Natural inhibitors of SARS-CoV-2 main protease: structure based pharmacophore modeling, molecular docking and molecular dynamic simulation studies
- PMID: 36031629
- PMCID: PMC9420677
- DOI: 10.1007/s00894-022-05286-6
Natural inhibitors of SARS-CoV-2 main protease: structure based pharmacophore modeling, molecular docking and molecular dynamic simulation studies
Abstract
Main protease (Mpro) plays a key role in replication of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This study was designed for finding natural inhibitors of SARS-CoV-2 Mpro by in silico methods. To this end, the co-crystal structure of Mpro with telaprevir was explored and receptor-ligand pharmacophore models were developed and validated using pharmit. The database of "ZINC Natural Products" was screened, and 288 compounds were filtered according to pharmacophore features. In the next step, Lipinski's rule of five was applied and absorption, distribution, metabolism, excretion, and toxicity (ADMET) of the filtered compounds were calculated using in silico methods. The resulted 15 compounds were docked into the active site of Mpro and those with the highest binding scores and better interaction including ZINC61991204, ZINC67910260, ZINC61991203, and ZINC08790293 were selected. Further analysis by molecular dynamic simulation studies showed that ZINC61991203 and ZINC08790293 dissociated from Mpro active site, while ZINC426421106 and ZINC5481346 were stable. Root mean square deviation (RMSD), radius of gyration (Rg), number of hydrogen bonds between ligand and protein during the time of simulation, and root mean square fluctuations (RMSF) of protein and ligands were calculated, and components of binding free energy were calculated using the molecular mechanic/Poisson-Boltzmann surface area (MM/PBSA) method. The result of all the analysis indicated that ZINC61991204 and ZINC67910260 are drug-like and nontoxic and have a high potential for inhibiting Mpro.
Keywords: Docking; Molecular dynamic simulation; Mpro; Natural inhibitor; Pharmacophore modelling.
© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
Conflict of interest statement
The authors declare no competing interests.
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