Molecular dynamics simulation approach for discovering potential inhibitors against SARS-CoV-2: A structural review

Abstract

Since the commencement of the novel Coronavirus, the disease has quickly turned into a worldwide crisis so that there has been growing attention in discovering possible hit compounds for tackling this pandemic. Discovering standard treatment strategies is a serious challenge because little information is available about this emerged infectious virus. Regarding the high impact of time, applying computational procedures to choose promising drugs from a catalog of licensed medications provides a precious chance for combat against the life-threatening disorder of COVID-19. Molecular dynamics (MD) simulation is a promising approach for assessing the binding affinity of ligand-receptor as well as observing the conformational trajectory of docked complexes over time. Given that many computational studies are performed using MD along with the molecular docking on various candidates as antiviral inhibitors of COVID-19 protease, there is a demand to conduct a comprehensive review of the most important studies to reveal and compare the potential introduced agents that this study covers this defect. In this context, the present review intends to prepare an overview of these studies by considering RMSD, RMSF, radius of gyration, binding free energy, and Solvent-Accessible Surface Area (SASA) as effective parameters for evaluation. The outcomes will offer a road map for adjusting antiviral inhibitors, which can facilitate the selection and development of drug candidates for use in the medical therapy. Finally, the molecular modeling approaches rendered by this study may be valuable for future computational studies.

Keywords: COVID-19; Coronavirus main protease; Drug discovery; MD simulations; SARS‐CoV‐2.

Fig. 1

Average value of RMSD of high score agents corresponding to the SARS-CoV-2 main protease , , , , .

Fig. 2

The RMSF plot of docked complex of MolPort-002-530-156, Remdesivir and 6LU7-D1-P-D2 , , .

Fig. 3

Average value of radius of gyration (Rg) of high score agents , , .

Fig. 4

Mean value of the number of hydrogen bonds between some ligands and corresponding main protease , .