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Research Articles

Structure based virtual screening, 3D-QSAR, molecular dynamics and ADMET studies for selection of natural inhibitors against structural and non-structural targets of Chikungunya

, , , , , & show all
Pages 3150-3161 | Received 17 May 2018, Accepted 02 Aug 2018, Published online: 28 Dec 2018
 

Abstract

The transmission of mosquito-borne Chikungunya virus (CHIKV) has large epidemics worldwide. Till date, there are neither anti-viral drugs nor vaccines available for the treatment of Chikungunya. Accumulated evidences suggest that some natural compounds i.e., Epigallocatechin gallate, Harringtonine, Apigenin, Chrysin, Silybin, etc. have the capability to inhibit CHIKV replication in vitro. Natural compounds are known to possess less or no side effects. Therefore, natural compound in its purified or crude extracts form could be the preeminent and safe mode of therapies for Chikungunya. Wet lab screening and identification of natural compounds against Chikungunya targets is a time consuming and expensive exercise. In the present study, we used in silico techniques like receptor-ligand docking, Molecular dynamic (MD), Three Dimensional Quantitative Structure Activity Relation (3D-QSAR) and ADME properties to screen out potential compounds. Aim of the study is to identify potential lead/s from natural sources using in silico techniques that can be developed as a drug like molecule against Chikungunya infection and replication. Three softwares were used for molecular docking studies. Potential ligands selected by docking studies were subsequently subjected 3D-QSAR studies to predict biological activity. Based on docking scores and pIC50 value, potential anti-Chikungunya compounds were identified. Best docked receptor-ligands were also subjected to MD for more accurate estimation. Lipinski’s rule and ADME studies of the identified compounds were also studied to assess their drug likeness properties. Results of in silico findings, led to identification of few best fit compounds of natural origin against targets of Chikungunya virus which may lead to discovery of new drugs for Chikungunya.

Communicated by Ramaswamy H. Sarma

Graphical Abstract

Acknowledgement

All authors are thankful to Dr. B. R. Ambedkar Centre for Biomedical Research, University of Delhi, India for providing the Discovery studio 4.0 client (licence version) software facilities. We are also thankful to L. M. College of Pharmacy, Ahmedabad for providing Schrodinger software facility. Authors are also thankful to Dr. John Georgee, CHRIST College, Rajkot for providing the Molegro Software facility. Authors are also thankful to Mr. Raghu and Mr. Vinod Devaraji, representatives of Schrodinger for their helps in MD study.

Disclosure statement

No potential conflict of interest was reported by the authors.

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