Abstract

The biolarvicide is a substitute of synthetic larvicide to prevent mosquitotransmitted diseases. The present study was aimed to detect percentage mortality of larvae of Culex epidesmus Theobald, 1910 by aqueous extract of neem leaf (Azadirachta indica A. Juss) and the inhibitory potential of established the phytoconstituents present in the leaf of neem against the protein of mosquito (acetylcholinesterase) through molecular docking and toxicokinetics. The acetylcholinesterase (receptor) was obtained (PDB ID: 2AZG) from the Protein Data Bank (PDB) and the information of ligands (phytochemicals) were obtained from PubChem database. Few established phytochemicals of leaf were used as ligands in this study. These chemical structures (threedimensional) were procured from online CORINA software. The software, PyRx (Version 0.8) for the structurebased virtual screening and ADMETSAR were used for toxicokinetics study. The present results indicate that phytochemicals found in the leaf extract of A. indica observed mortality to the larvae at higher concentrations (70100%). The interaction with different residues of mosquito acetylcholinesterase protein observed ligand binding energy for quercetin (9.4 Kcal/mol). Among other phytochemicals, quercetin may have an inhibitory effect on nerve protein for larvae mortality and may be suitable compound for environment by toxicokinetics evaluation. In conclusion, it was obtained through faster screening by using software that phytoconstitent quercetin of A. indica may use future larvicide as a lead compound for the prevention of C. epidesmus growth. It is suggested that functional assay (in vivo and in vitro assay) should be carried out for the validation of the present results.

Details

Title
Assessment of bio-larvicide for Culex epidesmus through bioassay along with toxicokinetics and virtual screening of phytoligands from the leaf of Azadirachta indica against mosquito acetylcholinesterase
Author
Talukdar, Partha; Ganguly, Debarati; Mandal, Sampriti
Pages
445-451
Publication year
2017
Publication date
May 2017
Publisher
International Journal of Advanced Research in Computer Science
e-ISSN
09765697
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
1912637271
Copyright
© May 2017. This work is published under https://creativecommons.org/licenses/by-nc-sa/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.