Molecular simulation of compounds from n-hexane fraction of Sonchus arvensis L. leaves as SARS-CoV-2 antiviral through inhibitor activity targeting strategic viral protein

Abstract

Context: COVID-19 was caused by the spread and transmission of SARS-CoV-2 at the end of 2019 until now. The problem comes when antiviral drugs have not yet been found and patients infected with SARS-CoV-2 can trigger a cytokine storm condition due to the effects of viral replication. Indonesia has various kinds of medicinal plants, such as Sonchus arvensis L., which are used as medicinal plants. Aims: To analyze the activity of the inhibitor as SARS-CoV-2 antiviral agents from n-hexane fractions of S. arvensis leaves. Methods: The sample was collected from GC-MS analysis, PubChem, and Protein Databank database, then drug-likeness identification using Lipinski Rule of Five server and bioactive prediction of bioactive compounds as inhibitor activity was conducted by Molinspiration server. Furthermore, the docking simulation was performed using PyRx 0.9.9 software to determine the binding activity, molecular interaction by Discovery Studio software to identify position and interaction type, 3D molecular visualization by PyMol 2.5. software, and dynamic by CABS-flex 2.0 server to predict interaction stability. Results: α-Amyrin and β-amyrin from n-hexane fractions of S. arvensis leaves had activity as SARS-CoV-2 inhibitors through interactions on helicase, RdRp, Mpro, and RBD-Spike, both compounds had more negative binding affinity than control drug and can produce stable chemical bond interactions in the ligand-protein complexes. However, the results were merely computational, so they must be validated through an in vivo and in vitro research approach. Conclusions: Sonchus arvensis L. leaves were predicted to have SARS-CoV-2 antiviral through inhibitor activity by α-amyrin and β-amyrin.

Keywords

• antiviral
• bioinformatics
• sars-cov-2
• sonchus arvensis l.