Computational Simulation of Indonesian Natural Compounds as Mainprotease Inhibitors of SARS CoV 2

Abstract

The computational method provides an alternative approach for conducting screening of natural substances antiviral properties against the SARS-CoV-2 virus. This research focuses on the Main Protease, a target protein that plays a central role in viral replication by producing an enzyme that cleaves the host protein nuclear factor (NF)-κB in SARS-CoV-2. The study used a thousand natural compound structures from the Indonesian Natural Compound Database (Herbaldb), filtered based on the similarity of their pharmacophore features with Mainprotease inhibitors. In compounds with good pharmacophore properties, docking will be carried out to determine the binding affinity with the target protein and obtain the complex structure. The ADMETSAR test was used to determine the pharmacology and pharmacokinetics of the five best natural compounds. Finally, molecular dynamics simulation of the complex structure was performed to assess the stability of the best compound interactions with the SARS-CoV-2 Mainprotease. The compounds identified as Mainprotease inhibitors in this study were cosmosiin, glucobrassicin, and isobavachin.