Computer Model for Finding Mosquito Repellent
May 28, 2008
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. Their
findings are reported in the Proceedings of
the National Academy of Sciences.
ARS is the chief scientific research agency of the U.S. Department of
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
Clark, research leader of the
and Fly Unit at ARS' Center for Medical, Agricultural and Veterinary
in Gainesville, Fla.; and CMAVE Director
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.
A dataset of 200 known compounds tested for repellency between 1950 and 1980
from the USDA screening program was used as the base data for the modeling.
This phase of the work trained the neural network to recognize the
most effective kinds of chemicals. Then, 23 novel compounds were tested under
ANN, some of which were predicted by lab tests to repel mosquito bites three
times longer than the equivalent concentration of DEET.
This approach may streamline the process of testing new active ingredients,
lead to repellents that are longer lasting, and bring them to market faster.