Summer reminds us that one of the most useful tools for preventing mosquito bites is insect repellent. Agricultural Research Service (ARS) scientists and colleagues at the University of Florida (UF) have shown that a computer modeling program that looks at compounds' chemical structure can predict which compounds are likely to stop mosquito bites.
For more than 50 years, DEET has been the "gold standard" of mosquito repellents. DEET was discovered during a USDA screening program that tested 40,000 chemicals in an expensive process that took a decade.
The ARS research team included chemist Ulrich Bernier; Gary Clark, research leader of the Mosquito and Fly Unit at ARS' Center for Medical, Agricultural and Veterinary Entomology (CMAVE) in Gainesville, Fla.; and CMAVE Director Kenneth Linthicum. The UF researchers were Alan R. Katritzky, Zuoquan Wang, Svetoslav Slavov, Maia Tsikolia, Dimitar Dobchev, Novruz G. Akhmedov and C. Dennis Hall of the Center for Heterocyclic Compounds, also in Gainesville.
In the research, a modeling system that can use chemical structures and insect receptors was used to predict repellents’ effectiveness against mosquitoes. The researchers used a particularly efficient approach, called quantitative structure-activity relationship, or QSAR. They chose a modeling system called an artificial neural network (ANN), because it can test theoretical compounds generated by the computer against a complicated phenomenon like duration of repellency.
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