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Research Articles

Traditional herbal compounds as candidates to inhibit the SARS-CoV-2 main protease: an in silico study

, , , , ORCID Icon & ORCID Icon
Pages 1603-1616 | Received 28 Sep 2021, Accepted 22 Dec 2021, Published online: 04 Jan 2022
 

Abstract

COVID-19, a disease caused by the SARS-CoV-2 virus, is responsible for a pandemic since March 2020 and it has no cure. Therefore, herein, different theoretical methods were used to obtain potential candidates from herbal compounds to inhibit the SARS-CoV-2 main protease (Mpro). Initially, the 16 best-scored compounds were selected from a library containing 4066 ligands using virtual screening by molecular docking. Among them, six molecules (physalin B 5,6-epoxide (PHY), methyl amentoflavone (MAM), withaphysalin C (WPC), daphnoline or trilobamine (TRI), cepharanoline (CEP) and tetrandrine (TET)) were selected based on Lipinski’s rule and ADMET analysis as criteria. These compounds complexed with the Mpro were submitted to triplicate 100ns molecular dynamics simulations. RMSD, RMSF, and radius of gyration results show that the overall protein structure is preserved along the simulation time. The average ΔGbinding values, calculated by the MM/PBSA method, were −41.7, −55.8, −45.2, −38.7, −49.3, and −57.9kcal/mol for the PHY-Mpro, MAM-Mpro, WPC-Mpro, CEP-Mpro, TRI-Mpro, and TET-Mpro complexes, respectively. Pairwise decomposition analyses revealed that the binding pocket is formed by His41-Val42, Met165-Glu166-Leu167, Asp187, and Gln189. The PLS regression model generated by QSPR analysis indicated that non-polar and polar groups with the presence of hydrogen bond acceptors play an important role in the herbal compounds-Mpro interactions. Overall, we found six potential candidates to inhibit the SARS-CoV-2 Mpro and highlighted key residues from the binding pocket that can be used for future drug design.

Communicated by Ramaswamy H. Sarma

Acknowledgments

This research was carried out with the support of the IFSULDEMINAS/IFSP 01/2021. Also, the computing support of the Ohio Supercomputer Center (OSC, 1987) was used.

Disclosure statement

No potential conflict of interest was reported by the authors.

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