人工智能平台发现的原卟啉原氧化酶抑制剂

IF 1.8 4区 农林科学 Q2 PLANT SCIENCES Advances in Weed Science Pub Date : 2023-01-01 DOI:10.51694/advweedsci/2023;41:00011
Abigail L. Barker, Yosef Geva, Eyal Simonovsky, Netta Shemesh, Yael Phillip, Ifat Shub, Franck E. Dayan
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引用次数: 0

摘要

杂草控制在现代农业中是必不可少的,尽管随着对大多数现有除草剂的抗性的出现和新化合物登记过程缓慢,杂草控制变得更加困难。目的利用一种考虑生物参数的创新人工智能算法识别候选除草剂,以缩短新除草剂的研发时间。结果我们描述了4-氯-2-五烯酰胺作为原卟啉原氧化酶(PPO)的新型抑制剂的发现,PPO是已知的除草剂靶点。
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Protoporphyrinogen oxidase inhibitors discovered by Artificial Intelligence platform
Background Weed control is essential in modern agriculture, though it has become more difficult with the emergence of resistance to most current herbicides and the slow registration process for new compounds. Objective Identify herbicide candidates using an innovative artificial intelligence algorithm that takes into effect biological parameters with the goal of reducing research and development time of new herbicides. Results We describe the discovery of 4-chloro-2-pentenamides as novel inhibitors of protoporphyrinogen oxidase (PPO), a known herbicide target site, by [...]
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来源期刊
Advances in Weed Science
Advances in Weed Science PLANT SCIENCES-
CiteScore
2.10
自引率
42.90%
发文量
25
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