Optimization of enrofloxacin-imprinted polymers by computer-aided design

Area of Science:

• Materials Science
• Computational Chemistry
• Polymer Chemistry

Background:

• Molecularly imprinted polymers (MIPs) are crucial for selective molecular recognition.
• Optimizing MIPs for specific templates like enrofloxacin (ENRO) is essential for analytical applications.
• Computational and combinatorial approaches offer efficient screening of MIP systems.

Purpose of the Study:

• To computationally screen and experimentally validate optimal functional monomers and molar ratios for enrofloxacin (ENRO)-imprinted MIPs.
• To investigate the imprinting mechanism and binding characteristics using theoretical calculations.
• To determine the best monomer and imprinting ratio for enhanced adsorption of ENRO.

Main Methods:

• Density Functional Theory (DFT) calculations (B3LYP/6-31G(d,p)) to optimize MIP geometries and binding energies.
• Simulation of hydrogen nuclear magnetic resonance ((1)H NMR) spectra to elucidate the imprinting mechanism.
• Experimental preparation of MIPs using identified optimal template-to-monomer ratios.
• Adsorption experiments to evaluate the binding affinity and capacity of the prepared MIPs.

Main Results:

• DFT calculations identified trifluoromethacrylic acid (TFMAA) and ENRO at a 1:7 molar ratio as having the strongest interactions and lowest binding energy.
• Simulated (1)H NMR spectra supported the theoretical binding model.
• Experimental adsorption studies confirmed TFMAA as the optimal monomer, achieving a saturated adsorption capacity of 30.25 mg/g for ENRO.
• The study successfully determined the optimal monomer and imprinting ratio for ENRO-MIPs.

Conclusions:

• Trifluoromethacrylic acid (TFMAA) is the most effective functional monomer for creating enrofloxacin (ENRO)-imprinted MIPs.
• A 1:7 molar ratio of ENRO to TFMAA is optimal for maximizing binding affinity and imprinting efficiency.
• Computational modeling accurately predicts MIP performance, guiding experimental design for enhanced molecular recognition systems.