A new method for predicting the acute toxicity of carbamate pesticides based on the perspective of binding information with carrier protein

Study on the toxicity prediction model ofacetolactate synthase inhibitor herbicides based on human serum albumin and superoxide dismutase binding information

Toxicity significantly influences the successful development of drugs. Based on the toxicity prediction method (carrier protein binding information-toxicity relationship) previously established by the our group, this paper introduces information on the interaction between pesticides and environmental markers (SOD) into the model for the first time, so that the toxicity prediction model can not only predict the toxicity of pesticides to humans and animals, but also predict the toxicity of pesticides to the environment. Firstly, the interaction of acetolactate synthase inhibitor herbicides (ALS inhibitor herbicides) with human serum albumin (HSA) and superoxide dismutase (SOD) was investigated systematically from theory combined with experiments by spectroscopy methods and molecular docking, and important fluorescence parameters were obtained. Then, the fluorescence parameters, pesticides acute toxicity LD50 and structural splitting information were used to construct predictive modeling of ALS inhibitor herbicides based on the carrier protein binding information (R2 = 0.977) and the predictive modeling of drug acute toxicity based on carrier protein binding information and conformational relationship (R2 = 0.991), which had effectively predicted pesticides toxicity in humans and animals. To predict potential environmental toxicity, the predictive modeling of drug acute toxicity based on superoxide dismutase binding information was established (R2 = 0.883) by ALS inhibitor herbicides-SOD binding information, which has a good predictive ability in the potential toxicity of pesticides to the environment. This study lays the foundation for developing low toxicity pesticides.

Applying molecular docking to pesticides

Pesticide creation is related to the development of sustainable agricultural and ecological safety, and molecular docking technology can effectively help in pesticide innovation. This paper introduces the basic theory behind molecular docking, pesticide databases, and docking software. It also summarizes the application of molecular docking in the pesticide field, including the virtual screening of lead compounds, detection of pesticides and their metabolites in the environment, reverse screening of pesticide targets, and the study of resistance mechanisms. Finally, problems with the use of molecular docking technology in pesticide creation are discussed, and prospects for the future use of molecular docking technology in new pesticide development are discussed. © 2023 Society of Chemical Industry.

Current electroanalytical approaches in the carbamates and dithiocarbamates determination

Pesticides are a suitable tool for controlling plagues and disease vectors. However, their inappropriate use allows for contamination of the environment, soil, water, and foods. Carbamates and dithiocarbamates pesticides present accumulative effects in the human body resulting in hormonal, neurological and reproductive disorders, and some are still suspected or proven to give carcinogenic or mutagenic effects. This review provides a current electroanalytical approach in the carbamates and dithiocarbamates determination, showing the use of voltammetric techniques such as amperometry, cyclic and linear scan, differential pulse, and square wave voltammetry, indicating their advantages, disadvantages, and perspectives in electroanalytical detection of carbamates and dithiocarbamates in natural water and foods. Also are reported the different materials used in the preparation of working electrodes since their choice has an important impact on the success of the analytical applications, resulting in suitable sensitivity, selectivity, stability, and robustness.

Study of modeling and optimization for predicting the acute toxicity of carbamate pesticides using the binding information with carrier protein

To predict drug acute toxicity using the binding information with human serum albumin, our research group established a new method (Carrier protein binding information-toxicity relationship, CPBITR). Unfortunately, the previous model had too few data sets which may affect the accuracy and credibility of the model. In this paper, therefore, we measured the binding modes of three carbamate pesticides, Bendiocarb, Butocarboxim and Dioxacarb with human serum albumin (HSA) to supplement the previously modeled training set. Multispectral methods and molecular docking were used to study their binding modes. We built and optimized the previous models with the combined information of three different toxicity pesticides and HSA in order to find better prediction method. The results showed that Back-propagation Artificial Neural Network model has the best fitting effect among these models. In conclusion, the proposed model effectively improves the accuracy and credibility of the existing model. It results in significant predict drug acute toxicity using the binding information with carrier protein and contribute to drug development and research.

Synthesis and antifungal screening of tetramethyl hexahydro-1H-xanthene-1,8(2H)-dione derivatives as potential inhibitors of morphogenesis and biofilm formation in Candida albicans

A series of hexahydro-1H-xanthene-1,8(2H)-dione derivatives were synthesized. All the derivatives were screened for their anti-virulence properties against Candida albicans. In silico studies were performed to corroborate the experimentally observed facts.