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对昆虫选择性道毒素的结构洞察力推动了人工智能增强的生物农药设计

Heng Jiang¹, Ruibo Gao^2,3,4, Huiqin Xu⁵

¹State Key Laboratory of Synthetic Biology; Frontiers Science Center for Synthetic Biology; Tianjin Key Laboratory for Modern Drug Delivery & High-Efficiency; School of Pharmaceutical Science and Technology, Faculty of Medicine, Tianjin University, Tianjin, China.

Nature communications

|March 5, 2026

概括

昆虫选择性毒素通过与电压感应域4结合来向昆虫的通道,从而破坏失活. 人工智能驱动的设计增强了一种子毒素.

科学领域:

结构生物学是结构生物学.
神经科学是一个神经科学.
生物化学生物化学

背景情况:

动物毒素选择性地准昆虫的电压通道.
了解昆虫的选择性是开发更安全的生物杀虫剂的关键.

研究的目的:

确定两种毒素对昆虫道选择性的结构基础.
研究毒素结合方式和作用机制.
应用AI进行增强的杀虫剂毒素设计.

主要方法:

低温电子显微镜 (cryo-EM) 用于解决与毒素结合的昆虫通道结构.
电生理学和毒性测试用于验证发现.
人工智能驱动的蛋白质设计和杀虫剂生物试验,用于有效性测试.

主要成果:

冷-EM结构显示Av3和LqhαIT毒素与VSD4的Na_vPaS结合,稳定了失活的S4构造.
不同的绑定位点 (Av3:VSD4-PD1接口;LqhαIT:位点3) 在共享的失活中断上趋同.
人工智能设计的LqhαIT变种显示出两倍的杀虫力.

结论:

结构洞察力阐明了昆虫道选择性的分子决定因素.
毒素的结合方式和作用机制是多样化的,但却趋同.
人工智能驱动的设计为开发强大的结构导向生物农药提供了强大的框架.

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