The use of in silico models for the rationalization of molecularly imprinted polymer synthesis

Molecular dynamics simulations in pre-polymerization mixtures for peptide recognition

CONTEXT

Molecularly imprinted polymers (MIPs) have promising applications as synthetic antibodies for protein and peptide recognition. A critical aspect of MIP design is the selection of functional monomers and their adequate proportions to achieve materials with high recognition capacity toward their targets. To contribute to this goal, we calibrated a molecular dynamics protocol to reproduce the experimental trends in peptide recognition of 13 pre-polymerization mixtures reported in the literature for the peptide toxin melittin.

METHODS

Three simulation conditions were tested for each mixture by changing the box size and the number of monomers and cross-linkers surrounding the template in a solvent-explicit environment. Fully atomistic MD simulations of 350 ns were conducted with the AMBER20 software, with ff19SB parameters for the peptide, gaff2 parameters for the monomers and cross-linkers, and the OPC water model. Template-monomer interaction energies under the LIE approach showed significant differences between high-affinity and low-affinity mixtures. Simulation systems containing 100 monomers plus cross-linkers in a cubic box of 90 Å3 successfully ranked the mixtures according to their experimental performance. Systems with higher monomer densities resulted in non-specific intermolecular contacts that could not account for the experimental trends in melittin recognition. The mixture with the best recognition capacity showed preferential binding to the 13-26-α-helix, suggesting a relevant role for this segment in melittin imprinting and recognition. Our findings provide insightful information to assist the computational design of molecularly imprinted materials with a validated protocol that can be easily extended to other templates.

Development of a "turn off" fluorescent molecularly imprinted nanoparticle-based sensor for selective captopril quantification in synthetic urine and wastewater samples

The combination of silica nanoparticles with fluorescent molecularly imprinted polymers (Si-FMIPs) prepared by a one-pot sol-gel synthesis method to act as chemical sensors for the selective and sensitive determination of captopril is described. Several analytical parameters were optimized, including reagent ratio, solvent, concentration of Si-FMIP solutions, and contact time. Fourier-transform infrared spectroscopy (FT-IR), transmission electron microscopy (TEM), and the ninhydrin assay were used for characterization. The selectivity was evaluated against molecules belonging to other drug classes, such as fluoroquinolones, nonacid nonopioids, benzothiadiazine, alpha amino acids, and nitroimidazoles. Under optimized conditions, the Si-FMIP-based sensor exhibited a working range of 1-15 µM, with a limit of detection (LOD) of 0.7 µM, repeatability of 6.4% (n = 10), and suitable recovery values at three concentration levels (98.5% (1.5 µM), 99.9% (3.5 µM), and 99.2% (7.5 µM)) for wastewater samples. The sensor provided a working range of 0.5-15 µM for synthetic urine samples, with an LOD of 0.4 µM and a repeatability of 7.4% (n = 10) and recovery values of 93.7%, 92.9%, and 98.0% for 1.0 µM, 3.5 µM, and 10 µM, respectively. In conclusion, our single-vessel synthesis approach for Si-FMIPs proved to be highly effective for the selective determination of captopril in wastewater and synthetic urine samples.

In Silico Evaluation of Oligomeric Representations for Molecularly Imprinted Polymer Modeling Using a Biological Template

Molecularly imprinted polymers (MIPs) have significant relevance to analytical sensing due to their functionalized and template-specific structurally complementary cavities, providing increased sensibility and specificity for instrumental analyses, thereby enabling a wide variety of applications, especially for biological processes. Designing and developing MIPs entirely by experimental approaches are time-consuming and costly processes; thus, computational tools are used to assess some of the most critical parameters for imprinting, such as ligand screening. A typical practice is to model functional ligands as monomers; however, this representation fails to predict how ligand-template interactions evolve during polymer growth. In this context, this work aims to evaluate whether additional oligomeric representations affect the formation of noncovalent complexes between typical ligands and the P31 Asian lineage Zika virus epitope, using classical molecular dynamics. The ligands 2-vinylpyridine, 4-vinylaniline, acrylic acid, acrylamide, and 2-hidroxyethyl methacrylate were simulated as monomers, trimers, pentamers, and decamers, and their influence on the epitope structural conservation and ligand-template interactions were evaluated. Analyses of root-mean-square deviation, fluctuation, radius of gyration, pair correlation function, and number of hydrogen bonding-type interactions were conducted, showing the ligand chain size had an influence on the complex formation. However, this influence had no discernible pattern, exhibiting better performance in some cases while noninfluential in others. Of particular significance, in terms of epitope structural conservation, distinct oligomeric chains led to the selection of the distinct most interactive ligands. This observation raises important questions regarding the use of oligomeric chains in MIP simulations, thus prompting the need for further investigations of this subject.

A Novel Electrochemical Sensor Modified with a Computer-Simulative Magnetic Ion-Imprinted Membrane for Identification of Uranyl Ion

In this paper, a novel ion-imprinted electrochemical sensor modified with magnetic nanomaterial Fe₃O₄@SiO₂ was established for the high sensitivity and selectivity determination of UO₂²⁺ in the environment. Density functional theory (DFT) was employed to investigate the interaction between templates and binding ligands to screen out suitable functional binding ligand for the reasonable design of the ion imprinted sensors. The MIIP/MCPE (magnetic ion imprinted membrane/magnetic carbon paste electrode) modified with Fe₃O₄@SiO₂ exhibited a strong response current and high sensitivity toward uranyl ion comparison with the bare carbon paste electrodes. Meanwhile, the MCPE was fabricated simultaneously under the action of strong magnetic adsorption, and the ion imprinted membrane can be adsorbed stably on the electrode surface, handling the problem that the imprinted membrane was easy to fall off during the process of experimental determination and elution. Based on the uranyl ion imprinting network, differential pulse voltammetry (DPV) was adopted for the detection technology to realize the electrochemical reduction of uranyl ions, which improved the selectivity of the sensor. Thereafter, uranyl ions were detected in the linear concentration range of 1.0 × 10⁻⁹ mol L⁻¹ to 2.0 × 10⁻⁷ mol L⁻¹, with the detection and quantification limit of 1.08 × 10⁻⁹ and 3.23 × 10⁻¹⁰ mol L⁻¹, respectively. In addition, the sensor was successfully demonstrated for the determination of uranyl ions in uranium tailings soil samples and water samples with a recovery of 95% to 104%.