Machine learning decodes chemical features to identify novel agonists of a moth odorant receptor
Machine learning decodes chemical features to identify novel agonists of a moth odorant receptor
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DOI：
10.1038/s41598-020-58564-9
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发表时间：
2020-02-03
影响因子：
4.6
通讯作者：
Jacquin-Joly, Emmanuelle
中科院分区：
文献类型：
--
作者：
Caballero-Vidal, Gabriela;Bouysset, Cedric;Jacquin-Joly, Emmanuelle
在动物的外周嗅觉器官中表达的气味受体是动物感知挥发物的关键蛋白。虽然它们决定了给定物种的气味空间，但它们的功能表征是一个漫长的过程，并且仍然有限。迄今为止，机器学习虚拟筛选已用于预测哺乳动物和昆虫中此类受体的新配体，使用已知配体的化学特征。在昆虫中，这种方法还限于双翅目，而昆虫气味受体是已知的高度不同的目的。在这里，我们将这种策略扩展到鳞翅目受体，SlitOR 25，参与识别有吸引力的气味在农作物害虫Spodoptera littoralis幼虫。通过对300万个分子的虚拟筛选，预测了32个已在SlitOR 25上系统测试功能的化合物，揭示了11个新的激动剂，成功率为28%。我们的研究结果表明，支持向量机优化发现新的激动剂和扩大的化学空间的鳞翅目OR。此外，它开辟了结构-功能关系的分析，通过比较激动剂的化学结构。在作物害虫中的这种概念验证最终能够鉴定能够在生物防治背景下改变嗅觉行为的OR激动剂或拮抗剂。
Odorant receptors expressed at the peripheral olfactory organs are key proteins for animal volatile sensing. Although they determine the odor space of a given species, their functional characterization is a long process and remains limited. To date, machine learning virtual screening has been used to predict new ligands for such receptors in both mammals and insects, using chemical features of known ligands. In insects, such approach is yet limited to Diptera, whereas insect odorant receptors are known to be highly divergent between orders. Here, we extend this strategy to a Lepidoptera receptor, SlitOR25, involved in the recognition of attractive odorants in the crop pest Spodoptera littoralis larvae. Virtual screening of 3 million molecules predicted 32 purchasable ones whose function has been systematically tested on SlitOR25, revealing 11 novel agonists with a success rate of 28%. Our results show that Support Vector Machine optimizes the discovery of novel agonists and expands the chemical space of a Lepidoptera OR. More, it opens up structure-function relationship analyses through a comparison of the agonist chemical structures. This proof-of-concept in a crop pest could ultimately enable the identification of OR agonists or antagonists, capable of modifying olfactory behaviors in a context of biocontrol.