Exploring the Potency of <i>Nigella sativa</i> Seed in Inhibiting SARS-CoV-2 Main Protease Using Molecular Docking and Molecular Dynamics Simulations

Abstract

Coronavirus disease (COVID-19) is a pandemic burdening the global economy. It is caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Black cumin (Nigella sativa) seed may contain antivirals for the disease since it was reported to inhibit the human immunodeficiency virus (HIV) and hepatitis C virus (HCV). Main protease (Mpro) is a vital protein for viral replication and a promising target for COVID-19 drug development. Hence, in this study, we intended to uncover the potency of N. sativa seed as the natural source of inhibitors for SARS-CoV-2 Mpro. We collected secondary metabolites in N. sativa seed through a literature search and employed Lipinski’s rule of five as the initial filter. Subsequently, virtual screening campaigns using a molecular docking method were performed, with N3 inhibitor and leupeptin as reference ligands. The top hits were analyzed further using a molecular dynamics simulation approach. Molecular dynamics simulations showed that binding affinities of nigellamine A2 and A3 to Mpro are comparable to that of leupeptin, with median values of -43.9 and -36.2 kcal mol–1, respectively. Ultimately, this study provides scientific information regarding N. sativa seeds’ potency against COVID-19 and helps direct further wet experiments.

Bioinformatics Study of Flavonoids From Genus Erythrina As Ace2 inhibitor Candidates For Covid-19 Treatment

“…From the molecular docking result, compound 310 is predicted to have lower binding energy toward ACE2 than compound 471 ( Table 1 ), whereas the molecular dynamics simulation suggested the opposite (−15.9612 ± 1.9765 and −18.1921 ± 2.6197 kcal/mol respectively for compounds 310 and 471, expressed as median ± SD) The difference of binding energy value obtained from molecular docking and MD simulation may due to the ability of MD simulation to accommodate complete flexibility of ligand and protein, therefore allowing intermolecular interaction adjustment. 18 , 22

Figure 1 Comparative ΔG MMGBSA profiles for compounds 310 and 471 every 10 ns over 100 ns simulation time. Compound 310 shows relatively stable free energy values around −16 Kcal/mol, whereas compound 471 exhibits more fluctuation, indicating differing stabilities in their interactions with the target.

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“…The method is considered valid if the root mean square deviation (RMSD) is less than 2.00 Å. 18 , 22 …”

“…From the molecular docking result, compound 310 is predicted to have lower binding energy toward ACE2 than compound 471 (Table 1), whereas the molecular dynamics simulation suggested the opposite (−15.9612 ± 1.9765 and −18.1921 ± 2.6197 kcal/mol respectively for compounds 310 and 471, expressed as median ± SD) The difference of binding energy value obtained from molecular docking and MD simulation may due to the ability of MD simulation to accommodate complete flexibility of ligand and protein, therefore allowing intermolecular interaction adjustment. 18,22 In addition to the MMGBSA free energy calculation, we also conducted RMSD calculations to evaluate the ACE2 protein stability upon the binding of compounds 310 and 471. The RMSD profile (Figure 2) of the Cα atoms remained stable at average value of 1.59 ± 0.22 Å with interquartile range (IQR) of 0.25 Å for 310-ACE2 complex and 1.65 ± 0.19 Å (IQR 0.23 Å) for 310-ACE2 complex.…”

Unveiling the Anti-Cancer Potential of Onoceranoid Triterpenes from Lansium domesticum Corr. cv. kokosan: An In Silico Study against Estrogen Receptor Alpha

“…Before subjecting all onoceranoid triterpenes to molecular docking, we performed a redocking procedure using the complex of ERα and 4-hydroxy tamoxifen (4OHT) with a PDB code, 3ERT. Such a procedure warrants the finding of global minimum using the stochastic search method during molecular docking, which eventually minimizes errors [36]. Redocking such an active form of tamoxifen to ERα produces a hundred poses.…”

“…kokosan. However, molecular docking uses a rigid receptor, which does not account for the flexibility of the protein-ligand complex [36,44]. This rigidity can restrict the sampling of both ligand and receptor conformations, potentially affecting pose prediction accuracy.…”