通过人工智能生成模型和基于结构的虚拟选来发现潜在的新类杀虫剂
Yijin Kong1, Cong Zhou1, Du Tan1
1Shanghai Key Laboratory of Chemical Biology, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China.
Journal of agricultural and food chemistry
|February 29, 2024
概括
人工智能识别了新型尼可类杀虫剂候选者. 两种化合物,A2和A5,对Aphis craccivora表现出显著的杀虫活性,验证了人工智能对农药发现的方法.
科学领域:
- 农业化学 农业化学
- 计算化学计算化学
- 杀虫剂开发 杀虫剂开发
背景情况:
- 发现新型的类杀虫剂对于有效的害虫防治至关重要.
- 现有的杀虫剂面临着诸如耐药性和环境影响等挑战.
研究的目的:
- 为了利用人工智能 (AI) 和虚拟选来识别新尼类杀虫剂的潜在使用者.
- 为了验证人工智能产生的化合物的疗效和结合模式.
主要方法:
- 使用循环神经网络和转移学习构建了一个深度生成模型.
- 应用分层虚拟选和相似性搜索来过生成的分子.
- 对化合物进行了生物测试和分子对接/动力学模拟.
主要成果:
- 人工智能模型成功地产生了具有精确分子语法的潜在的新烟类化合物.
- 化合物A2和A5对Aphis craccivora的死亡率分别为52.5%和50.3%.
- 对接和分子动力学研究证实了与已知的新烟类药物相似的结合方式.
结论:
- 人工智能驱动的发现对于识别新型杀虫剂支架是有效的.
- 化合物A2和A5代表了新尼丁类杀虫剂的有希望的线索.
- 综合的人工智能和选策略加快了农药发现管道.
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