Abstract

Although a comparatively robust method, immobilized protein-based techniques have displayed limited precision and inconsistent results due to a lack of strategy for the accurate selection of drug adsorption models on the protein surface. We generated the adsorption data of three drugs on immobilized beta-2-adrenoceptor (β2-AR) by frontal affinity chromatography-mass spectrometry (FAC-MS) and site-specific competitive FAC-MS. Using adsorption energy distribution (AED) calculations, we achieved the best adsorption models for the binding of salbutamol, terbutaline, and pseudoephedrine to immobilized β2-AR. The Langmuir model proved to be desirable for describing the adsorptions of salbutamol and terbutaline on immobilized β2-AR, while the bi-Langmuir model was favorable to characterize the adsorption of pseudoephedrine on the receptor. Relying on the accurate determination of association constants, we presented an efficient approach for β2-AR ligand screening based on the loss of breakthrough time of an indicator drug caused by the inclusion of competitive drugs in the mobile phase. We concluded that the current strategy enables the reliable and accurate analysis of G protein-coupled receptor (GPCR)-drug interaction. The percentage change in the breakthrough time for drugs can provide useful information for estimating their binding affinity to the receptor. This approach builds a powerful platform for high-throughput ligand screening.

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