How Computational Studies of Mosquito Repellents Contribute to the Control of Vector Borne Diseases
Vector Borne Diseases (VBD) present a serious threat to millions of people. In this paper various computational approaches towards new drugs design against some of them are reviewed. Malaria attracts particular attention of computational medicinal chemists. A promising strategy of the fight with VBD is usage of insect repellents. N,N-Diethyl-m-toluamide (DEET) has been the mostly used mosquito repellent for over five decades. Its mode of action is still a matter of intensive studies and debate. A possible mechanism of DEET activity is inactivation of odorant receptor proteins expressed in female mosquitoes, and being critical for finding a prey. In order to check possible interactions of DEET with such a transmembrane protein and to indicate a plausible biophore, we have constructed a hybrid "ab initio" model of Anopheles gambiae Odorant Receptor Protein 1 (AgOR1). The transmembrane regions of AgOR1 were predicted using 10 different bioinformatics algorithms and a consensus approach. A full torsional potential energy surface of DEET was determined using the AM1 method and low energy conformers were further optimized using the HF/6-31G method. DEET and a series of diastereomers of alternative repellent cyclohex-3-enyl 2-methylpiperidin-1-yl ketone (220) was docked to the AgOR1 model using the AutoDock 3.0.5 code, and possible interactions sites inside this GPCR AgOR1 were identified.
mosquito repellents vbd malaria deet agor1 gpcr