观点
计算机科学
药物发现
数据科学
纳米技术
生物信息学
生物
材料科学
艺术
视觉艺术
作者
Wei Wang,Yu Chen,Dao-Hong Gong,Runjiang Song,Lang Pan,Dandan Wang,Lianyang Bai,Wishwajith Kandegama,P. C. G. Bandaranayake,Lei Lian,Ge‐Fei Hao
标识
DOI:10.1021/acs.jafc.5c02504
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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