Laboratory of Biomolecular Research, Villigen, Switzerland (F.M.H., A.R., D.M., D.B.V.); Department of Biology, Paul Scherrer Institute, Zürich, Switzerland (F.M.H., A.R., D.M., D.B.V.); Department of Biochemistry and Molecular Medicine, Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, Québec, Canada (F.M.H., B.P., J.Z., B.B., C.L., M.B.); MRC Laboratory of Molecular Biology, Cambridge, United Kingdom (F.M.H.); The Wellcome-Wolfson Institute for Experimental Medicine, School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, United Kingdom (B.P.); Department of Structural and Computational Biology, Max Perutz Laboratories, University of Vienna, Vienna, Austria (D.M.); Graduate School of Pharmaceutical Sciences, Tohoku University, Sendai, Japan (A.I.); Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham and University of Nottingham, Midlands, United Kingdom (D.B.V.); and Division of Physiology, Pharmacology and Neuroscience, School of Life Sciences, University of Nottingham, Nottingham, United Kingdom (D.B.V.)
Laboratory of Biomolecular Research, Villigen, Switzerland (F.M.H., A.R., D.M., D.B.V.); Department of Biology, Paul Scherrer Institute, Zürich, Switzerland (F.M.H., A.R., D.M., D.B.V.); Department of Biochemistry and Molecular Medicine, Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, Québec, Canada (F.M.H., B.P., J.Z., B.B., C.L., M.B.); MRC Laboratory of Molecular Biology, Cambridge, United Kingdom (F.M.H.); The Wellcome-Wolfson Institute for Experimental Medicine, School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, United Kingdom (B.P.); Department of Structural and Computational Biology, Max Perutz Laboratories, University of Vienna, Vienna, Austria (D.M.); Graduate School of Pharmaceutical Sciences, Tohoku University, Sendai, Japan (A.I.); Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham and University of Nottingham, Midlands, United Kingdom (D.B.V.); and Division of Physiology, Pharmacology and Neuroscience, School of Life Sciences, University of Nottingham, Nottingham, United Kingdom (D.B.V.).
Mol Pharmacol. 2022 Sep;102(3):139-149. doi: 10.1124/molpharm.122.000497. Epub 2022 Jul 2.
Activation of G protein-coupled receptors by agonists may result in the activation of one or more G proteins and recruitment of arrestins. The extent of the activation of each of these pathways depends on the intrinsic efficacy of the ligand. Quantification of intrinsic efficacy relative to a reference compound is essential for the development of novel compounds. In the operational model, changes in efficacy can be compensated by changes in the "functional" affinity, resulting in poorly defined values. To separate the effects of ligand affinity from the intrinsic activity of the receptor, we developed a Michaelis-Menten based quantification of G protein activation bias that uses experimentally measured ligand affinities and provides a single measure of ligand efficacy. We used it to evaluate the signaling of a promiscuous model receptor, the Vasopressin V2 receptor (V2R). Using BRET-based biosensors, we show that the V2R engages many different G proteins across all G protein subfamilies in response to its primary endogenous agonist, arginine vasopressin, including Gs and members of the Gi/o and G12/13 families. These signaling pathways are also activated by the synthetic peptide desmopressin, oxytocin, and the nonmammalian hormone vasotocin. We compared bias quantification using the operational model with Michaelis-Menten based quantification; the latter accurately quantified ligand efficacies despite large difference in ligand affinities. Together, these results showed that the V2R is promiscuous in its ability to engage several G proteins and that its' signaling profile is biased by small structural changes in the ligand. SIGNIFICANCE STATEMENT: By modelling the G protein activation as Michaelis-Menten reaction, we developed a novel way of quantifying signalling bias. V2R activates, or at least engages, G proteins from all G protein subfamilies, including Gi2, Gz, Gq, G12, and G13. Their relative activation may explain its Gs-independent signalling.
激动剂激活 G 蛋白偶联受体可能导致一种或多种 G 蛋白的激活和抑制蛋白的募集。这些途径的激活程度取决于配体的内在效力。相对于参考化合物，对内在效力进行定量对于新化合物的开发至关重要。在操作模型中，效力的变化可以通过“功能”亲和力的变化来补偿，从而导致定义不明确的值。为了将配体亲和力的影响与受体的内在活性分开，我们开发了一种基于米氏方程的 G 蛋白激活偏性定量方法，该方法使用实验测量的配体亲和力，并提供了配体效力的单一度量。我们使用它来评估一个混杂模型受体，即血管加压素 V2 受体（V2R）的信号转导。使用 BRET 基生物传感器，我们表明 V2R 在响应其主要内源性激动剂精氨酸加压素时，通过许多不同的 G 蛋白亚家族（包括 Gs 和 Gi/o 和 G12/13 家族的成员）来结合许多不同的 G 蛋白。这些信号通路也被合成肽去氨加压素、催产素和非哺乳动物激素血管升压素激活。我们比较了使用操作模型和基于米氏方程的定量方法的偏置定量；尽管配体亲和力存在很大差异，但后者准确地定量了配体效力。这些结果表明，V2R 在结合几种 G 蛋白的能力上具有混杂性，其信号谱受配体结构微小变化的影响而产生偏差。
通过将 G 蛋白激活建模为米氏方程反应，我们开发了一种新的定量信号转导偏性的方法。V2R 激活或至少与所有 G 蛋白亚家族（包括 Gi2、Gz、Gq、G12 和 G13）的 G 蛋白结合。它们的相对激活可能解释了其 Gs 非依赖性信号转导。
