A computational biology approach for the identification of potential SARS-CoV-2 main protease inhibitors from natural essential oil compounds

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has fomented a climate of fear worldwide due to its rapidly spreading nature, and high mortality rate. The World Health Organization (WHO) declared it as a global pandemic on 11th March, 2020. Many endeavors have been made to find appropriate medications to restrain the SARS CoV-2 infection from spreading but there is no specific antiviral therapy to date. However, a computer-aided drug design approach can be an alternative to identify probable drug candidates within a short time. SARS-CoV-2 main protease is a proven drug target, and it plays a pivotal role in viral replication and transcription. Methods: In this study, we identified a total of 114 essential oil compounds as a feasible anti-SARS-CoV-2 agent from several online reservoirs. These compounds were screened by incorporating ADMET profiling, molecular docking, and 50 ns of molecular dynamics simulation to identify potential drug candidates against the SARS-CoV-2 main protease. The crystallized SARS-CoV-2 main protease structure was collected from the RCSB PDB database (PDB ID 6LU7). Results: According to the results of the ADMET study, none of the compounds have any side effects that could reduce their druglikeness or pharmacokinetic properties. Out of 114 compounds, we selected bisabololoxide B, eremanthin, and leptospermone as our top drug candidates based on their higher binding affinity scores, and strong interaction with the Cys 145-His 41 catalytic dyad. Finally, the molecular dynamics simulation was implemented to evaluate the structural stability of the ligand-receptor complex. MD simulations disclosed that all the hits showed conformational stability compared to the positive control α-ketoamide. Conclusions: Our study showed that the top three hits might work as potential anti-SARS-CoV-2 agents, which can pave the way for discovering new drugs, but for experimental validation, they will require more in vivo trials.