Department of Pharmacology, Faculty of Pharmacy, University of Debrecen, H-4012 Debrecen, PO Box 8, Hungary.
Can J Physiol Pharmacol. 2010 Nov;88(11):1074-83. doi: 10.1139/y10-089.
The receptorial responsiveness method (RRM) was proposed to estimate changes in the concentration of an agonist in the microenvironment of its receptor. Usually, this is done by providing the equieffective concentration of another agonist for the same receptor or for a largely overlapping postreceptorial signaling ("test agonist"). The RRM is a special nonlinear regression algorithm to analyze a concentration-response (E/c) curve that represents the simultaneous actions of a single agonist concentration to be estimated and of increasing concentrations of the test agonist. The aim of this study was to explore whether asymmetry of the E/c curve to be analyzed influences the reliability of the RRM. For this purpose, computer simulation was performed by constructing symmetric and asymmetric E/c curves using the operational model of agonism, and then these curves were analyzed with the RRM. To perform the RRM, 2 types of equations were used: one involving the Hill equation, the simplest model of the E/c relationship, and one containing the Richards equation, an advanced model properly handling E/c curve asymmetry. Results of this study indicate that E/c curve asymmetry does not significantly influence the accuracy of the estimates provided by the RRM. Thus, when using the RRM, it is not necessary to replace the Hill equation with the Richards equation to obtain useful estimates. Furthermore, it was found that estimation of a high concentration of a high-efficacy agonist can fail when the RRM is performed with a low-efficacy test agonist in a system characterized by a small operational slope factor.
受体反应性响应方法(RRM)被提议用于估计其受体的微环境中激动剂浓度的变化。通常,这是通过提供相同受体或大量重叠的受体后信号传导的等效有效浓度的另一种激动剂(“测试激动剂”)来完成的。RRM 是一种特殊的非线性回归算法,用于分析浓度反应(E/c)曲线,该曲线表示要估计的单一激动剂浓度的同时作用以及测试激动剂浓度的增加。本研究的目的是探讨要分析的 E/c 曲线的不对称性是否会影响 RRM 的可靠性。为此,使用激动作用的操作模型通过构建对称和不对称的 E/c 曲线进行计算机模拟,然后使用 RRM 对这些曲线进行分析。为了执行 RRM,使用了 2 种类型的方程:一种涉及 Hill 方程,这是 E/c 关系的最简单模型,另一种包含 Richards 方程,该方程是适当处理 E/c 曲线不对称性的高级模型。本研究的结果表明,E/c 曲线的不对称性不会显着影响 RRM 提供的估计值的准确性。因此,在使用 RRM 时,没有必要用 Richards 方程代替 Hill 方程来获得有用的估计值。此外,还发现当在以小操作斜率因子为特征的系统中用低效能测试激动剂进行 RRM 时,高效能的高浓度激动剂的估计可能会失败。