Unknown

Dataset Information

0

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


ABSTRACT: The main protease of SARS-CoV-2 is one of the important targets to design and develop antiviral drugs. In this study, we have selected 40 antiviral phytochemicals to find out the best candidates which can act as potent inhibitors against the main protease. Molecular docking is performed using AutoDock Vina and GOLD suite to determine the binding affinities and interactions between the phytochemicals and the main protease. The selected candidates strongly interact with the key Cys145 and His41 residues. To validate the docking interactions, 100?ns molecular dynamics (MD) simulations on the five top-ranked inhibitors including hypericin, cyanidin 3-glucoside, baicalin, glabridin, and ?-ketoamide-11r are performed. Principal component analysis (PCA) on the MD simulation discloses that baicalin, cyanidin 3-glucoside, and ?-ketoamide-11r have structural similarity with the apo-form of the main protease. These findings are also strongly supported by root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), radius of gyration (Rg), and solvent accessible surface area (SASA) investigations. PCA is also used to find out the quantitative structure-activity relationship (QSAR) for pattern recognition of the best ligands. Multiple linear regression (MLR) of QSAR reveals the R2 value of 0.842 for the training set and 0.753 for the test set. Our proposed MLR model can predict the favorable binding energy compared with the binding energy detected from molecular docking. ADMET analysis demonstrates that these candidates appear to be safer inhibitors. Our comprehensive computational and statistical analysis show that these selected phytochemicals can be used as potential inhibitors against the SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

SUBMITTER: Islam R 

PROVIDER: S-EPMC7232885 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

altmetric image

Publications

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

Islam Rajib R   Parves Md Rimon MR   Paul Archi Sundar AS   Uddin Nizam N   Rahman Md Sajjadur MS   Mamun Abdulla Al AA   Hossain Md Nayeem MN   Ali Md Ackas MA   Halim Mohammad A MA  

Journal of biomolecular structure & dynamics 20200512 9


The main protease of SARS-CoV-2 is one of the important targets to design and develop antiviral drugs. In this study, we have selected 40 antiviral phytochemicals to find out the best candidates which can act as potent inhibitors against the main protease. Molecular docking is performed using AutoDock Vina and GOLD suite to determine the binding affinities and interactions between the phytochemicals and the main protease. The selected candidates strongly interact with the key Cys145 and His41 re  ...[more]

Similar Datasets

| S-EPMC9142792 | biostudies-literature
| S-EPMC7499150 | biostudies-literature
| S-EPMC8638226 | biostudies-literature
| S-EPMC8652770 | biostudies-literature
| S-EPMC7754928 | biostudies-literature
| S-EPMC10470497 | biostudies-literature
| S-EPMC8288410 | biostudies-literature
| S-EPMC9273859 | biostudies-literature
| S-EPMC8514552 | biostudies-literature
| S-EPMC7817485 | biostudies-literature