellular domain (ECD) in GLP-1R signaling bias through saturation mutagenesis at seven key sites. We examined 126 mutations and identified several that selectively abolished β-arrestin recruitment while retaining cAMP production. Additionally, we employed a large language model (LLM) to interpret the functional impacts of these mutations, uncovering correlations between sequence features and signaling outcome. These findings provide new insight into the "two-domain" model of class B1 G protein-coupled receptors (GPCRs), highlighting the ECD's role in biased agonism and offering novel information for designing more effective and selective GLP-1R agonists.
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来源期刊
CiteScore
8.10
自引率
0.00%
发文量
124
审稿时长
19 days
期刊介绍: IJBCB publishes original research articles, invited reviews and in-focus articles in all areas of cell and molecular biology and biomedical research. Topics of interest include, but are not limited to: -Mechanistic studies of cells, cell organelles, sub-cellular molecular pathways and metabolism -Novel insights into disease pathogenesis -Nanotechnology with implication to biological and medical processes -Genomics and bioinformatics
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