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Pharmacophore based virtual screening, molecular docking, molecular dynamics and MM-GBSA approach for identification of prospective SARS-CoV-2 inhibitor from natural product databases.

ABSTRACT: COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) primarily appeared in Wuhan, China, in December 2019. At present, no proper therapy and vaccinations are available for the disease, and it is increasing day by day with a high mortality rate. Pharmacophore based virtual screening of the selected natural product databases followed by Glide molecular docking and dynamics studies against SARS-CoV-2 main protease was investigated to identify potential ligands that may act as inhibitors. The molecules SN00293542 and SN00382835 revealed the highest docking score of -14.57 and -12.42 kcal/mol, respectively, when compared with the co-crystal ligands of PDB-6Y2F (O6K) and 6W63 (X77) of the SARS-CoV-2 M^pro. To further validate the interactions of top scored molecules SN00293542 and SN00382835, molecular dynamics study of 100 ns was carried out. This indicated that the protein-ligand complex was stable throughout the simulation period, and minimal backbone fluctuations have ensued in the system. Post-MM-GBSA analysis of molecular dynamics data showed free binding energy-71.7004 +/- 7.98, -56.81+/- 7.54 kcal/mol, respectively. The computational study identified several ligands that may act as potential inhibitors of SARS-CoV-2 M^pro. The top-ranked molecules SN00293542, and SN00382835 occupied the active site of the target, the main protease like that of the co-crystal ligand. These molecules may emerge as a promising ligands against SARS-CoV-2 and thus needs further detailed investigations. Communicated by Ramaswamy H. Sarma.

SUBMITTER: Kumar BK

PROVIDER: S-EPMC7544939 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Pharmacophore based virtual screening, molecular docking, molecular dynamics and MM-GBSA approach for identification of prospective SARS-CoV-2 inhibitor from natural product databases.

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