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Abstract: Lepidopteran pests, such as Helicoverpa armigera and Spodoptera frugiperda, pose significant threats to agriculture worldwide due to their resistance to traditional insecticides. Targeting the GABA receptors of these pests has emerged as a promising approach for effective pest control. This study utilized 3D-QSAR modeling to optimize a series of GABA receptor inhibitors, focusing on steric, electrostatic, hydrophobic, and hydrogen bonding interactions to enhance selectivity and potency. Diacylhydrazines were modified to interact with GABA receptors, and molecular alignment techniques were employed to ensure accurate mortality predictions. Statistical analyses, including cross-validation and contour maps, guided the rational design of new compounds with high predicted mortality rates. Based on the model we design serials new structures and finally selected 4th structure has the lowest mortality rate. The results demonstrate the potential for designing selective GABA receptor inhibitors that mitigate the environmental risks associated with broad-spectrum insecticides.
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