Nitenpyram detection by a carbon quantum dots-based sensor and molecular modification using 3D-QSAR modeling

Rostami, Masoumeh (2022) Nitenpyram detection by a carbon quantum dots-based sensor and molecular modification using 3D-QSAR modeling. Masters thesis, Memorial University of Newfoundland.

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Abstract

Due to the high demand for agricultural products, pesticides have been widely used to protect crops from potential diseases. Recently, some pesticides have been categorized as harmful emerging contaminants found in natural water, soil, and agricultural products, leading to toxicity for human beings. Therefore, monitoring and controlling their existence in the environment is essential. Carbon quantum dots-based optical sensors are a promising candidate for selective detection of pesticides at low concentrations because of their high sensitivity, selectivity, and fast procedure. In the first part of this study, a hybrid fluorescent sensor based on nitrogen-doped carbon quantum dots (N-CQDs) and silica gel was developed for quantitative detection of nitenpyram, a toxic neonicotinoid existing in the aquatic environment. The prepared N-CQDs@SiO2 sensor exhibited remarkable sensing selectivity and sensitivity towards nitenpyram among the four tested pesticides. A prominent fluorescence quenching of N-CQDs@SiO2 at 445 nm was observed in the presence of nitenpyram with a linear response range of 0–300.0 mg/L and an estimated detection limit of 2.6 mg/L. The excellent sensing selectivity could be attributed to a good affinity between N-CQDs and nitenpyram through hydrogen bonding and π–π interaction, which provokes an auto-absorption of excitation/emission light (IFE) for fluorescence quenching. The design of nitenpyram derivatives with improved environmental properties and functionality and enhanced sensing capacity is a critical way to control the harmfulness of the pesticide. In the second part of this study, 3D-QSAR modeling was adopted to obtain nitenpyram derivatives with improved environmental properties (i.e., biodegradability and bioaccumulation capacity). The functionality of these derivatives as pesticides was further investigated by evaluating their toxicity to pests. Based on the modeling results, the nitenpyram derivatives with higher biodegradability, lower bioaccumulation capacity, and better functionality were selected. They were then examined for their interaction with N-CQDs through molecular docking. The nitenpyram derivative showing a better interaction toward N-CQDs would result in improved sensing and detection. Integrating 3D-QSAR modeling and molecular docking successfully facilitated the design of environmentally friendly nitenpyram derivatives and CQDs-based detection of these products.

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