Application of response surface modeling optimization in UV spectrophotometric determination of 4-aminobenzoic acid by molecularly imprinted polypyrrole.

Selective determination of 4-aminobenzoic acid (ABA) in pharmaceutical and human serum samples was performed by molecularly imprinted polypyrrole and ultraviolet (UV) spectrophotometry, based on precipitation polymerization. The molecularly imprinted polymer (MIP) was prepared using pyrrole functional monomer and ABA template molecules. The significant factors controlling the performance of the synthesized ABAMIP sorbent were screened and optimized using Plackett- Burman design (PBD) and central composite design (CCD), respectively. The model was used to obtain the optimal values of the significant response factors. The predicted MIP to NIP response ratio demonstrated an approximate deviation of 5 % from the experimental value. Under the obtained optimal conditions, the calibration curve showed a linear range of 0.05-2 mM with a correlation coefficient (r2) of 0.9920 and a limit of detection (LOD) of 0.0310 mM. The method recovery for the analyte was obtained 88.10-100.5 in the investigated real samples. The proposed ABA-MIP sorbent showed an acceptable selectivity in the presence of some pharmaceuticals.

Selective determination of closantel by artificial neural network-genetic algorithm optimized molecularly imprinted polypyrrole using UV-visible spectrophotometry.

A molecularly imprinted polymer (MIP) for the selective solid-phase extraction (SPE) was prepared applying polymerization of pyrrole monomer in the presence of closantel (CLS) as a template molecule. The quantitative measurements were carried out using UV-Vis spectrophotometry. Several important parameters control the performance of polypyrrole sorbent. The influence of seven factors including loading time, polymerization time, amount of sorbent, stirring rate, desorption time, initiator concentration and monomer to template ratio were investigated. The optimization of parameters was performed using Plackett-Burman design (PBD), central composite design (CCD), artificial neural network (ANN) and genetic algorithm (GA). The Pareto plot showed that the effects of loading time, reaction time and amount of sorbent are most important to the process. These significant factors were investigated using CCD and the obtained data were used to train the ANN. The predicted model obtained from the trained ANN was introduced to GA as the fitness function to be optimized. The calibration curve demonstrated linearity over a concentration range of 0.010-10 mM with a correlation coefficient (R2) of 0.9833 under optimal condition. The synthesized MIP sorbent showed a good selectivity and sensitivity toward CLS. The limit of detection (LOD) for CLS was obtained 1.0 µM. The real sample analysis was performed to determine CLS in pharmaceutical and human serum samples.

Determination of methimazole based on electropolymerized-molecularly imprinted polypyrrole modified pencil graphite sensor.

Preparation of a molecularly imprinted polymer (MIP) film and its recognition property for methimazole (MMZ) was investigated. The polypyrrole (PPy) film was prepared by the cyclic voltammetric deposition of pyrrole in the presence of a supporting electrolyte (NaClO4·H2O) with and without MMZ through on a pencil graphite electrode (PGE). A computational study based on density functional theory was developed to evaluate the template-monomer geometry and interaction energy in the prepolymerization mixture. The performance of MIP sensor and non-imprinted polymer (NIP) film was evaluated by differential pulse voltammetry (DPV). The most important parameters controlling the performance of sensor were investigated and optimized. The prepared electrode was used for MMZ measurement by a three-step procedure, including analyte extraction in the electrode, electrode washing and electrochemical measurement of MMZ. The molecularly imprinted film exhibited a high selectivity and sensitivity toward methimazole in the experimental conditions. The calibration curve demonstrated linearity over a concentration range of 0.007-6mM with a correlation coefficient (r2) of 0.9808. The accuracy of the method was studied through spiking blank samples showed recovery of 98% with precision of 4%. Limit of detection based on S/N=3 was obtained 3×10-6M. The proposed sensor was applied successfully to determine MMZ in biological model samples and pharmaceuticals.