Structure-Based Virtual Screening and Molecular Dynamics Investigation of Natural Bioactive Compounds Against SARS-CoV-2 Proteins

The continuous emergence of SARS-CoV-2 variants necessitates the identification of effective multi-target antiviral agents with enhanced stability and binding efficiency. This study employed an integrated computational approach, including molecular docking, molecular dynamics (MD) simulations, free energy landscape (FEL) analysis, and Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) calculations, to evaluate the inhibitory potential of twenty natural compounds against SARS-CoV-2 proteins 7XJW, 8DRW, and 9PFH. Molecular docking identified Amentoflavone as the most promising candidate, exhibiting strong binding affinities toward all targets through favorable hydrogen-bond and hydrophobic interactions within the active sites. Interaction analysis revealed that its biflavonoid scaffold promoted extensive ligand–protein complementarity through hydroxyl and aromatic functional groups. MD simulations demonstrated stable protein-ligand complexes, characterized by low fluctuations in RMSD, RMSF, SASA, and radius of gyration values throughout the 100 ns trajectories. Persistent hydrogen-bond interactions further supported complex stability. FEL analysis revealed compact low-energy conformational basins, indicating thermodynamically favorable binding states. MM-PBSA calculations confirmed favorable binding free energies primarily driven by van der Waals and electrostatic contributions, with the 7XJW-Amentoflavone complex exhibiting the most favorable energetic profile. Overall, these findings highlight Amentoflavone as a promising multi-target inhibitor and potential lead compound for future antiviral drug development and experimental validation against SARS-CoV-2.