Stott Lisa A, Hall David A, Holliday Nicholas D
Cell Signalling Research Group, School of Life Sciences, University of Nottingham, The Medical School, Queen's Medical Centre, Nottingham NG7 2UH, UK.
Fibrosis & Lung Injury DPU, RD Respiratory R&D, GlaxoSmithKline Medicines Research Centre, Gunnels Wood Road, Stevenage, Hertfordshire SG1 2NY, UK.
Biochem Pharmacol. 2016 Feb 1;101:1-12. doi: 10.1016/j.bcp.2015.10.011. Epub 2015 Oct 23.
Stephenson's empirical definition of an agonist, as a ligand with binding affinity and intrinsic efficacy (the ability to activate the receptor once bound), underpins classical receptor pharmacology. Quantifying intrinsic efficacy using functional concentration response relationships has always presented an experimental challenge. The requirement for realistic determination of efficacy is emphasised by recent developments in our understanding of G protein coupled receptor (GPCR) agonists, with recognition that some ligands stabilise different active conformations of the receptor, leading to pathway-selective, or biased agonism. Biased ligands have potential as therapeutics with improved selectivity and clinical efficacy, but there are also pitfalls to the identification of pathway selective effects. Here we explore the basics of concentration response curve analysis, beginning with the need to distinguish ligand bias from other influences of the functional system under study. We consider the different approaches that have been used to quantify and compare biased ligands, many of which are based on the Black and Leff operational model of agonism. Some of the practical issues that accompany these analyses are highlighted, with opportunities to improve estimates in future, particularly in the separation of true agonist intrinsic efficacy from the contributions of system dependent coupling efficiency. Such methods are by their nature practical approaches, and all rely on Stephenson's separation of affinity and efficacy parameters, which are interdependent at the mechanistic level. Nevertheless, operational analysis methods can be justified by mechanistic models of GPCR activation, and if used wisely are key elements to biased ligand identification.
斯蒂芬森对激动剂的经验性定义，即具有结合亲和力和内在活性（一旦结合就能激活受体的能力）的配体，是经典受体药理学的基础。利用功能浓度反应关系来量化内在活性一直是一个实验挑战。随着我们对G蛋白偶联受体（GPCR）激动剂认识的最新进展，强调了对活性进行实际测定的必要性，因为认识到一些配体可稳定受体的不同活性构象，从而导致途径选择性或偏向激动作用。偏向配体具有作为治疗药物提高选择性和临床疗效的潜力，但在识别途径选择性效应方面也存在陷阱。在这里，我们探讨浓度反应曲线分析的基础知识，首先需要区分配体偏向与所研究功能系统的其他影响。我们考虑了用于量化和比较偏向配体的不同方法，其中许多方法基于布莱克和莱夫的激动作用操作模型。强调了这些分析伴随的一些实际问题，以及未来改进估计的机会，特别是在将真正的激动剂内在活性与系统依赖性偶联效率的贡献区分开来方面。这些方法本质上都是实用方法，并且都依赖于斯蒂芬森对亲和力和活性参数的区分，而这两个参数在机制层面是相互依存的。然而，操作分析方法可以通过GPCR激活的机制模型来证明其合理性，并且如果明智地使用，是识别偏向配体的关键要素。
