Computational Modeling Oriented Substructure Splicing Application in the Identification of Thiazolidine Derivatives as Potential Low Honeybee Toxic Neonicotinoids

Cong Zhou, Yijin Kong, Huihui Zhang, Na Zhai, Zhong Li, Xuhong Qian, Zewen Liu, Jiagao Cheng

JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY(2024)

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Abstract
With the aim of identifying novel neonicotinoid insecticides with low bee toxicity, a series of compounds bearing thiazolidine moiety, which has been shown to be low bee toxic, were rationally designed through substructure splicing strategy and evaluated insecticidal activities. The optimal compounds A24 and A29 exhibited LC50 values of 30.01 and 17.08 mg/L against Aphis craccivora, respectively. Electrophysiological studies performed on Xenopus oocytes indicated that compound A29 acted on insect nAChR, with EC50 value of 50.11 mu M. Docking binding mode analysis demonstrated that A29 bound to Lymnaea stagnalis acetylcholine binding protein through H-bonds with the residues of D_Arg55, D_Leu102, and D_Val114. Quantum mechanics calculation showed that A29 had a higher highest occupied molecular orbit (HOMO) energy and lower vertical ionization potential (IP) value compared to the high bee toxic imidacloprid, showing potentially low bee toxicity. Bee toxicity predictive model also indicated that A29 was nontoxic to honeybees. Our present work identified an innovative insecticidal scaffold and might facilitate the further exploration of low bee toxic neonicotinoid insecticides.
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Key words
neonicotinoid insecticides,thiazolidine derivatives,insecticidal activity,bee toxicity,acetylcholinebinding protein
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