Arthur Comte, Maxence Lalis, Ludivine Brajon, Riccardo Moracci, Nicolas Montagné, Jérémie Topin, Emmanuelle Jacquin Joly, Sébastien Fiorucci
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引用次数: 0
摘要
气味受体(ORs)是昆虫外周嗅觉系统的主要角色,因此成为通过嗅觉干扰控制害虫的主要目标。在化学生态学背景下,识别气味受体配体的传统方法依赖于分析昆虫环境中存在的化合物或筛选与已知配体结构相似的分子。然而,这些方法耗时长,而且受限于其探索的有限化学空间。近来对 OR 结构理解的进步,加上蛋白质结构预测方面的科学突破,促进了基于结构的虚拟筛选(SBVS)技术在加速配体发现方面的应用。在此,我们报告了 SBVS 在昆虫 ORs 中的首次成功应用。我们开发了一种独特的工作流程,将分子对接预测、体内验证和行为试验结合在一起,为非外激素受体鉴定新的行为活性挥发物。这项工作可作为概念验证,为今后的研究奠定基础,并强调了改进计算方法的必要性。最后,我们提出了一个预测受体反应谱的简单模型,该模型基于这样一个假设:结合口袋的特性部分地编码了这一信息,正如我们对滨海蝶ORs的研究结果所表明的那样。
Accelerating Ligand Discovery for Insect Odorant Receptors
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.