ABSTRACT
This chapter demonstrates the advantages of the numerical integration approach using experimental data instead of simulated data. The introduction of surface plasmon resonance (SPR) technology has provided a new approach to studying macromolecular interactions between immobilised ligands and soluble analytes. Although several types of SPR-based biosensors are commercially available, the BIAcoreTM instrument is the most widely used. The BIAcore system applies SPR to detect the refractive index change that occurs as an analyte delivered through a flow cell interacts with a ligand that has been immobilised on a sensor chip surface. Non-optimised experimental conditions can lead to non-mechanistic effects that can cause BIAcore data curves to deviate from ones that can be fitted to a simple binding model. Complex reaction schemes often result in nonlinear differential equation sets that cannot be analytically integrated. It is then necessary to integrate them numerically and introduce the subroutine performing this integration into nonlinear parameter estimation algorithms.
