ArticleCellular and molecular life sciences : CMLS2021
Reverse chemical ecology in a moth: machine learning on odorant receptors identifies new behaviorally active agonists.
Article in Cellular and molecular life sciences : CMLS, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 34 citations in OpenAlex.
- Machine learning-enabled chemical ecology for integrated pest management: from volatiles to field applications.Journal of insect science (Online) · 2026Review
- Article
- Molecular bases of insect odorant receptor function: specificity and evolution.Biological reviews of the Cambridge Philosophical Society · 2026Review
- Harnessing semiochemicals for parasitoid-based biological control: from laboratory identification to field applications.Crop health · 2025Review
- Olfactory binding proteins: a review across the Insecta.Frontiers in zoology · 2025Review
- Transcriptome Screening and Identification of Chemosensory Genes in the Goji Berry Psyllid,Biology · 2025Article
- De novo genome assembly, annotation, and characterization of chemosensory genes in the camel ked (Hippobosca camelina).BMC genomics · 2025Article
- Insight into the Relationships Between Chemical, Protein and Functional Variables in the PBP/GOBP Family in Moths Based on Machine Learning.International journal of molecular sciences · 2025Article
- Functional Characterization of a Female-Biased Chemoreceptor of the Codling Moth (Cydia pomonella) Responding to Aldehydes and Other Volatile Compounds.Journal of chemical ecology · 2025Article
- Combining Machine Learning and Electrophysiology for Insect Odorant Receptor Studies.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Accelerating Ligand Discovery for Insect Odorant Receptors.International journal of biological sciences · 2025Article
- Eurasian spruce bark beetle detects lanierone using a highly expressed specialist odorant receptor, present in several functional sensillum types.BMC biology · 2024Article
Corrections and comments
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Authors and funding
10 authors at 1 institution in 3 countries.
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Abstract
The concept of reverse chemical ecology (exploitation of molecular knowledge for chemical ecology) has recently emerged in conservation biology and human health. Here, we extend this concept to crop protection. Targeting odorant receptors from a crop pest insect, the noctuid moth Spodoptera littoralis, we demonstrate that reverse chemical ecology has the potential to accelerate the discovery of novel crop pest insect attractants and repellents. Using machine learning, we first predicted novel natural ligands for two odorant receptors, SlitOR24 and 25. Then, electrophysiological validation proved in silico predictions to be highly sensitive, as 93% and 67% of predicted agonists triggered a response in Drosophila olfactory neurons expressing SlitOR24 and SlitOR25, respectively, despite a lack of specificity. Last, when tested in Y-maze behavioral assays, the most active novel ligands of the receptors were attractive to caterpillars. This work provides a template for rational design of new eco-friendly semiochemicals to manage crop pest populations.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.