COVID-19 has caused over 7 million deaths worldwide. The virus binds to ACE2 receptors, and disease progression can trigger a cytokine storm, an intense inflammatory response linked to a higher mortality rate. Given the potential role of α7nAChR in modulating anti-inflammatory pathways, this study investigates its agonists and their interactions, integrating pharmacophore modeling for virtual screening of FDA-approved drugs. Initially, EVP-6124 was redocked into 7EKP to establish a docking protocol. Subsequently, the 7EKI model underwent a 100 ns MD simulation, followed by cluster analysis to identify the most representative conformation for docking EVP-6124. The best docking pose was then subjected to a 500 ns MD simulation until convergence. Pharmacophore models derived from representative conformations were validated using ROC curves, yielding scores above 0.8. These models guided the screening of FDA-approved compounds, with top candidates further evaluated via MD simulations. To do so, all results were docked using GOLD and evaluated with GoldScore, ChemScore, ChemPLP, and ASP scoring functions. For each function, 100 poses were generated and clustered within <2 Å. Representative clusters were rescored using GNINA, and the top-scoring pose was selected for MD simulation. While additional compounds remain under evaluation, this approach highlighted aclidinium as a potential ligand for α7nAChR, sustaining receptor interactions for up to 300 ns so far.