In silico Identification of Potential Small Molecules Targeting Six Proteins in Nipah Virus using Molecular Docking, Pharmacophore and Molecular Dynamics Simulation

Abstract

Introduction: Nipah virus (NiV) is a highly pathogenic zoonotic virus of the genus Henipavirus, which causes severe respiratory illness and deadly encephalitis with a fatality rate of 50%-70 % in humans. A total of 16 NiV proteins are available in the Protein Data Bank (PDB) of which six proteins belong to the structural class. Method: In this study, a cluster of six proteins of classes Viral attachment glycoproteins (2VWD, 2VSM), Fusion glycoprotein (5EVM, 6PD4), Matrix protein (6BK6), and Phosphoprotein (4HEO) were considered as potential therapeutic targets. Here, 25 small molecule inhibitors were chosen which include 23 natural compounds with antiviral properties and 2 antiviral drug molecules as control. The potential inhibitors among the selected compounds were identified based on docking score, significant intermolecular interactions, ADME (absorption, distribution, metabolism, and excretion) properties, pharmacophore and toxicity studies. Moreover, 100 nanoseconds molecular dynamics simulation was carried out for the best selected compound with all protein targets to understand the stability and binding strength. Result and Discussion: In this study, we propose that the baicalin was found to be the most potential lead molecule with higher binding affinity, strong bonded interactions, favorable pharmacophore features and higher complex stability. Conclusion: Hence, the compound identified shall prove effective against the Nipah virus targeting the viral attachment glycoprotein.