Publications by authors named "De-Xing Ye"
Article Synopsis
- Insect neuropeptide allatostatins (ASTs) are key regulators of growth and reproduction in insects, but their complex structures and production costs limit their use in pest management, prompting the need for shorter and cheaper AST analogs.
- This study applied machine learning techniques to identify crucial structural components that enhance the effectiveness of AST analogs, leading to the creation of six new compounds, with one (A53) showing exceptional potency compared to natural variants.
- The findings highlight how computational methods can streamline the design and evaluation of novel AST analogs as potential insect growth regulators, providing a strategic approach for improving pest control.
Background: As one of the most abundant and destructive pests in agriculture, aphids cause significant damage to crops due to their sap-taking and as virus vectors. Chemical insecticides are the most effective method to control aphids, but they bring insecticide resistance problems and harm nontarget organisms, especially bees, therefore the search for novel eco-friendly aphid control agents with low bee toxicity is urgent. Insect kinins are a class of small neuropeptides that control important functions in insects.
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