Molecular docking and dynamics study of natural compound for potential inhibition of main protease of SARS-CoV-2

Abstract

Newly emerged SARS-CoV-2 made recent pandemic situations across the globe is accountable for countless unwanted death and insufferable panic associated with co-morbidities among mass people. The scarcity of appropriate medical treatment and no effective vaccine or medicine against SARS-CoV-2 has turned the situation worst. Therefore, in this study, we made a deep literature review to enlist plant-derived natural compounds and considered their binding mechanism with the main protease of SARS-CoV-2 through combinatorial bioinformatics approaches. Among all, a total of 14 compounds were filtered where Carinol, Albanin, Myricetin were had better binding profile than the rest of the compounds with having binding energy of-8.476,-8.036,-8.439 kcal/mol, respectively. Furthermore, MM-GBSA calculations were also considered in this selection process to support docking studies. Besides, 100 ns molecular dynamics simulation endorsed the rigid nature, less conformational variation and binding stiffness. As this study, represents a perfect model for SARS-CoV-2 main protease inhibition through bioinformatics study, these potential drug candidates may assist the researchers to find a superior and effective solution against COVID-19 after future experiments.

Virtual screening and molecular dynamics simulation study of plant-derived compounds to identify potential inhibitors of main protease from SARS-CoV-2

“…The Glide program and its virtual screening workflow process were applied, including three docking protocols; high throughput virtual screening or HTVS, Standard Precision or SP module, and Extra Precision or XP module [ 35 , 36 ]. To obtain the best compounds, we follow the previous literature as earlier published [ 37 ]. The HTVS was used to dock each ligand to the receptor, which generates one pose.…”

Efficacy of Phytochemicals Derived from Avicennia officinalis for the Management of COVID-19: A Combined In Silico and Biochemical Study

“…Computer-aided drug designing involves the generation of an artificial environment that can simulate the environment found in the human body [ 31 ], which can be used to examine the interactions between a target protein and bioactive compounds under simulated physiological conditions in a time-saving and cost-effective manner. In our investigation, both in vitro and in silico analyses were used to identify the top candidate phytochemicals derived from A. officinalis with the potential to inhibit SARS-CoV-2 M pro active sites, and molecular dynamics studies were performed to predict the formation of probable ligand-receptor complexes with optimized conformations [ 32 ].…”

Structure-Based Designing, Solvent Less Synthesis of 1,2,3,4-Tetrahydropyrimidine-5-carboxylate Derivatives: A Combined In Vitro and In Silico Screening Approach

“…The average RMSD descriptor of all the docked compounds were calculated to corroborate their stability in biological system [ 28 , 29 , 30 ]. As the justified threshold for RMSD calculation is 2 Å, its mean average RMSD value of all the complexes less than this threshold provides us with the proof that our docking process is validated, as having RMSD for anti-cancer docking protocol 2.0 Å, for anti-diabetic 1.35 Å and for anti-oxidant 0.71 Å [ 31 , 32 , 33 , 34 ].…”