Unravelling the influenza virus inhibitory potential: Ligand-based docking, pharmacophore, MM-GBSA, and molecular dynamic simulation of phytochemicals and cyanobacteria metabolites

Abstract

Viral outbreaks facilitated by global travel and modernity pose significant threats to global health. Influenza viruses, particularly α-influenza and β-influenza strains, have been plaguing human populations since time immemorial. Despite their long-standing impact, effective drugs are yet to be developed, and co-infection with these viruses can lead to severe health complications. In light of these challenges, this study aimed to investigate the potential antiviral molecules sourced from cyanobacteria and herbs. We conducted virtual screening using ligand-based docking to identify potential phytochemicals and cyanobacterial metabolites as candidates for further evaluation. Subsequently, pharmacophore modeling was employed to validate the binding modes of the selected compounds, followed by MM-GBSA calculations to assess their binding affinities and stabilities within the viral target. Among the molecules investigated, the cyanobacterial compound Symplocamide A (-8.042) demonstrated notable outcomes in docking than the herb molecules in the docked ligand. This finding suggests its potential as a therapeutic agent against influenza A virus proteins. Additionally, cyanobacterial molecules such as Lyngbyastatins 3 (-8.001), Lyngbyastatin G1 (-7.501), and Kempenopeptide (-6.128) exhibit stronger binding affinities and more potent docking scores, making them promising candidates for targeting viral proteins in potential therapeutic applications. The present study reveals the possibility of harnessing cyanobacterial molecules as novel antiviral agents against influenza viruses. Ultimately, we believe that this research will serve as a stepping stone in the quest for innovative drugs to combat respiratory diseases caused by viral infections.

Keywords

Influenza A virus / Phytochemicals / Cyanobacteria metabolites / Molecular docking / Pharmacophore / MM-GBSA / MD simulations

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