ABSTRACT
SARS-CoV-2 has caused a global COVID-19 pandemic since late 2019 and the reported cases have not ended until now. One way to overcome the Covid-19 pandemic is to find the main viral protease inhibitor (Mpro) SARS-CoV-2 which is a key enzyme of virus replication. Honey is a bee-derived product that contains various phenolic compounds and has antiviral activity. This study aimed to find candidate Mpro SARS-CoV-2 inhibitors from honey phenolic compounds using molecular docking simulations in a directed manner. A total of 27 test ligands (from honey's phenolic compounds), 4 comparison ligands (from synthetic antiviral compounds), and reference ligands (N3 compound) were screened for their character as drug compounds by Lipinski's rules and for their toxicity by admetSAR. All ligands were docked to the Mpro SARS-CoV-2 receptor code 7BQY using AutoDock Tools 1.5.6 and Autodock Vina with center of coordinates: X = 10,398;Y = -1,254;Z = 23.473 and grid size: X = 40;Y = 46;Z = 40. Molecular docking simulation produces affinity energy and molecular interactions data. The results showed that the best candidate for Mpro SARS-CoV-2 inhibitor from honey's phenolic compounds was genistein because it complied with all Lipinski rules, was non-toxigenic, not a carcinogen, had an affinity energy of -7.6 kCal/mol, 80% similarity to the reference ligand N3, and occupies 63,64% of the tether coverage area. The results of this study are expected to be used in further research, both in vitro and in vivo.
ABSTRACT
COVID-19, caused by SARS-CoV-2, has become a massive worldwide concern of the 21st century. One potential strategy to block the biochemical pathway of SARS-CoV-2 was by inhibiting the main protease (Mpro), which is a key enzyme on viral replication. Black seed (Nigella sativa L.) has a long history for its use as a traditional medicine. Therefore, we hypothesised that the black seed contains numerous active compounds that could potentially confer inhibitory activity against SARS-CoV-2 viral Mpro. In this study, 24 active compounds from black seed were tested. Compounds were screened using Lipinski's Rules and admetSAR, then docked to viral Mpro 7BQY by AutoDockTools-1.5.6 and AutoDock Vina using a site directed docking approach resulting in affinity energy (Delta G) and binding data. We found that the most potential active compound of N. sativa is 3-[(4-Methylphenyl)sulfanyl]-1,3-diphenyl-1-propanone, since its affinity energy was -7.6 kCal.mol(-1). Its similarity to N3 inhibitor based on Ligplot analysis and DS were 86.7% and 76.19%, respectively, and the occupancy on binding site based on Ligplot analysis and DS were 90.91% and 81.82%, respectively. These findings can be used as a starting point for further investigation using in vitro and in vivo studies.