(564a) Kinetics of Binding and Dissociation of TNT in Aqueous Solution to Anti-TNP by a Highly Sensitive TNT Immunosensor

A fractal analysi is presented for the binding and dissocation of trinitrotoluene (TNT) in aquatic environments (Bromage et al., 2007) to biosensor surfaces. Binding and dissocation rate coefficients as well as the degree of heterogeneity present on the KinexA Inline biosensor surface are presented. The degree of heterogeneity present on the biosensor surface is made quantitative by the fractal dimension, Df value. An increase in the fractal dimension value leads to an increase in the Df value. Most chemicals will have a biological impact on aquatic species at concentrations too low to be visually observed (Anderson et al., 1997). Thus, the need of rapid detection and making quantitative trace contaminants of different chemicals. The authors focused on the detection of trace amounts of TNT in aqueous environments since environmental contamination occurs particularly from military sites due to manufacturing, storage, and handling of munitions. TNT is known to accumulate in plants and fish. Predictive relations are developed for the binding and the dissociation rate coefficients and for the fractal dimensions in the dissociation phase. For example, for the binding of TNT in aqueous solution to the anti-TNP antibody immobilized on a KinexA biosensor the binding rate coefficient, k for a single-fractal analysis exhibits close to a one-half (equal to 0.492) order of dependence on the fractal dimension, Df, and the dissociation rate coefficient, kd exhibits a 4.65 order of dependnce on the degree of heterogeneity that exists on the sensing surface. The predictive relationships analyzed and presented are of use since they may be used to manipulate the different biosensor parameters (such as the binding and dissociation rate coefficients) in desired directions. A particular advantage of the fractal analysis method is that it provides a quantitative measure of the degree of heterogeneity that exists on the biosensor surface. This provides one with an extra variable that biosensorists may use to help enhance or modify the different relevant biosensor parameters in desired directions. It behooves one to know as much as one can about the biosensor system being analyzed. The fractal analysis presented is one step in that direction.