Molecular docking and dynamics studies for the identification of Nipah virus glycoprotein inhibitors from Indian medicinal plants

Abstract

The infection by Nipah Virus (NiV), a zoonotic paramyxovirus, is fatal and several outbreaks have been reported in humans in various countries. No effective vaccines or drugs are developed till date to control this infection. The NiV-Glycoprotein (NiV-G) is one of the essential proteins for viral entry by binding to the Ephrin-B receptors. The present study screens the potential phytocompounds that can target NiV-G and thereby inhibit the viral entry to human. Computer-aided virtual screening of 1426 phytocompounds from various medicinal plants was carried out to investigate their efficacy as potential therapeutics. Ribavirin, the currently used drug, was also docked to compare the docking score and intermolecular interactions between ligand and target protein. Further, molecular dynamics simulations and MM-PBSA binding free energy calculations were performed to understand the stability of the docked complexes. Radius of gyrations and Solvent Accessible Surface Area were also performed to evaluate the compactness and solvent behaviour of ligand-receptor complexes during the 100 ns simulation. Our analysis revealed that the alkaloid, Serpentinine, has the highest potency to block NiV-G with favourable binding.

Communicated by Ramaswamy H. Sarma

Keywords:

• Nipah viral infection
• virtual screening
• Nipah viral therapeutics
• phytocompounds
• viral entry inhibitor

Acknowledgements

The authors thank Prof. P. R Sudhakaran (Department of Computational Biology and Bioinformatics, University of Kerala, India) for providing his valuable inputs throughout the study. The authors acknowledge the AICADD and DBT-BIF support for the Department of Computational Biology and Bioinformatics, University of Kerala, and Campus Computing Facility (CCF) at the Central Laboratory for Instrumentation and Facilitation, University of Kerala, India, for providing the necessary facilities to carry out this study.

Authors’ contributions

CSA designed the study. CSA and JMI performed the experiments. CSA and JMI analyzed the data. Manuscript written by CSA and edited by RR, TSKP, ASN and OVO. All authors read and approved the final manuscript

Disclosure statement

The authors declare no conflict of interest.

Additional information

Funding

This study was supported by the SIUCEB at the Department of Computational Biology and Bioinformatics, University of Kerala, India.