Issue 6, 2020

Simulation of a phenobarbital molecularly imprinted polymerization self-assembly system and its adsorption property

Abstract

Using the density functional theory M062X/6-31G(d,p) method, a molecularly imprinted self-assembly system has been simulated with phenobarbital (PHN) as the imprinted molecule and 4-vinyl pyridine (4-VPY), acrylamide (AM), methacrylic acid (MAA), and itaconic acid (IA) as the functional monomers. The steric configuration, key cooperation binding site, imprinted ratio, and binding energy of the complex have been investigated to obtain the optimal functional monomer. The cross-linking agent was optimized by calculating its binding energy with PHN and IA. The theory of atoms in molecules was used to predict the molecular diagram and Laplace quantity contour map of the stable PHN–IA complex. The imprinting nature between PHN and IA was also discussed. Meanwhile, the selectivity property of PHN–IA stable complex was studied via barbiturate (BAR) and barbiturate acid (BA) as structural analogues. The results showed that, among the four functional monomers, IA is most suitable to form the complex with PHN through hydrogen bond interaction. When the molar ratio between PHN and IA was 1 : 7 and TRIM was the cross-linking agent, the formed complex had the lowest energy and best selectivity to PHN. The maximum apparent adsorption of PHN molecular imprinted polymer (PHN-MIPs) was 16.02 mg g−1 and the maximum dissociation equilibrium constant was 94.97 mg L−1. The selective identification of PHN-MIPs for PHN is higher than for BAR.

Graphical abstract: Simulation of a phenobarbital molecularly imprinted polymerization self-assembly system and its adsorption property

Supplementary files

Article information

Article type
Paper
Submitted
26 Nov 2019
Accepted
14 Jan 2020
First published
29 Jan 2020

Anal. Methods, 2020,12, 813-821

Simulation of a phenobarbital molecularly imprinted polymerization self-assembly system and its adsorption property

J. Liu, W. Zhao, G. Wang, S. Tang and R. Jin, Anal. Methods, 2020, 12, 813 DOI: 10.1039/C9AY02539A

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