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A fractal analysis, which takes into account, the effect of surface heterogeneity brought about by ligand immobilization on the reaction kinetics in surface plasmon resonance (SPR) biosensors is presented. The binding and dissociation of estrogen receptors, ER∀ and ER∃ in solution to different ligands immobilized on the SPR biosensor is analyzed within the fractal framework. The heterogeneity on the biosensor surface is made quantitative by using a single number, the fractal dimension, Df. The analysis provides physical insights into the binding of these receptors to different ligands and compounds, particularly the EDCs (endocrine disrupting compounds). These EDCs have deleterious effects on humans and on wildlife. Single-and dualfractal models were employed to fit the ER binding data obtained from the literature. Values of the binding and dissociation rate coefficient and fractal dimensions were obtained from a regression analysis provided by Corel Quattro Pro, 8.0. Values for the affinity, KD (= k d /k a) were also calculated. This provides us with some extra flexibility in designing biomolecular assays. The analysis should provide further information on the mode of action and interaction of EDCs with the ERs. This would help in the design of agents and modulators against these EDCs. The treatment is of a general enough nature, and should also be applicable to non biosensor applications wherein further physical insights could be obtained. It has been applied to model DNA-Hybridization, Cell-Receptor, SPR biosensor, Antigen-Antibody reactions, etc. More such studies are required to determine whether the binding and the dissociation rate coefficient are influenced by the degree of heterogeneity or roughness existing on the biosensor and other reaction surfaces. If this is correct, then experimentalists may find it worth their effort to pay a little more attention to the nature of the biosensor surface, and how it may be manipulated, for example by (i) changing the nature of the chip or the matrix, (ii) coupling homogeneous ligands or linkers, (iii) controlling immobilization density etc. to manipulate biosensor performance characteristics and to improve biosensor speed, sensitivity, response time, and robustness. Clinical efficacy of monoclonal antibodies against SPan-1 antigen of human pancreatic carcinoma
A fractal analysis, which takes into account, the effect of surface heterogeneity brought about by ligand immobilization on the reaction kinetics in surface plasmon resonance (SPR) biosensors is presented. The binding and dissociation of estrogen receptors, ER∀ and ER∃ in solution to different ligands immobilized on the SPR biosensor is analyzed within the fractal framework. The heterogeneity on the biosensor surface is made quantitative by using a single number, the fractal dimension, Df. The analysis provides physical insights into the binding of these receptors to different ligands and compounds, particularly the EDCs (endocrine disrupting compounds). These EDCs have deleterious effects on humans and on wildlife. Single-and dualfractal models were employed to fit the ER binding data obtained from the literature. Values of the binding and dissociation rate coefficient and fractal dimensions were obtained from a regression analysis provided by Corel Quattro Pro, 8.0. Values for the affinity, KD (= k d /k a) were also calculated. This provides us with some extra flexibility in designing biomolecular assays. The analysis should provide further information on the mode of action and interaction of EDCs with the ERs. This would help in the design of agents and modulators against these EDCs. The treatment is of a general enough nature, and should also be applicable to non biosensor applications wherein further physical insights could be obtained. It has been applied to model DNA-Hybridization, Cell-Receptor, SPR biosensor, Antigen-Antibody reactions, etc. More such studies are required to determine whether the binding and the dissociation rate coefficient are influenced by the degree of heterogeneity or roughness existing on the biosensor and other reaction surfaces. If this is correct, then experimentalists may find it worth their effort to pay a little more attention to the nature of the biosensor surface, and how it may be manipulated, for example by (i) changing the nature of the chip or the matrix, (ii) coupling homogeneous ligands or linkers, (iii) controlling immobilization density etc. to manipulate biosensor performance characteristics and to improve biosensor speed, sensitivity, response time, and robustness. Clinical efficacy of monoclonal antibodies against SPan-1 antigen of human pancreatic carcinoma
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