Abstract
Despite the intense worldwide efforts towards the identification of potential anti-CoV therapeutics, no antiviral drugs have yet been discovered. Numerous vaccines are now approved for use, but they all serve as preventative measures. To effectively treat viral infections, it is crucial to find new antiviral drugs that are derived from natural sources. Various compounds with potential activity against 3 chymotrypsin-like protease (3CLpro) were reported and some are validated by bioassay studies. Therefore, we performed the computational screening of phytoconstituents of Codonopsis lanceolata to search for potential antiviral hit candidates. The curated compounds of the plant C. lanceolata were collected and downloaded from the literature. The binding affinity of the curated datasets was predicted for the target 3CLpro. Stigmasterol exhibits the highest docking score for the 3CLpro target. In addition, molecular dynamics (MD) simulations were conducted for the validation of docking results using root mean square deviation and root mean square fluctuation plots. The MD results indicated that the docked complex was stable and retained hydrogen bonding and non-bonding interactions. Furthermore, the calculation of pharmacokinetic parameters and Lipinski’s rule of five suggest that C. lanceolata has the potential for drug-likeness. In order to develop new medicines for this debilitating disease, we will focus on the primary virus-based and host-based targets that can direct medicinal chemists to identify novel treatments to produce new drugs for it.
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The authors are thankful to B. N. College of Pharmacy for providing the computational facility for this research work.
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Sharma, G., Kumar, N., Sharma, C.S. et al. In silico guided screening of active components of C. lanceolata as 3-chymotrypsin-like protease inhibitors of novel coronavirus. 3 Biotech 13, 324 (2023). https://doi.org/10.1007/s13205-023-03745-2
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DOI: https://doi.org/10.1007/s13205-023-03745-2