SARS-CoV-2-Main Protease Inhibitor by the Active Alkaloid: An in silico Molecular Docking and Dynamic Approach
The rampant outbursts of alpha, beta, gamma, delta, omicron, and their subvariants were so vehement that the millions of dramatic deaths forced us to think about a potential inhibitor against SARS-CoV-2 main protease in the future. In the present research work, we have searched bioactive compounds from Withania somnifera, Ocimum sanctum, and Tinospora cordifolia to inhibit the replication of main protease Mpro through in-silico molecular docking and dynamic approach. The ADMET evaluation was applied to confirm the absorption, distribution, metabolism, excreation, and toxicity parameters based on Lipinski’s rule of five. The free energy change for the Withanone docked complex is found -8.50 Kcal/mol, -7.82 Kcal/mol for Tetrahydropalmatine, -7.77 Kcal/mol for Isocolumbin and -7.50 Kcal/mol for Magnoflorine. Similarly, their RMSD and RMSF spectra are more stable than the main protease inhibitory capacity of Dexamethasone, Chloroquine, and Remdesivir prescribed in SARS- CoV-2. The docked complex of the main protease with Withanone is a very strong and stable with conventional hydrogen bonding of bond lengths 1.76 Å (ARG A: 105), and 2.16 Å (GLN A: 107). The molecular dynamic results revealed that the docked complex is stable up to 100 ns for RMSD, and 10 ns running for RMSF. The finding shows that the inhibitory potential of Withanone, Tetahydropalmatine, Isocolumbin, and Magnoflorine are comparatively high for SARS-CoV-2, and can be effectively used against SARS-CoV-2 infection without side effects. Based on the investigation, it could be recommended that further tests and trials are required to confirm the efficacy of the drug.
Authors
- Sahadeb Prasad Dhungana (ORCID: https://orcid.org/0000-0003-3071-8710)
- Ram Prasad Baral (ORCID: https://orcid.org/0009-0006-0602-4830)
- Rameshwar Adhikari (ORCID: https://orcid.org/0000-0002-7350-0204)
- Shukra Raj Regmi
- Padam Raj Joshi
- Nurul Hoda Khan
- Narendra Prakash Shawd
Institutions
- Central Statistical Office (ZM)
- Tribhuvan University (NP)
Publication Details
- Journal
- Journal of Physical and Life Sciences
- Published
- 2024-12-31
- DOI
- https://doi.org/10.3126/jopls.v1i1.78984
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00