Abstract
A model was developed using 167 carboxamide derivatives, from the United States Department of Agriculture archival database, that were tested as arthropod repellents over the past 60 yr. An artificial neural network employing CODESSA PRO descriptors was used to construct a quantitative structure-activity relationship model for prediction of novel mosquito repellents. By correlating the structure of these carboxamides with complete protection time, a measure of repellency based on duration, 34 carboxamides were predicted as candidate mosquito repellents. There were four additional compounds selected on the basis of their structural similarity to those predicted. The compounds were synthesized either by reaction of 1-acylbenzotriazoles with secondary amines or by reaction of acid chlorides with secondary amines in the presence of sodium hydride. The biological efficacy was assessed by duration of repellency on cloth at two dosages (25 and 2.5 mu mol/cm(2)) and by the minimum effective dosage to prevent Aedes aegypti (L.) (Diptera: Culicidae) bites. One compound, (E)-N-cyclohexyl-N-ethyl-2-hexenamide, was superior to N,N-diethyl-3-methylbenzamide (deet) at both the high dosage (22 d versus 7 d for deet) and low dosage (5 d versus 2.5 d for deet). Only one of the carboxamides, hexahydro-1-(1-oxohexyl)-1H-azepine, had a minimum effective dosage that was equivalent or slightly better than that of deet (0.033 mu mol/cm(2) versus 0.047 mu mol/cm(2)).