Discovery of Potential Antiviral Compounds against Hendra Virus by Targeting Its Receptor-Binding Protein (G) Using Computational Approaches

Abstract

Hendra virus (HeV) belongs to the paramyxoviridae family of viruses which is associated with the respiratory distress, neurological illness, and potential fatality of the affected individuals. So far, no competitive approved therapeutic substance is available for HeV. For that reason, the current research work was conducted to propose some novel compounds, by adopting a Computer Aided Drug Discovery approach, which could be used to combat HeV. The G attachment Glycoprotein (Ggp) of HeV was selected to achieve the primary objective of this study, as this protein makes the entry of HeV possible in the host cells. Briefly, a library of 6000 antiviral compounds was screened for potential drug-like properties, followed by the molecular docking of short-listed compounds with the Protein Data Bank (PDB) structure of Ggp. Docked complexes of top two hits, having maximum binding affinities with the active sites of Ggp, were further considered for molecular dynamic simulations of 200 ns to elucidate the results of molecular docking analysis. MD simulations and Molecular Mechanics Energies combined with the Generalized Born and Surface Area (MMGBSA) or Poisson–Boltzmann and Surface Area (MMPBSA) revealed that both docked complexes are stable in nature. Furthermore, the same methodology was used between lead compounds and HeV Ggp in complex with its functional receptor in human, Ephrin-B2. Surprisingly, no major differences were found in the results, which demonstrates that our identified compounds can also perform their action even when the Ggp is attached to the Ephrin-B2 ligand. Therefore, in light of all of these results, we strongly suggest that compounds (S)-5-(benzylcarbamoyl)-1-(2-(4-methyl-2-phenylpiperazin-1-yl)-2-oxoethyl)-6-oxo-3,6-dihydropyridin-1-ium-3-ide and 5-(cyclohexylcarbamoyl)-1-(2-((2-(3-fluorophenyl)-2-methylpropyl)amino)-2-oxoethyl)-6-oxo-3,6-dihydropyridin-1-ium-3-ide could be considered as potential therapeutic agents against HeV; however, further in vitro and in vivo experiments are required to validate this study.

Targeting the RBD of Omicron Variant (B.1.1.529) with Medicinal Phytocompounds to Abrogate the Binding of Spike Glycoprotein with the hACE2 Using Computational Molecular Search and Simulation Approach

“…Post-Simulation Validation of the Top Hits 2.5.1. The Binding Free Energy Calculations For the estimation of the binding free energies of various biological complexes such as protein-DNA/RNA or protein-protein, the MMGBSA is the most authentic approach used in different research investigations [34][35][36][37][38]. In the present study, the script MMPBSA.py was used to calculate the binding free energy of the protein-ligand complexes by considering 2500 snapshots.…”

Integrated computer-aided drug design and biophysical simulation approaches to determine natural anti-bacterial compounds for Acinetobacter baumannii

“…As traditional drug discovery process is time consuming and costly, bioinformatics approaches are gaining great attention to identify novel drug targets that are specific and selective against bacterial pathogens 17 – 19 . As an example, using bioinformatics techniques seven metabolic pathway enzymes and 15 non-homologous membrane proteins were discovered as promising antibacterial targets against Staphylococcus aureus 20 .…”

“…Telithromycin, a third-generation ketolide antibiotic, was identified by Andrade and coworkers as a specific antibacterial molecule against bacterial resistant strains 23 . In short, lead compounds can be screened by combine applications of computer aided drug designing and using knowledge of medicinal chemistry for accumulating structure activity information to facilitate the development of next-generation of antibiotics 17 , 19 , 24 .…”

Computational exploration of maternal embryonic leucine zipper kinase (MELK) as a cancer drug target

“…Traditional drug discovery is a very slow process and consume significant cost and human efforts ( Ahmad et al, 2022 , Menchaca et al, 2020 ). In contrast, computer aided drug designing is fast and is cost effective in screening new drug molecules against any given biological macromolecule ( Islam et al, 2022 , Yu and MacKerell, 2017 ).…”