Computational Discovery of SARS-CoV-2 NSP 16 Drug Candidates Based on Pharmacophore Modeling and Molecular Dynamics Simulation

Non-Structural Protein 16 (NSP-16) is one of the most suitable targets for discovery of drugs for corona viruses including SARS-CoV-2. In this study, drug discovery of SARS-CoV-2 nsp-16 has been accomplished by pharmacophore-based virtual screening among some analogs (FDA approved drugs) and marine natural plants (MNP). The comparison of the binding energies and the inhibition constants was determined using molecular docking method. Three compounds including two FDA approved (Ibrutinib, Idelalisib) and one MNP (Kumusine) were selected for further investigation using the molecular dynamics simulations. The results indicated that Ibrutinib and Idelalisib are oral medications while Kumusine, with proper hydrophilic and solubility properties, is an appropriate candidate for nsp-16 inhibitor and can be effective to control COVID-19 disease. Drug discovery of SARS-CoV-2 nsp-16 has been accomplished by pharmacophore-based virtual screening among FDA approved drugs and marine natural plants (MNP). Based on molecular docking results Ibrutinib, Kumusine and Idelalisib demonstrated the highest binding. Kumusine can be considered as the best drug candidate due to the highest binding, the ability of destroying the secondary structure of the protein and its suitable ADMET properties.