Evaluation of affinity sensor response kinetics towards dimeric ligands linked with spacers of different rigidity: Immobilized recombinant granulocyte colony-stimulating factor based synthetic receptor binding with genetically engineered dimeric analyte derivatives

Abstract

The modelling of protein-protein binding kinetics is important for the development of affinity-sensors and the prediction of signaling protein based drug efficiency. Therefore, in this research we have evaluated the binding kinetics of several genetically designed protein models: (i) three different ligands based on granulocyte colony-stimulating factor GCSF homo-dimeric derivatives linked by differed by linkers of different length and flexibility; (ii) an antibody-like receptor (GCSF-R) based on two GCSF-receptor sites immobilized to Fc domains, which are common parts of protein structures forming antibodies. Genetically engineered GCSF-R is similar to an antibody because it, like the antibody, has two binding sites, which both selectively bind with GCSF ligands. To design the affinity sensor model studied here, GCSF-R was immobilized on a thin gold layer via self-assembled monolayer conjugated with Protein-G. Binding kinetics between immobilized GCSF-R and all three different recombinant GCSF-based homo-dimeric derivatives were evaluated by total internal reflection ellipsometry. Association constants were determined by fitting mathematical models to the experimental data. It was clearly observed that both (i) affinity and (ii) binding kinetics depend on the length and flexibility of the linker that connects both domains of a GCSF-based ligand. The fastest association between immobilized GCSF-R and GCSF-based ligands was observed for ligands whose GCSF domains were interconnected by the longest and the most flexible linker. Here we present ellipsometry-based measurements and models of the interaction kinetics that advance the understanding of bidentate-receptor-based immunosensor action and enables us to predict the optimal linker structure for the design of GCSF-based medications.