Ramakrishnan A, Sadana A
Chemical Engineering Department, University of Mississippi, University 38677-9740, USA.
Appl Biochem Biotechnol. 1999 Sep;81(3):161-79. doi: 10.1385/abab:81:3:161.
A fractal analysis is presented for analyte-receptor binding kinetics for different types of biosensor applications. Data taken from the literature may be modeled using a single-fractal analysis, a single- and a dual-fractal analysis, or a dual-fractal analysis. The latter two methods represent a change in the binding mechanism as the reaction progresses on the surface. Predictive relationships developed for the binding rate coefficient as a function of the analyte concentration are of particular value since they provide a means by which the binding rate coefficients may be manipulated. Relationships are presented for the binding rate coefficients as a function of the fractal dimension Df or the degree of heterogeneity that exists on the surface. When analyte-receptor binding is involved, an increase in the heterogeneity on the surface (increase in Df) leads to an increase in the binding rate coefficient. It is suggested that an increase in the degree of heterogeneity on the surface leads to an increase in the turbulence on the surface owing to the irregularities on the surface. This turbulence promotes mixing, minimizes diffusional limitations, and leads subsequently to an increase in the binding rate coefficient. The binding rate coefficient is rather sensitive to the degree of heterogeneity, Df, that exists on the biosensor surface. For example, the order of dependence on Df1 is 7.25 for the binding rate coefficient k1 for the binding of a Fab fragment of an antiparaquat monoclonal antibody in solution to an antigen in the form of a paraquat analog immobilized on a sensor surface. The predictive relationships presented for the binding rate coefficient and the fractal dimension as a function of the analyte concentration in solution provide further physical insights into the binding reactions on the surface, and should assist in enhancing biosensor performance. In general, the technique is applicable to other reactions occurring on different types of surfaces, such as cell-surface reactions.
本文针对不同类型生物传感器应用中的分析物 - 受体结合动力学进行了分形分析。从文献中获取的数据可以用单分形分析、单分形和双分形分析或双分形分析进行建模。后两种方法代表了随着反应在表面上进行，结合机制的变化。针对结合速率系数作为分析物浓度的函数所建立的预测关系具有特别的价值，因为它们提供了一种可以操控结合速率系数的方法。给出了结合速率系数作为分形维数Df或表面存在的非均一性程度的函数的关系。当涉及分析物 - 受体结合时，表面非均一性的增加（Df增加）会导致结合速率系数增加。有人认为，表面非均一性程度的增加会由于表面的不规则性而导致表面湍流增加。这种湍流促进混合，最小化扩散限制，并随后导致结合速率系数增加。结合速率系数对生物传感器表面存在的非均一性程度Df相当敏感。例如，对于固定在传感器表面的百草枯类似物形式的抗原，溶液中抗百草枯单克隆抗体的Fab片段与之结合的结合速率系数k1对Df1的依赖顺序为7.25。针对结合速率系数和分形维数作为溶液中分析物浓度的函数所呈现的预测关系，为表面上的结合反应提供了进一步的物理见解，并应有助于提高生物传感器的性能。一般来说，该技术适用于发生在不同类型表面上的其他反应，如细胞表面反应。
