Molecular Dynamics Simulation of Fusion Inhibitors Targeting SARS-Cov-2 Entry Pathways
Abstract
Molecular dynamics (MD) simulations are critical in drug design for evaluating the stability of protein-ligand interactions under physiological conditions. In this study, MD simulations were used to analyze the behavior and binding stability of two fusion inhibitors, Happy_00 and Happy_06, targeting the SARS-CoV-2 spike protein cleavage sites. These inhibitors were designed to block the action of TMPRSS2, a key enzyme facilitating viral entry. The simulations were conducted using the GROMACS 2021.3 package, with systems solvated using the TIP3P water model and neutralized with sodium ions. Energy minimization, followed by NVT (constant volume) and NPT (constant pressure) equilibration, ensured the system’s stability before running the production MD for 50 nanoseconds. Visualization tools, including PyMol and VMD, were used to analyze simulation trajectories. Key metrics such as Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF), and Radius of Gyration (Rg) were computed to assess structural stability and flexibility. RMSD values remained consistent (~2.5 Å), indicating minimal deviation from the initial docked conformations. RMSF analysis revealed that Happy_06 exhibited greater flexibility due to its linkers, allowing better adaptation to dynamic protein surfaces. Rg data confirmed the inhibitors maintained their compact structures throughout the simulation. These results suggest that both inhibitors can stably bind SARS-CoV-2 spike cleavage sites, with Happy_06 demonstrating enhanced flexibility and potential for deeper site interaction. This study highlights the utility of MD simulations in evaluating drug candidates, offering insights for future experimental validation of these inhibitors as antiviral therapeutics.
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