Location: Mosquito and Fly ResearchTitle: Development of novel repellents using structure-activity modeling of compounds in the USDA archival database) Author
Submitted to: Book Chapter
Publication Type: Book / chapter
Publication Acceptance Date: 8/16/2011
Publication Date: 12/28/2011
Citation: Bernier, U.R., Tsikolia, M. 2011. Development of novel repellents using structure-activity modeling of compounds in the USDA archival database. In: Paluch, G.E., Coats, J.R. In Recent Developments in Invertebrate Repellents. American Chemical Society. 1090:21-46. Interpretive Summary: Scientists at the USDA-ARS, Center for Medical, Agricultural, and Veterinary Entomology in Gainesville, FL, in collaboration with scientists from the University of Florida, have studied mosquito repellents to predict how well a repellent will perform based on its chemical structure. The study was performed on chemicals that are similar in structure to the well known mosquito repellent DEET (N,N-diethyl-3-methylbenzamide). Some of the chemicals came from the sixty year historical archives of tested repellents at the laboratory in Gainesville and some of the chemicals were novel, having been designed based upon these studies. The chemicals were evaluated by placing them on cloth, drying then, and then testing the number of days that the repellent prevented mosquito bites when the cloth was worn over the arm of a human volunteer. Over a third of the chemicals lasted at least twice as long as DEET in these tests. The results from these tests were then used to produce a model of a “good” repellent based on the chemical structure. The models were found to be very accurate in their ability to predict good repellents. These studies provide information on how repellents work based on the chemical structure of the repellent. The outcomes from these studies will lead to better repellents to protect humans and animals from diseases transmitted by mosquitoes and other biting flies. This work is of interest to the United States military, it’s civilians, and to the global population that may be bitten by disease-transmitting mosquitoes and flies.
Technical Abstract: The United States Department of Agriculture (USDA) has developed repellents and insecticides for the U.S. military since 1942. Repellency and toxicity data for over 30,000 compounds are contained within the USDA archive. Repellency data from subsets of similarly structured compounds were used to develop artificial neural network (ANN) models to predict new compounds for testing. Compounds were then synthesized and evaluated for their repellency against Aedes aegypti mosquitoes. The repellent data, i.e., complete protection time (CPT) were used to develop Quantitative Structure Activity Relationship (QSAR) models to predict repellency. Successful prediction of novel acylpiperidine structures by ANN models resulted in the discovery of compounds that provided protection over three times longer than DEET. The acylpiperidine QSAR models employed 4 descriptors to describe the relationship between structure and repellent duration. The ANN model of the carboxamides did not predict compound structures with exceptional CPTs as accurately; however, several carboxamide candidates did perform equal to or better than DEET.