Published February 18, 2025
| Version v1
Journal article
Accelerating Ligand Discovery for Insect Odorant Receptors
Contributors
Others:
- Institut d'écologie et des sciences de l'environnement de Paris (iEES Paris) ; Institut de Recherche pour le Développement (IRD)-Sorbonne Université (SU)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (INRAE)
- Institut de Chimie de Nice (ICN) ; Université Nice Sophia Antipolis (1965 - 2019) (UNS)-Institut de Chimie - CNRS Chimie (INC-CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UniCA)
- ANR-20-CE20-0003,CryOR,Structure Cryo-EM de récepteurs olfactifs chez les insectes: accélération de la découverte de nouveaux sémiochimiques pour le biocontrôle(2020)
- ANR-15-IDEX-0001,UCA JEDI,Idex UCA JEDI(2015)
Description
Odorant receptors (ORs) are main actors of the insects peripheral olfactory system, making them prime targets for pest control through olfactory disruption. Traditional methods employed in the context of chemical ecology for identifying OR ligands rely on analyzing compounds present in the insect's environment or screening molecules with structures similar to known ligands. However, these approaches can be time-consuming and constrained by the limited chemical space they explore. Recent advances in OR structural understanding, coupled with scientific breakthroughs in protein structure prediction, have facilitated the application of Structure-Based Virtual Screening (SBVS) techniques for accelerated ligand discovery. Here, we report the first successful application of SBVS to insect ORs. We developed a unique workflow that combines molecular docking predictions, in vivo validation and behavioral assays to identify new behaviorally active volatiles for non-pheromonal receptors. This work serves as a proof of concept, laying the groundwork for future studies and highlighting the need for improved computational approaches. Finally, we propose a simple model for predicting receptor response spectra based on the hypothesis that the binding pocket properties partially encode this information, as suggested by our results on Spodoptera littoralis ORs.
Abstract
International audienceAdditional details
Identifiers
- URL
- https://hal.science/hal-04974632
- URN
- urn:oai:HAL:hal-04974632v1
Origin repository
- Origin repository
- UNICA