Malaria, Dengue Fever, West Nile Encephalities, Sleeping Sickness, Leishmaniasis, Japanese encephalitis (JE) are the widest large range of diseases causing highest mortality to human beings at Global level and they belong to the group Vector borne diseases (VBD). It is estimated that more than one million deaths were happening every year mostly in tropical regions of South America, Africa & Asia due to these vectors i.e., mosquitoes and mites, which are main disease transporting vectors from one host to another. A remarkable effort has been made to develop various types of insecticides and insect repellents. To control VBD, a bio-defense strategy methods have been employed which were found to be more costly and labour intensive, recurring and time consuming. A new class of repellents were made based on structure based rational approaches of ligand molecules based binding efficiencies with Odorant binding proteins (OBPs) or other olfaction inhibitory compounds with attractive characteristics. But, with very limited knowledge available to screen photo-chemical compounds to design novel mosquito repellents employing a very high-throughput Insilco computational biology methods. Therefore, in this context, we attempted to screen out 3 phytochemicals from different plants exhibiting mosquito repellent activities reported from published literature and various public domains & molecular docking studies, aiming at the Odorant Binding Proteins of Culex quinquefasciatus. The N, N-Diethyl-m-toluamide (DEET) was widely used mosquito repellent chemical chosen as standard reference to validate the binding affinities and specificities of selected compounds aligned with Odoront Binding Proteins. A total of such 50 compounds including DEET were docked against the active site of OBT models or Crystal Structures using AutoDock. Among 5 phytochemical compounds, sum of 3 compounds have resulted in high affinity binding energies & high no of hydrogen-bonds as compared to standard reference of DEET. Among the selected Citronellol, Saponin, and Azadirachtin, are showing the highest docking scores which secure to develop more effective and safer mosquito repellents in future prospect.
Exploring the Potentiality of Natural Products from Essential Oils as Inhibitors of Odorant-Binding Proteins: A Structure- and Ligand-Based Virtual Screening Approach To Find Novel Mosquito Repellents
