Larsson A
University of Stockholm, Department of Immunology, Sweden.
Mol Immunol. 1988 Dec;25(12):1239-49. doi: 10.1016/0161-5890(88)90038-7.
Different possibilities of modelling equilibrium data on polyclonal antibody binding of ligand were investigated. The binding curves of the exact polyclonal model, based upon the mass-action law, and the Sips' model were compared. The basic assumption was that the free energy of binding is distributed according to the Gauss normal distribution. Using a few equations, the values of binding site concns and affinity constants of the individual clones were converted to the parameters of Sips' equation (that is, A = Ab binding site concn, K0 = average affinity, Hi = heterogeneity index). It was demonstrated that the binding curves from the exact polyclonal and the Sips' equations were very similar for simulated, approximately normally distributed antibody populations. Even when only two or three Ab-clones are involved, the Sips' and the exact polyclonal binding curves are very similar as long as the ratio between affinity constants does not exceed 10. Equilibrium data plotted as bound ligand concn on a linear scale vs free ligand concn on a logarithmic scale (or alternatively after logarithmic transformation of free ligand concn) form the well known sigmoid saturation curve. A mathematical relationship was demonstrated between half-height slope of such curves, resulting from approximately normally distributed antibody populations, and parameters of Sips' equation. The half-height slope is Hi X A/4 when natural logarithms are used. The ideas described were illustrated by weighted nonlinear curve-fittings applied to actual equilibrium data on anti-DNP antibodies. Tested in this way, the Sips' and a 2-clonal model gave equally good fit but somewhat different average affinities. It was concluded that it is often impossible to distinguish between a 2-clonal, a 3-clonal or an approximately normally distributed antibody population by curve-fitting to experimental equilibrium data.
研究了多克隆抗体与配体结合平衡数据建模的不同可能性。比较了基于质量作用定律的精确多克隆模型和西普斯模型的结合曲线。基本假设是结合自由能根据高斯正态分布进行分布。通过几个方程,将各个克隆的结合位点浓度值和亲和常数转换为西普斯方程的参数(即,A = 抗体结合位点浓度,K0 = 平均亲和力,Hi = 异质性指数)。结果表明,对于模拟的、近似正态分布的抗体群体,精确多克隆方程和西普斯方程的结合曲线非常相似。即使只涉及两三个抗体克隆,只要亲和常数之间的比值不超过10,西普斯模型和精确多克隆结合曲线也非常相似。以线性尺度绘制结合配体浓度与以对数尺度绘制的游离配体浓度(或者在游离配体浓度进行对数转换之后)的平衡数据形成了众所周知的S形饱和曲线。证明了由近似正态分布的抗体群体产生的此类曲线的半高斜率与西普斯方程的参数之间存在数学关系。当使用自然对数时,半高斜率为Hi×A/4。通过应用于抗DNP抗体实际平衡数据的加权非线性曲线拟合说明了上述观点。以这种方式进行测试,西普斯模型和双克隆模型拟合效果同样良好,但平均亲和力略有不同。得出的结论是,通过对实验平衡数据进行曲线拟合,通常无法区分双克隆、三克隆或近似正态分布的抗体群体。