Computer-Aided Design of Molecularly Imprinted Polymers for Simultaneous Detection of Clenbuterol and Its Metabolites

Polymers (Basel). 2018 Dec 23;11(1):17. doi: 10.3390/polym11010017.

Abstract

Molecular imprinting technology (MIT) offers an effective technique for efficient separation and enrichment of specific analytes from complicated matrices and has been used for illicit veterinary drug detectionin recent years due to its high selectivity, good chemical stability, and simple preparation. The development of in silico-based approaches has enabled the simulation of molecularly imprinted polymers (MIPs) to facilitate the selection of imprinting conditions such as template, functional monomer, and the best suitable solvent. In this work, using density functional theory (DFT), the molecularly imprinted polymers of clenbuterol and its metabolites were designed by computer-aided at B3LYP/6-31 + G (d, p) level. Screening molecular imprinting components such as functional monomers, cross-linkers, and solvents has been achieved in the computational simulation considerations. The simulation results showed that methacrylic acid (MAA) is the best functional monomer; the optimal imprinting ratio for both clenbuterol (CLB) and its dummy template molecule of phenylephrine (PE) to functional monomer is 1:3, while the optimal imprinting ratio for the two dummy template molecules of CLB's metabolites is 1:5. Choosin gethyleneglycol dimethacrylate (EDGMA) as a crosslinker and aprotic solvents could increase the selectivity of the molecularly imprinted system. Atoms in Molecules (AIM) topology analysis was applied to investigate the template-monomer complexes bonding situation and helped to explain the nature of the reaction in the imprinting process. These theoretical predictions were also verified by the experimental results and found to be in good agreement with the computational results. The computer-simulated imprinting process compensates for the lack of clarity in the mechanism of the molecular imprinting process, and provides an important reference and direction for developing better recognition pattern towards CLB and its metabolite analytes in swine urine samples at the same time.

Keywords: clenbuterol; computer simulations; density functional theory; metabolites; molecularly imprinted polymer.