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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

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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]

PMID: 32340562

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Project description:The continued toll of COVID-19 has halted the smooth functioning of civilization on a global scale. With a limited understanding of all the essential components of viral machinery and the lack of structural information of this new virus, initial drug discovery efforts had limited success. The availability of high-resolution crystal structures of functionally essential SARS-CoV-2 proteins, including 3CLpro, supports the development of target-specific therapeutics. 3CLpro, the main protease responsible for the processing of viral polypeptide, plays a vital role in SARS-CoV-2 viral replication and translation and is an important target in other coronaviruses. Additionally, 3CLpro is the target of repurposed drugs, such as lopinavir and ritonavir. In this study, target proteins were retrieved from the protein data bank (PDB IDs: 6 M03, 6LU7, 2GZ7, 6 W63, 6SQS, 6YB7, and 6YVF) representing different open states of the main protease to accommodate macromolecular substrate. A hydroxyethylamine (HEA) library was constructed from harvested chemical structures from all the series being used in our laboratories for screening against malaria and Leishmania parasites. The database consisted of ∼1000 structure entries, of which 70% were new to ChemSpider at the time of screening. This in-house library was subjected to high throughput virtual screening (HTVS), followed by standard precision (SP) and then extra precision (XP) docking (Schrodinger LLC 2021). The ligand strain and complex energy of top hits were calculated by Molecular Mechanics Generalized Born Surface Area (MM/GBSA) method. Promising hit compounds (n = 40) specifically binding to 3CLpro with high energy and average MM/GBSA scores were then subjected to (100-ns) MD simulations. Using this sequential selection followed by an in-silico validation approach, we found a promising HEA-based compound (N,N'-((3S,3'S)-piperazine-1,4-diylbis(3-hydroxy-1-phenylbutane-4,2-diyl))bis(2-(5-methyl-1,3-dioxoisoindolin-2-yl)-3-phenylpropanamide)), which showed high in vitro antiviral activity against SARS-CoV-2. Further to reduce the size of the otherwise larger ligand, a pharmacophore-based predicted library of ∼42 derivatives was constructed, which were added to the previous compound library and rescreened virtually. Out of several hits from the predicted library, two compounds were synthesized, tested against SARS-CoV-2 culture, and found to have markedly improved antiviral activity.

Dataset Information

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

Publications

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

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