Peptide-like and small-molecule inhibitors against Covid-19

Abstract

Coronavirus disease strain (SARS-CoV-2) was discovered in 2019, and it is spreading very fast around the world causing the disease Covid-19. Currently, more than 1.6 million individuals are infected, and several thousand are dead across the globe because of Covid-19. Here, we utilized the in-silico approaches to identify possible protease inhibitors against SARS-CoV-2. Potential compounds were screened from the CHEMBL database, ZINC database, FDA approved drugs and molecules under clinical trials. Our study is based on 6Y2F and 6W63 co-crystallized structures available in the protein data bank (PDB). Seven hundred compounds from ZINC/CHEMBL databases and fourteen hundred compounds from drug-bank were selected based on positive interactions with the reported binding site. All the selected compounds were subjected to standard-precision (SP) and extra-precision (XP) mode of docking. Generated docked poses were carefully visualized for known interactions within the binding site. Molecular mechanics-generalized born surface area (MM-GBSA) calculations were performed to screen the best compounds based on docking scores and binding energy values. Molecular dynamics (MD) simulations were carried out on four selected compounds from the CHEMBL database to validate the stability and interactions. MD simulations were also performed on the PDB structure 6YF2F to understand the differences between screened molecules and co-crystallized ligand. We screened 300 potential compounds from various databases, and 66 potential compounds from FDA approved drugs. Cobicistat, ritonavir, lopinavir, and darunavir are in the top screened molecules from FDA approved drugs. The screened drugs and molecules may be helpful in fighting with SARS-CoV-2 after further studies. ARTICLE HISTORY

A molecular modeling approach to identify effective antiviral phytochemicals against the main protease of SARS-CoV-2

“…Finally, MD simulation was performed for 100 ns long and snapshots were saved at every 100 ps into MD trajectory for further analysis. Root-mean-square deviation (RMSD), rootmean-square fluctuation (RMSF), radius of gyration (Rg), solvent accessible surface area (SASA), and total number of Hbond count were calculated from the MD simulations similar to other studies (Elfiky & Azzam, 2020;Enayatkhani et al, 2020;Muralidharan et al, 2020;Pant et al, 2020).…”

SARS-CoV-2 RNA dependent RNA polymerase (RdRp) targeting: anin silicoperspective

“…(Doublie & Ellenberger, 1998;Elfiky, 2020a;Elfiky & Ismail, 2018). Several studies are suggesting the effectiveness of different anti-viral drugs and compounds against the coronavirus proteins (Aanouz et al, 2020;Boopathi et al, 2020;Elfiky & Azzam, 2020;Elmezayen et al, 2020;Enayatkhani et al, 2020;Gupta et al, 2020;Khan et al, 2020aKhan et al, , 2020bMuralidharan et al, 2020;Pant et al, 2020;Sarma et al, 2020).…”

An investigation into the identification of potential inhibitors of SARS-CoV-2 main protease using molecular docking study

“…Among all the treatment strategies, the uses of already known viral medications have great advantages as the pharmacokinetics, pharmacodynamics, and safety profiles of these drugs have already been established. This drug repurposing strategy has gained significance as they are expected to be faster with less investment (Fitchett et al, 2014;Law et al, 2013;Pant et al, 2020;Park, 2019). Preliminary studies revealed Lopinavir/ritonavir combined therapy as a potential inhibitor of the virus.…”