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.

摘要 蚊子利用它们的嗅觉系统寻找人类宿主，在这个过程中，可以传播疾病， 疟疾和登革热给全世界数亿人造成了严重的死亡， 发病率因此，嗅觉系统提供了一个很好的目标，设计行为中断策略。 使用中的大多数局部驱虫剂（DEET、picaridin、IR 3535）对蚊子有效，然而， 热带国家的高风险人群很少使用，因为成本相对于收入， 在高浓度下连续应用于皮肤上的不便性和不良的化妆性质。一个更 全球普遍使用的方法是低剂量拟除虫菊酯杀虫剂释放的空间保护效应 从加热的分配器。然而，蚊子对拟除虫菊酯耐药性的迅速传播令人担忧。 在最近的一项突破中，我们已经能够开发一种机器学习化学信息学方法来预测 新的驱避气味剂和新的拟除虫菊酯样分子，来自于对>10 M化合物的计算机筛选。在 在行为测定中验证它们，我们已经从天然来源中鉴定出几种强大的驱避剂， 包括食品和调味品中的化合物。此外，我们还确定了一些新的线索， 拟除虫菊酯，其似乎与浓度低100倍的丙烯菊酯一样有效。这个目标 4目标中的建议是确定最好的驱虫剂化合物，并利用它们来创造两个 类型的强大的广谱混合物：一个局部的，保护更长的时间在低浓度和空间 更有效对抗击倒抗性蚊子的制剂。对于每种混合物，我们还将评估 含有拟除虫菊酯成分的版本。首先，我们计划严格验证计算预测的 驱蚊剂在蚊子行为测定中的应用。由于预测具有多种化学结构，我们将 我还使用行为分析现存的突变体在埃及伊蚊，以确定潜在的受体途径 负责厌恶。其次，我们计划从行为上评估已知的挥发性化合物， 过度刺激和禁用二氧化碳受体，因为它们有能力在空间上掩盖吸引力。第三，我们建议 使用局部和空间试验验证两种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对蚊子的驱避作用，以找到最有效的 空间和局部排斥性的组合。成功完成此提案将提供安全， 负担得起的，和愉快的气味，比现有的活性物质更好地减少接触之间 人类和蚊子