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通过同时估算结合常数、免疫反应分数和特异性靶标上有效结合位点的数量来评估标记单克隆抗体。

Evaluation of labelled monoclonal antibodies by simultaneous estimation of the association constant, the immunoreactive fraction, and the number of effective binding sites on the specific target.

作者信息

Fjeld J G, Skretting A

机构信息

Central Laboratory, Norwegian Radium Hospital, Montebello, Oslo.

出版信息

J Immunol Methods. 1992 Jul 6;151(1-2):97-106. doi: 10.1016/0022-1759(92)90107-5.

Abstract

The reaction between a labelled monoclonal antibody (MoAb) and its specific target is characterised by three parameters: the association constant (Ka) of the labelled MoAb, the number (N) of effective binding sites on the specific target, and the immunoreactive fraction (F) of the labelled MoAb preparation. Immunological binding parameters are usually estimated graphically, by fitting the experimental data to linear equations derived from the first order law of mass action (FLMA) at equilibrium. However, only two parameters can be estimated simultaneously in a two-dimensional plot. Consequently, graphical estimation of Ka, F and N must be performed stepwise, using at least two different plots. The three parameters are interdependent, and therefore a stepwise estimation procedure might give suboptimal results. In order to investigate whether this is a problem of practical significance in the evaluation of labelled MoAbs, a computerised iterative nonlinear least squares (INLSQ) method was applied to estimate the three parameters simultaneously. The binding parameters in reactions between different 125I-labelled MoAbs and different types of targets were significantly changed when a graphical procedure was replaced by the computerised INLSQ method, and the goodness of fit to FLMA was improved. Hence, the nonlinear least squares method is the preferred procedure. Values were affected when only a subset of the data was included in the estimation procedure, indicating some heterogeneity even in these presumably homogeneous MoAb reactions. The radiolabelling procedure was presumed to be the main reason for this heterogeneity.

摘要

标记单克隆抗体(MoAb)与其特异性靶标的反应由三个参数表征:标记MoAb的结合常数(Ka)、特异性靶标上有效结合位点的数量(N)以及标记MoAb制剂的免疫反应分数(F)。免疫结合参数通常通过将实验数据拟合到平衡时质量作用一级定律(FLMA)推导的线性方程进行图形估计。然而,在二维图中只能同时估计两个参数。因此,必须使用至少两个不同的图逐步进行Ka、F和N的图形估计。这三个参数相互依赖,因此逐步估计程序可能会给出次优结果。为了研究在标记MoAb评估中这是否是一个具有实际意义的问题,应用了计算机化迭代非线性最小二乘法(INLSQ)来同时估计这三个参数。当用计算机化INLSQ方法取代图形程序时,不同125I标记的MoAb与不同类型靶标之间反应的结合参数发生了显著变化,并且对FLMA的拟合优度得到了改善。因此,非线性最小二乘法是首选程序。当估计程序中仅包含部分数据时,值会受到影响,这表明即使在这些可能均匀的MoAb反应中也存在一些异质性。放射性标记程序被认为是这种异质性的主要原因。

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