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AI-Empowered Molecular Editing Opens a New Horizon in Pesticide Discovery

文献类型： 外文期刊

作者： Wang, Wei 1 ; Chen, Yu 3 ; Gong, Dao-Hong 1 ; Song, Run-Jiang 1 ; Pan, Lang 4 ; Wang, Heng-Zhi 6 ; Bai, Lian-Yang 4 ; Kandegama, W. M. W. W. 1 ; Gunathilake Bandaranayake, Pradeepa C. 8 ; Lian, Lei 1 ; Hao, Ge-Fei 1 ;

作者机构： 1.Guizhou Univ, State Key Lab Green Pesticide, Guiyang 550025, Peoples R China

2.Guizhou Univ, Ctr Res & Dev Fine Chem, Guiyang 550025, Peoples R China

3.Qingdao KingAgroot Cpds Co Ltd, Qingdao 266000, Peoples R China

4.Hunan Acad Agr Sci, Hunan Agr Biotechnol Res Inst, Changsha 410125, Peoples R China

5.Hunan Agr Univ, Coll Plant Protect, Changsha 410128, Peoples R China

6.Shandong Agr Univ, Coll Plant Protect, Tai An 271018, Peoples R China

7.Wayamba Univ Sri Lanka, Fac Agr & Plantat Management, Dept Hort & Landscape Gardening, Makandura 60170, Sri Lanka

8.Univ Peradeniya, Fac Agr, Agr Biotechnol Ctr, Peradeniya 20400, Sri Lanka

关键词： pesticide discovery; artificial intelligence; molecular editing; molecular generation; moleculareditor

期刊名称：JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY （ 影响因子：6.2； 五年影响因子：6.4 ）

ISSN： 0021-8561

年卷期： 2025 年 73 卷 30 期

页码：

收录情况： SCI

摘要： Rapid evolution of digital technologies has enabled vital tools in pesticide discovery, which are crucial for agricultural productivity and food security. Therein, molecular editors have emerged as basic and critical tools in this field. However, existing molecular editors lack advanced features to optimize computer-aided pesticide discovery. We propose three enhancements: (1) generating practical synthesis strategies for novel candidates; (2) contributing to the generation of 2D structural molecules with AI technology; and (3) finding possible targetable pockets and sites based on 2D structural molecules. We believe that our viewpoints can contribute to further advancement of AI-driven molecular editing, enabling it to better facilitate pesticide discovery.

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