Pliska V
Department of Animal Science, Swiss Federal Institute of Technology, Zurich, Switzerland.
J Recept Signal Transduct Res. 1995 Jan-Mar;15(1-4):651-75. doi: 10.3109/10799899509045247.
This paper reviews present models and methods of parameter estimation in relationships describing receptor-ligand interactions in equilibrium, as used in the author's laboratory. The state-of-the-art and the present experience can be summarized as follows: 1) Binding isotherms (relationships of bound and free/total ligand concentrations) are superpositions of several elementary terms describing the ligand binding to individual binding sites (receptors) present in the biological material investigated. The "nonspecific binding" is usually represented by a linear term. 2) The elementary terms are most frequently described by a rectangular hyperbola, Hill (power) function, or a rational function (binding of several ligand molecules to one molecule of receptor). Heterologous displacement requires specific functions which, however, can be transformed into one of the elementary terms. 3) Parameters (binding capacities, dissociation constants, Hill coefficients, etc.) can most reliably be estimated by nonlinear regression methods. However, these methods frequently fail to yield physically relevant values if initial estimates are far from "real" values, or if the data are strongly scattered. Some of the available routines (e.g., LIGAND) offer manifold tools to solve these difficulties. 4) The "affinity spectrum", a relationship between binding capacities and equilibrium constants, shows the presence of individual binding sites in the binding system in question. The spectrum can be constructed either by Fourier analysis, or by a stepwise procedure (computation of binding capacity for several dissociation constants). The former way of analysis is demanding; software tools are rare. 5) The "STEP" routine based on Hill/Scatchard linearization routines yields profiles similar to affinity spectra, but offers, in addition, values of Hill coefficients of individual binding populations. Values obtained can be used as initial estimates for nonlinear regression. 6) Selection of a suitable model, its testing, numerical procedures, statistical estimates, etc. frequently entail severe difficulties which are approached in the available software packages in different ways, none of them is usually optimal.
本文回顾了作者实验室中用于描述平衡状态下受体 - 配体相互作用关系的参数估计的现有模型和方法。目前的技术水平和经验可总结如下：1）结合等温线（结合配体与游离/总配体浓度的关系）是描述配体与所研究生物材料中存在的各个结合位点（受体）结合的几个基本项的叠加。“非特异性结合”通常由一个线性项表示。2）基本项最常由矩形双曲线、希尔（幂）函数或有理函数（几个配体分子与一个受体分子的结合）来描述。异源置换需要特定函数，不过这些函数可转化为基本项之一。3）参数（结合容量、解离常数、希尔系数等）最可靠地通过非线性回归方法进行估计。然而，如果初始估计值远离“真实”值，或者数据高度分散，这些方法常常无法得出符合实际情况的值。一些可用的程序（例如LIGAND）提供了多种工具来解决这些困难。4）“亲和力谱”，即结合容量与平衡常数之间的关系，表明所讨论的结合系统中存在各个结合位点。该谱可以通过傅里叶分析或逐步程序（计算几个解离常数下的结合容量）构建。前一种分析方法要求较高；软件工具很少。5）基于希尔/斯卡查德线性化程序的“STEP”程序产生的图谱类似于亲和力谱，但此外还提供各个结合群体的希尔系数值。获得的值可用作非线性回归的初始估计值。6）选择合适的模型、对其进行测试、数值程序、统计估计等常常会带来严重困难，现有软件包以不同方式处理这些困难，但通常都不是最优的。
