Computationally modelled receptors for drug monitoring using an optical based biomimetic SPR sensor

Molecularly imprinted polymers (MIPs) were designed using computational simulation for the synthesis of high affinity synthetic receptors to be used for drug recognition and detection in combination with optical based biosensors. The monomer library was screened for the target drug metoprolol based on binding energy between each monomer and the target for the selection of best monomers to develop a successful production recipe. Metoprolol-specific imprinted polymers were then produced using a solid phase synthesis method as nanoparticles. The quality and size of the produced receptors were characterized prior to the affinity testing through a surface plasmon resonance (SPR)-based optical biosensor. High quality synthetic receptors were obtained with the best monomer found using the molecular modelling program. The size of the receptors was found to be ∼169.4 nm ± 3.5 with polydispersity index of 0.3. The target specific receptor was then immobilized on the sensor surface via covalent coupling. Metoprolol which is a β-blocker drug was successfully detected in the range of 1.9 ng mL−1–1 μg mL−1 with correlation coefficient of 0.97. A regeneration method was developed for the sensor reuse and cross-reactivity studies were conducted using the control drugs. Kinetic data analysis was performed through SPR-2 and Biacore 3000 analysers to determine the affinity between the recognition element and metoprolol. The dissociation constant was found to be 1.35 × 10−10 M using Langmuir binding model. The size and quality of the synthetic receptor were periodically measured during six months to determine the stability. The size of the receptors was found nearly same (171.1 nm ± 5.4) and they still showed high activity for sensor assays. The receptor affinity and capacity towards metoprolol were also confirmed by solid phase extraction (SPE) method coupled with LC–MS. The achieved results highlight the success of computationally modelled receptor with SPR biosensor for pharmaceuticals detection and monitoring. The application of this work can be extended to the separation and detection of drugs from water samples, providing useful information and separation techniques for ecotoxicity studies.