利用人工智能和抗生素数据来促进新型真菌杀菌剂的设计
Ruo-Qi Yang1,2, Hong-Hao Li2, Jun-Ya Wang2
1National Pesticide Engineering Research Center, State Key Laboratory of Elemento-Organic Chemistry, College of Chemistry, Nankai University, Tianjin, People's Republic of China.
Pest management science
|September 9, 2025
概括
这项研究使用人工智能 (AI) 和抗生素数据来设计新型杀菌剂. 一个新的AI策略成功生成了杀菌剂候选物,其中一种化合物显示出强大的酶抑制,与现有治疗方法相比.
科学领域:
- 农业化学研究农业化学研究.
- 计算化学是一种计算化学.
- 药物发现 药物发现
背景情况:
- 生成型人工智能 (AI) 加快了农药开发.
- 当前的人工智能方法可能会通过关注分子相似性来限制新型脚手架的发现.
- 探索新的数据源对于创新的农药突破至关重要.
研究的目的:
- 利用抗生素数据和人工智能开发一种新的杀菌剂设计策略.
- 克服现有的AI方法在探索各种化学支架方面的局限性.
- 识别具有广泛应用潜力的新型真菌杀菌剂候选物.
主要方法:
- 结合预训练和转移学习,使用循环神经网络生成分子.
- 利用图形神经网络来区分杀菌剂和抗生素.
- 选生成的分子对抗细胞染色体bc1复合物的抑制活性.
主要成果:
- 产生具有关键杀菌特性的抗生素类分子,避免与现有杀菌剂过度相似.
- 识别了两个分子与杀菌剂花皮可沙米德共享一个支架,不在训练组中.
- 化合物cp461证明了与花皮胺 (17.9 ± 1.1 nM IC50) 相比的酶抑制.
结论:
- 开创AI应用,使用抗生素数据用于新型真菌杀菌剂设计.
- 证明了创新农药开发的可行研究方向.
- 验证了人工智能在发现有效农业化学化合物的潜力.
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