Nigelladine A among Selected Compounds from Nigella sativa Exhibits Propitious Interaction with Omicron Variant of SARS-CoV-2: An In Silico Study

COVID-19 has been a threat to the entire world for more than two years since its outbreak in December 2019 in Wuhan city of China. SARS-CoV-2, the causative agent, had been reported to mutate over time exposing new variants. To date, no impeccable cure for the disease has been unveiled. This study outlines an extensive in silico approach to scrutinize certain phytochemical compounds of Nigella sativa (mainly the black cumin seeds) targeting the spike protein and the main protease (M(pro)) enzyme of the Omicron variant of SARS-CoV-2. The objective of this study is to investigate the extracted compounds with a view to developing a potential inhibitor against the concerned SARS-CoV-2 variant. The investigation contemplates drug-likeness analysis, molecular docking study, ADME and toxicity prediction, and molecular dynamics simulation which have been executed to elucidate different phytochemical and pharmacological properties of the tested compounds. Based on drug-likeness parameters, a total of 96 phytochemical compounds from N. sativa have been screened in the study. Interestingly, Nigelladine A among the compounds exhibited the highest docking score with both the targets with the same binding affinity which is −7.8 kcal/mol. However, dithymoquinone, kaempferol, Nigelladine B, Nigellidine, and Nigellidine sulphate showed mentionable docking scores. Molecular dynamics up to 100 nanoseconds were simulated under GROMOS96 43a1 force field for the protein-ligand complexes exhibiting the top-docking score. The root mean square deviations (RMSD), root mean square fluctuations (RMSF), radius of gyration (Rg), solvent accessible surface area (SASA), and the number of hydrogen bonds have been evaluated during the simulation. From the findings, the present study suggests that Nigelladine A showed the most promising results among the selected molecules. This framework, however, interprets only a group of computational analyses on selected phytochemicals. Further investigations are required to validate the compound as a promising drug against the selected variant of SARS-CoV-2.