Characterizing Variations in Binding Kinetics of Affinity Biosensors: A Boundary-Layer and Site-Quality Approach

Affinity biosensors rely on biological recognition elements immobilized on a transducer surface to capture specific target analytes. Binding kinetics between target molecules and surface-immobilized receptors are commonly analyzed using the Langmuir interaction model, which assumes homogeneous binding sites with constant kinetic parameters. Here, we present a computational framework representing the evolution of apparent binding kinetics using a normalized coverage-dependent distribution function. The model assumes that binding at relatively low surface coverage is dominated by more accessible and favorably oriented receptor sites, followed by increasing contributions from heterogeneous binding environments as surface coverage increases. The kinetic formulation was coupled with fluid-flow and convection-diffusion modeling to account for mass transport and near-surface residual analyte concentration. The framework was evaluated using quartz crystal microbalance with dissipation measurements of IgG and C-reactive protein antibody-antigen interactions under varying experimental conditions. Quantitative assessment using normalized root-mean-square error (NRMSE) showed consistently improved agreement with the experimental measurements relative to the classical Langmuir model, with one benchmark comparison yielding an NRMSE below 1.5% for the proposed model compared with more than 4% for the classical model. The results demonstrate that incorporating coverage-dependent apparent kinetics improves the description of the investigated high-affinity binding responses and provides a phenomenological framework for characterizing heterogeneous surface binding. By providing a more detailed description of coverage-dependent binding behavior, the proposed framework has the potential to support the design and optimization of affinity biosensors under practical operating conditions.