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Screening of plant-based natural compounds as a potential COVID-19 main protease inhibitor: an in silico docking and molecular dynamics simulation approach.

ABSTRACT: A new strain of coronavirus (CoV) has been identified as SARS-CoV-2, which is responsible for the recent COVID-19 pandemic. Currently, there is no approved vaccine or drug available to combat the pandemic. COVID-19 main protease (M^pro) is a key CoV enzyme, which plays an important role in triggering viral replication and transcription, turns it into an attractive target. Therefore, we aim to screen natural products library to find out potential COVID-19 M^pro inhibitors. Plant-based natural compounds from Sigma-Aldrich plant profiler chemical library have been screened through virtual molecular docking and molecular dynamics simulation to identify potential inhibitors of COVID M^pro. Our virtual molecular docking results have shown that there are twenty-eight natural compounds with a greater binding affinity toward the COVID-19 M^pro inhibition site as compared to the co-crystal native ligand Inhibitor N3 (-7.9 kcal/mol). Also, molecular dynamics simulation results have confirmed that Peonidin 3-O-glucoside, Kaempferol 3-O-β-rutinoside, 4-(3,4-Dihydroxyphenyl)-7-methoxy-5-[(6-O-β-D-xylopyranosyl-β-D-glucopyranosyl)oxy]-2H-1-benzopyran-2-one, Quercetin-3-D-xyloside, and Quercetin 3-O-α-L-arabinopyranoside (selected based on the docking score) possess a significant amount of dynamic properties such as stability, flexibility and binding energy. Our In silco results suggests that all the above mention natural compounds have the potential to be developed as a COVID-19 M^pro inhibitor. But before that, it must go through under the proper preclinical and clinical trials for further scientific validation. Communicated by Ramaswamy H. Sarma.

SUBMITTER: Majumder R

PROVIDER: S-EPMC7544942 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Coronavirus (covid-19) infection is considered to be deadliest ever pandemic experienced by the human being. It has very badly affected the socio-economic health of human and stuck the scientific community to think and rethink about its complete eradication. But due to no effective treatment or unavailability of vaccine the health professional could not show any significant improvement to control the pandemic. The situation needs newer molecule, vaccine or effective treatment to control covid-19 infection. Different target in viruses has been explored and proteases enzymes were found to be therapeutically effective target for the design of potential anti-covid-19 molecule as it plays the vital role in viral replication and assembly. Structure-based drug design was employed to discover the small molecule of anti-covid-19. Here we considered the small library of naturally occurring polyphenolic compounds and molecular docking, Molecular dynamics (MD) simulations, free binding energy calculation and in-silico ADME calculations to identify the newer HITs. Based upon their score the two molecules were identified as promising candidate. The docking scores were found to be -7.643 and -7.065 for the HIT1 and HIT-2 respectively. In MD simulations study the RMSD values were found to be 4.3 Å & 4.9 Å respectively. To validate these results MM-GBSA was performed and their binding free energies were computationally determined. The prime energy values of identified HITs (-13412.45 & -13441.8 kJ/mole) were found to be very close proximity to reference molecule (-13493.05 kJ/mole). Then in-silico ADME calculations were performed to calculate the drug likeliness identified HITs. BY considering all the values comparative to reference molecule and obtained in-silico pharmacokinetic properties of identified HITs we can suggest that HIT-1 and HIT-2 would be the most promising molecules that can inhibit the main protease enzyme of covid-19. These two molecules would become the potential drug candidate for the treatment of covid-19 infections.

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Screening of plant-based natural compounds as a potential COVID-19 main protease inhibitor: an in silico docking and molecular dynamics simulation approach.

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