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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.

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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.

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Agricultural products are vitally important for sustaining life on earth and their production has notably grown over the years worldwide in general and in Brazil particularly. Elevating agricultural practices consequently leads to a proportionate increase in the usage of pesticides that are crucially important for enhanced crop yield and protection. These compounds have been employed excessively in alarming concentrations, causing the contamination of soil, water, and air. Additionally, they pose serious threats to human health. The current study introduces an innovative tool for producing appropriate materials coupled with an electrochemical sensor designed to measure carbendazim levels. The sensor is developed using a molecularly imprinted polymer (MIP) mounted on a glassy carbon electrode. This electrode is equipped with multi-walled carbon nanotubes (MWCNTs) for improved performance. The combined system demonstrates promising potential for accurately quantifying carbendazim. The morphological characteristics of the synthesized materials were investigated using field emission scanning electron microscopy (FESEM) and the Fourier-transform infrared (FTIR) technique. The analytical curve was drawn using the electrochemical method in the range of 2 to 20 ppm while for HPLC 2-12 ppm; the results are presented as the maximum adsorption capacity of the MIP (82.4%) when compared with NIP (41%) using the HPLC method. The analysis conducted using differential pulse voltammetry (DPV) yielded a limit of detection (LOD) of 1.0 ppm and a repeatability of 5.08% (n = 10). The results obtained from the analysis of selectivity demonstrated that the proposed electrochemical sensor is remarkably efficient for the quantitative assessment of carbendazim, even in the presence of another interferent. The sensor was successfully tested for river water samples for carbendazim detection, and recovery rates ranging from 94 to 101% were obtained for HPLC and 94 to 104% for the electrochemical method. The results obtained show that the proposed electrochemical technique is viable for the application and quantitative determination of carbendazim in any medium.

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An ultrafast, efficient, and eco-friendly method combining magnetic solid phase extraction and capillary electrophoresis with diode array detection have been developed to determine ractopamine residues in food samples. A restricted access material based on magnetic and mesoporous molecularly imprinted polymer has been properly synthesized and characterized, demonstrating excellent selectivity and high adsorbent capacity. Short-end injection capillary electrophoresis method was optimized: 75 mM triethylamine pH 7 as BGE, -20 kV, 50 mbar by hydrodynamic injection during 8 s, and capillary temperature at 25 °C; reaching ultrafast ractopamine analysis (∼0.6 min) with good peak asymmetry, and free from interfering and/or baseline noise. After sample preparation optimization, the conditions were: 1000 µL of sample at pH 6, 20 mg of adsorbent, stirring time of 120 s, 250 µL of ultrapure water as washing solvent, 1000 µL of methanol: acetic acid (7: 3, v/v) as eluent, and the adsorbent can be reused four times. In these conditions, the analytical method showed recoveries around to 100 %, linearity ranged from 9.74 to 974.0 µg kg-1, correlation coefficient (r) ≥ 0,99 in addition to adequate precision, accuracy, and robustness. After proper validation, the method was successfully applied in the analysis ractopamine residues in bovine milk and bovine and porcine muscle.

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This study proposes a new alternative for template removal from molecularly imprinted polymers by heat activated persulfate. It is known that trace amounts of template molecule remains in the polymer network after extraction by current methodologies leading to bleeding and incomplete removal of template which could compromise final determination of target analytes especially in trace analysis. A previously developed molecularly imprinted polymer specially designed for Coenzyme Q10 (CoQ10) extraction was employed as a model to test this template elimination approach. This polymer is based on methacrylic acid and ethylene glycol dimethylacrylate as monomers and Coenzyme Q0 as template. This coenzyme has the same quinone group as the CoQ10. Selectivity was analyzed comparing the recovery of CoQ10 and ubichromenol, a CoQ10 related substance. Chemical degradation using heat-activated persulfate allows the elimination of the template molecule with a high level of efficiency, being a simple and ecological methodology, yielding a polymer that exhibits comparable selectivity and imprinting effect with respect to traditional extraction methods.

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Curcumin is a compound of great importance in the food industry due to its biological and pharmacological properties, which include being an antioxidant, anti-inflammatory, antibacterial, antiviral, and anticarcinogenic. This paper proposes the synthesis of an electrochemical sensor based on molecularly imprinted polymers (MIPs) and MWCNT by drop casting deposited on a glassy carbon electrode (GCE) for the selective quantification of curcumin in food samples. The synthesized compounds are characterized by Fourier transform infrared (IR), Brunauer-Emmett-Teller (BET), and electrochemical techniques such as cyclic voltammetry (CV) and differential pulse voltammetry (DPV). The optimal conditions for further experiments were determined by selecting these parameters. We examined three food products, commercial capsules, turmeric rhizomes, and commercial turmeric powder, employing both electrochemical and HPLC methods for the analysis. The electrochemical method revealed a limit of detection (LOD) value of 0.1365 µmol L-1, compared with the HPLC analysis, which gave a value of 3.55 µmol L-1. Furthermore, the MIP material demonstrated superior selectivity for the analyte compared to potential interferents. The recovery percentage, determined using the HPLC method, fell within the range of 87.5% to 102.6.

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The aim of this study was the molecular imprinting polymers (MIPs) assessment as a controlled release system of ciprofloxacin. The MIPs synthesis was performed by three different methods: emulsion, bulk, and co-precipitation. Lactic acid (LA) and methacrylic acid (MA) were used as functional monomers and ethylene glycol dimethacrylate as crosslinker. Also, nonimprinted polymers (NIPs) were synthesized. MIPs and NIPs were characterized by scanning electron microscopy, Fourier Transform Infrared Reflection, specific surface area, pore size, and release kinetics. Their efficiency against Staphylococcus aureus and Escherichia coli, and their cytotoxicity in dermal fibroblast cells were proven. Results show that MIPs are mesoporous materials with a pore size between 10 and 20 nm. A higher adsorption with the co-precipitation MIP with MA as a monomer was found. The release kinetics proved that a non-Fickian process occurred and that the co-precipitation MIP with LA presented the highest release rate (90.51 mg/L) in 8 h. The minimum inhibitory concentration was found between 0.031 and 0.016 mg/L for Staphylococcus aureus and between 0.004 and 0.031 mg/L for the Escherichia coli. No cytotoxicity in cellular cultures was found; also, cellular growth was favored. This study demonstrated that MIPs present promising properties for drug administration and their application in clinical practice.

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Small-molecule analyte detection is key for improving quality of life, particularly in health monitoring through the early detection of diseases. However, detecting specific markers in complex multicomponent media using devices compatible with point-of-care (PoC) technologies is still a major challenge. Here, we introduce a novel approach that combines molecularly imprinted polymers (MIPs), electrolyte-gated transistors (EGTs) based on 2D materials, and machine learning (ML) to detect hippuric acid (HA) in artificial urine, being a critical marker for toluene intoxication, parasitic infections, and kidney and bowel inflammation. Reduced graphene oxide (rGO) was used as the sensory material and molecularly imprinted polymer (MIP) as supramolecular receptors. Employing supervised ML techniques based on symbolic regression and compressive sensing enabled us to comprehensively analyze the EGT transfer curves, eliminating the need for arbitrary signal selection and allowing a multivariate analysis during HA detection. The resulting device displayed simultaneously low operating voltages (<0.5 V), rapid response times (≤10 s), operation across a wide range of HA concentrations (from 0.05 to 200 nmol L-1), and a low limit of detection (LoD) of 39 pmol L-1. Thanks to the ML multivariate analysis, we achieved a 2.5-fold increase in the device sensitivity (1.007 µA/nmol L-1) with respect to the human data analysis (0.388 µA/nmol L-1). Our method represents a major advance in PoC technologies, by enabling the accurate determination of small-molecule markers in complex media via the combination of ML analysis, supramolecular analyte recognition, and electrolytic transistors.

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The present study reports the development and application of a rapid, low-cost in-situ method for the quantification of tartrazine in carbonated beverages using a smartphone-based colorimetric device with molecularly imprinted polymer (MIP). The MIP was synthesized using the free radical precipitation method with acrylamide (AC) as the functional monomer, N,N'-methylenebisacrylamide (NMBA) as the cross linker, and potassium persulfate (KPS) as radical initiator. The smartphone (RadesPhone)-operated rapid analysis device proposed in this study has dimensions of 10 × 10 × 15 cm and is illuminated internally by light emitting diode (LED) lights with intensity of 170 lux. The analytical methodology involved the use of a smartphone camera to capture images of MIP at various tartrazine concentrations, and the subsequent application of the Image-J software to calculate the red, green, blue (RGB) color values and hue, saturation, value (HSV) values from these images. A multivariate calibration analysis of tartrazine in the range of 0 to 30 mg/L was performed, and the optimum working range was determined to be 0 to 20 mg/L using five principal components and a limit of detection (LOD) of 1.2 mg/L was obtained. Repeatability analysis of tartrazine solutions with concentrations of 4, 8, and 15 mg/L (n = 10) showed a coefficient of variation (% RSD) of less than 6%. The proposed technique was applied to the analysis of five Peruvian soda drinks and the results were compared with the UHPLC reference method. The proposed technique showed a relative error between 6% and 16% and % RSD lower than 6.3%. The results of this study demonstrate that the smartphone-based device is a suitable analytical tool that offers an on-site, cost-effective, and rapid alternative for the quantification of tartrazine in soda drinks. This color analysis device can be used in other molecularly imprinted polymer systems and offers a wide range of possibilities for the detection and quantification of compounds in various industrial and environmental matrices that generate a color change in the MIP matrix.

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This paper demonstrates that determining adsorption capacity and affinity through data fitting of adsorption isotherms by nonlinear regression (NLR) is more accurate than linearized Langmuir equations. Linearization errors and the subjective choice of data points used to apply the linear regression analysis may deviate the fitted adsorption parameters (constants and adsorption capacities) from the expected values. The deviation magnitude increases for heterogeneous sorbents such as environmental particles and molecularly imprinted polymers, which adsorb by more than one sorption mechanism or adsorption sites of diverse chemical natures. For instance, Lineweaver-Burk linearization of isotherms simulated considering the presence of two adsorption sites (distinct adsorption energies) provides excellent linear regression fittings but for only one kind of adsorption site. Contrary, Scatchard and Eadie-Hoffsiee's equations indicate the presence of more than one kind of adsorption site, but if the difference between the adsorption constants is not significant, the choice of points used to perform the computation becomes subjective. On the contrary, NLR analysis considers all the adsorption points (experimental or simulated), providing objective criteria to define if more than one kind of site or retention mechanism rules the adsorbed amounts of analyte. The fitted constants have smaller deviations from the expected values than those obtained by linearization. In addition to the simulated data, the enhanced robustness of the NLR was demonstrated in the determination of the adsorption capacity and adsorption affinity of a humic acid sample towards Cu2+ at different pH.