National Fellow Lab, Division of Entomology and Nematology, Indian Institute of Horticultural Research, Bangalore, India.
BMC Genomics. 2014 Mar 19;15:209. doi: 10.1186/1471-2164-15-209.
Semiochemical is a generic term used for a chemical substance that influences the behaviour of an organism. It is a common term used in the field of chemical ecology to encompass pheromones, allomones, kairomones, attractants and repellents. Insects have mastered the art of using semiochemicals as communication signals and rely on them to find mates, host or habitat. This dependency of insects on semiochemicals has allowed chemical ecologists to develop environment friendly pest management strategies. However, discovering semiochemicals is a laborious process that involves a plethora of behavioural and analytical techniques, making it expansively time consuming. Recently, reverse chemical ecology approach using odorant binding proteins (OBPs) as target for elucidating behaviourally active compounds is gaining eminence. In this scenario, we describe a "computational reverse chemical ecology" approach for rapid screening of potential semiochemicals.
We illustrate the high prediction accuracy of our computational method. We screened 25 semiochemicals for their binding potential to a GOBP of B. dorsalis using molecular docking (in silico) and molecular dynamics. Parallely, compounds were subjected to fluorescent quenching assays (Experimental). The correlation between in silico and experimental data were significant (r2 = 0.9408; P < 0.0001). Further, predicted compounds were subjected to behavioral bioassays and were found to be highly attractive to insects.
The present study provides a unique methodology for rapid screening and predicting behaviorally active semiochemicals. This methodology may be developed as a viable approach for prospecting active semiochemicals for pest control, which otherwise is a laborious process.
信息素是一个通用术语，用于指影响生物体行为的化学物质。它是化学生态学领域中一个常用的术语，涵盖信息素、他感物质、利它素、引诱剂和驱避剂。昆虫已经掌握了使用信息素来作为通讯信号的艺术，并依赖它们来寻找配偶、宿主或栖息地。昆虫对信息素的这种依赖性使化学生态学家能够开发出对环境友好的害虫管理策略。然而，发现信息素是一个繁琐的过程，涉及到大量的行为和分析技术，因此需要大量的时间。最近，使用气味结合蛋白（OBP）作为阐明行为活性化合物的靶标反向化学生态学方法正在得到重视。在这种情况下，我们描述了一种用于快速筛选潜在信息素的“计算反向化学生态学”方法。
我们说明了我们计算方法的高预测准确性。我们使用分子对接（计算机模拟）和分子动力学筛选了 25 种信息素与 B. dorsalis 的 GOBP 的结合潜力。同时，对化合物进行了荧光猝灭实验（实验）。计算机模拟和实验数据之间的相关性具有统计学意义（r2 = 0.9408；P < 0.0001）。此外，预测的化合物进行了行为生物测定，发现它们对昆虫具有高度吸引力。
本研究提供了一种快速筛选和预测行为活性信息素的独特方法。这种方法可以作为一种可行的方法来寻找有效的害虫控制信息素，否则这是一个繁琐的过程。
