Development of an HPLC method for determination of pentachloronitrobenzene, hexachlorobenzene and their possible metabolites

Electrochemical sensors based on molecularly imprinted polymers for the detection of chlorophenols as emergent distributing chemicals (EDCs): a review

Environmental pollutants like chlorophenol chemicals and their derivatives are commonplace. These compounds serve as building blocks in the production of medicines, biocides, dyes, and agricultural chemicals. Chlorophenols enter the environment through several different pathways, including the breakdown of complex chlorinated hydrocarbons, industrial waste, herbicides, and insecticides. Chlorophenols are destroyed thermally and chemically, creating dangerous chemicals that pose a threat to public health. Water in particular is affected, and thorough monitoring is required to find this source of pollution because it can pose a major hazard to both human and environmental health. For the detection of chlorophenols, molecularly imprinted polymers (MIPs) have been incorporated into a variety of electrochemical sensing systems and assay formats. Due to their long-term chemical and physical stability as well as their simple and affordable synthesis process, MIPs have become intriguing synthetic alternatives over the past few decades. In this review, we concentrate on the commercial potential of the MIP technology. Additionally, we want to outline the most recent advancements in their incorporation into electrochemical sensors with a high commercial potential for detecting chlorophenols.

Molecularly imprinted polymer-based electrochemical sensors for monitoring the persistent organic pollutants chlorophenols

Because of the serious risks they pose to the environment and public health, chlorophenols (CPs), a typical class of the most persistent organic pollutants, have drawn increasing attention. Monitoring CPs effectively has become a pressing and difficult problem. The rapidly increasing need for onsite and real-time CP detection has led to the consideration of electrochemical sensing as a workable solution. Molecularly imprinted polymer (MIP)-based electrochemical sensing has emerged as a promising area for environmental monitoring in response to this analytical problem. MIPs, in conjunction with miniature electrochemical transducers, provide the opportunity to detect target analytes in situ. These devices have the advantages of great chemical and physical stability, cheap production costs, good selectivity, and quick response times. Most studies suggest that these sensors use nanoparticles to improve their analytical properties, especially sensitivity. Furthermore, these sensors have successfully used real water samples without the need for time-consuming pretreatment procedures. This article provides an overview of electrochemical MIP-based sensors reported to detect CPs in water samples. To obtain the highest sensitivity, special consideration is given to the fabrication of the sensors, which includes the use of various functional monomers, sensing platforms, and materials. Several other parameters are also discussed, including the linear concentration range, limit of detection, and the types of water samples that were examined.

Quantitative Structure-activity Relationship Analysis for Predicting Lipophilicity of Aniline Derivatives (Including some Pharmaceutical Compounds)

BACKGROUND

In this study, we used a hierarchical approach to develop quantitative structureactivity relationship (QSAR) models for modeling lipophilicity of a set of 81 aniline derivatives containing some pharmaceutical compounds.

OBJECTIVE

The multiple linear regression (MLR), principal component regression (PCR) and partial least square regression (PLSR) methods were utilized to construct QSAR models.

MATERIALS AND METHODS

Quantum mechanical calculations at the density functional theory level and 6- 311++G** basis set were carried out to obtain the optimized geometry and then, the comprehensive set of molecular descriptors was computed by using the Dragon software. Genetic algorithm (GA) was applied to select suitable descriptors which have the most correlation with lipophilicity of the studied compounds.

RESULTS

It was identified that such descriptors as Barysz matrix (SEigZ), hydrophilicity factor (Hy), Moriguchi octanol-water partition coefficient (MLOGP), electrophilicity (ω/eV) van der Waals volume (vWV) and lethal concentration (LC50/molkg-1) are the best descriptors for QSAR modeling. The high correlation coefficients and the low prediction errors for MLR, PCR and PLSR methods confirmed good predictability of the three models.

CONCLUSION

In present study, the high correlation between experimental and predicted logP values of aniline derivatives indicated the validation and the good quality of the resulting three regression methods, but MLR regression procedure was a little better than the PCR and PLSR methods. It was concluded that the studied aniline derivatives are not hydrophilic compounds and this means these compounds hardly dissolve in water or an aqueous solvent.