In-Silico Analysis to Identify Potential Inhibitors Against the Protein NSP12 of SARS-CoV-2

In-Silico Analysis to Identify Potential Inhibitors Against the Protein NSP12 of SARS-CoV-2

Hima Vyshnavi, Gayathri S. S., Shahanas Naisam, Suvanish Kumar, Nidhin Sreekumar
Copyright: © 2021 |Pages: 13
DOI: 10.4018/IJQSPR.2021070104
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Abstract

In this pandemic condition, a drug candidate which is effective against COVID-19 is very much desired. This study initiates an in silico analysis to screen small molecules such as phytochemicals, drug metabolites, and natural metabolites against Nsp12 (a catalytic unit for RNA transcription and replication). Molecular interaction analysis of 6M71 was carried out against 2,860 ligands using Schrodinger Glide software. After docking analysis, the top 10 molecules (Glide score) were subjected to MD simulation for validating the stability. It resulted in top 10 compounds with high binding affinities with the target molecule NSP 12. Out of these, top 3 compounds including PSID_08_LIG3 (HMDB0133544), PSID_08_LIG4 (HMDB0132898), and PSID_08_LIG9 (HMDB0128199) show better Glide scores, better H-bond interaction, better MMGBSA value and stability on dynamic simulation after analysis of the results. The suggested ligands can be postulated as effective antiviral drugs against COVID-19. Further in vivo analysis is needed for validating the drug efficacy.
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Materials And Methods

Identification of Ligand

A total of 19,016 ligands were initially considered for the study. Among these, 5100 were phytochemicals, 2523 were drug metabolites and 1193 were natural metabolites. The SDF structure of phytochemicals, drug metabolites, and natural metabolites were retrieved from PubChem (https://hmdb.ca/) respectively.

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