Multi-target insect repellents for topical and spatial protection

用于局部和空间保护的多目标驱虫剂

• 批准号: 10852200
• 负责人: Anandasankar Ray
• 金额: $ 20万
• 依托单位: UNIVERSITY OF CALIFORNIA RIVERSIDE
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-02-15 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10852200
• 关键词: Aedes; Anopheles Genus; Beds; Behavior; Behavioral; Behavioral Assay; Biological Assay; Carbon Dioxide; Chemical Structure; Chemicals; Clothing; Cosmetics; Country; Culex (Genus); Culicidae; Data; Data Set; Dengue; Disease; Dose; Electrophysiology (science); Evaluation; Flavoring; Food; Formulation; Foundations; Future; Generations; Goals; Human; Income; Insect Repellents; Insecta; Insecticides; Intervention; Lead; Ligands; Machine Learning; Malaria; Masks; Methods; Modeling; Morbidity - disease rate; Natural Source; Neurons; Odors; Olfactory Pathways; Pathway interactions; Persons; Pesticides; Play; Process; Property; Research; Resistance; Resistance development; Risk; Role; Skin; Smell Perception; Testing; Textiles; Vaccines; Validation; Volatilization; West Nile Fever; Yellow Fever; behavior test; candidate identification; carbon dioxide receptor; cheminformatics; comparative efficacy; cost; design; disease transmission; disorder control; efficacy validation; experimental study; global health; high risk population; in silico; knock-down; machine learning prediction; mortality; mutant; next generation; predictive modeling; pressure; prevent; protective effect; pyrethroid; rational design; receptor; relative cost; screening; tool; vapor; vector; vector control

ABSTRACT Mosquitoes use their olfactory system to find human hosts and, in the process, can transmit diseases like Malaria and Dengue to hundreds of millions of people worldwide that cause substantial mortality and morbidity. The olfactory system therefore provides an excellent target to design behavior disruption strategies. Most topical insect repellents in use (DEET, picaridin, IR3535) are effective against mosquitoes, however are rarely used by the high risk population in tropical countries due to the cost relative to incomes, the inconvenience of continuous application on skin at high concentrations and poor cosmetic properties. A more commonly used method globally is the spatial protective effect from low dose pyrethroid insecticides emitted from heated dispensers. However, the rapid spread of pyrethroid resistance in mosquitoes is cause for concern. In a recent breakthrough we have been able to develop a Machine Learning cheminformatic method to predict new repellent odorants and new pyrethroid-like molecules from in silico screening of >10 M compounds. In validating them in behavior assays, we have identified several powerful repellents from natural sources including compounds found in food and flavoring. In addition, we have identified a couple of leads for new pyrethroids, which appear to be up as effective as allethrin at a 100 x lower concentration. The goal of this proposal in 4 Aims is to identify the best-in-class insect repellent compounds and utilize them to create two types of powerful broad-spectrum blends: a topical that protects for longer at a low concentration and a spatial formulation that is more effective against knockdown resistant mosquitoes. For each blend we will also evaluate a version which has a pyrethroid component. First, we plan to rigorously validate the computationally predicted repellents in mosquito behavioral assays. Since the predictions have a variety of chemical structures, we will also use behavioral analysis of extant mutants in Aedes aegypti to identify the underlying receptor pathways responsible for aversion. Second, we plan to behaviorally evaluate volatile compounds that are known to overstimulate and disable the CO2-recpetor for their ability to mask attraction spatially. Third, we propose to validate the efficacy of the two newly discovered pyrethroids using topical and spatial assays. And fourth, we will test the dual and triple aversive pathway compounds for repellency in mosquitoes to find the most effective combination for spatial and topical repellency. Successful completion of this proposal will provide safe, affordable, and pleasant-smelling odorants that are better than existing actives in reducing contact between humans and mosquitoes.

抽象的 蚊子使用其嗅觉系统查找人类宿主，在此过程中，可以传播疾病 全球数亿人的疟疾和登革热，导致大量死亡和 发病率。因此，嗅觉系统为设计行为中断策略提供了一个绝佳的目标。 大多数使用的局部驱虫剂（DEET，Picaridin，IR3535）有效地防止蚊子 由于收入相对于收入， 在高浓度和化妆品性能差的皮肤上连续应用不便。更多 全球常用的方法是发出的低剂量拟除虫毒杀虫剂的空间保护作用 来自加热分配器。然而，昆虫抗性在蚊子中的迅速传播引起了人们的关注。 在最近的突破中，我们已经能够开发一种机器学习化学技术方法来预测 来自> 10 m化合物的硅筛筛选中的新驱蚊剂和新型拟除虫菊酯样分子。在 在行为分析中验证它们，我们已经从自然来源确定了几个强大的驱虫剂 包括食物和调味料中发现的化合物。此外，我们已经确定了一些新线索 拟除虫菊酯在浓度低100 x的情况下似乎与Allethrin一样有效。目标的目标 4个目标的建议是识别一流的驱虫剂化合物，并利用它们创建两个 强大的广谱混合物的类型：一种局部性，可在低浓度和空间上保护更长的时间 防止抗击倒的蚊子更有效的配方。对于每种混合物，我们还将评估 具有拟除虫菊酯分量的版本。首先，我们计划严格验证计算预测的 蚊子行为分析中的驱虫剂。由于预测具有多种化学结构，我们将 还要对伊蚊中现有突变体的行为分析来识别潜在的受体途径 负责厌恶。其次，我们计划在行为上评估已知的挥发性化合物 过度刺激并禁用二氧化碳重点的空间掩盖能力。第三，我们建议 使用局部和空间测定法验证两个新发现的拟除虫菊酯的功效。第四，我们 将测试双重和三重厌恶途径化合物，以发现蚊子的驱虫率最有效 空间和局部驱除的组合。成功完成此提案将提供安全， 负担得起，令人愉悦的气味剂，比现有活跃者更好地减少了接触 人类和蚊子。