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Identification of polyphenols from Broussonetia papyrifera as SARS CoV-2 main protease inhibitors using in silico docking and molecular dynamics simulation approaches.
J Biomol Struct Dyn. 2020 Aug 07 [Online ahead of print]JB

Abstract

The current COVID-19 pandemic is caused by SARS CoV-2. To date, ∼463,000 people died worldwide due to this disease. Several attempts have been taken in search of effective drugs to control the spread of SARS CoV-2 infection. The main protease (Mpro) from SARS CoV-2 plays a vital role in viral replication and thus serves as an important drug target. This Mpro shares a high degree of sequence similarity (>96%) with the same protease from SARS CoV-1 and MERS. It was already reported that Broussonetia papyrifera polyphenols efficiently inhibit the catalytic activity of SARS CoV-1 and MERS Mpro. But whether these polyphenols exhibit any inhibitory effect on SARS CoV-2 Mpro is far from clear. To understand this fact, here we have adopted computational approaches. Polyphenols having proper drug-likeness properties and two repurposed drugs (lopinavir and darunavir; having binding affinity -7.3 to -7.4 kcal/mol) were docked against SARS CoV-2 Mpro to study their binding properties. Only six polyphenols (broussochalcone A, papyriflavonol A, 3'-(3-methylbut-2-enyl)-3',4',7-trihydroxyflavane, broussoflavan A, kazinol F and kazinol J) had interaction with both the catalytic residues (His41 and Cys145) of Mpro and exhibited good binding affinity (-7.6 to -8.2 kcal/mol). Molecular dynamic simulations (100 ns) revealed that all Mpro-polyphenol complexes are more stable, conformationally less fluctuated; slightly less compact and marginally expanded than Mpro-darunavir/lopinavir complex. Even the number of intermolecular H-bond and MM-GBSA analysis suggested that these six polyphenols are more potent Mpro inhibitors than the two repurposed drugs (lopinavir and darunavir) and may serve as promising anti-COVID-19 drugs. Communicated by Ramaswamy H. Sarma.

Authors+Show Affiliations

School of Basic Sciences, Indian Institute of Technology Bhubaneswar, Bhubaneswar, India.School of Basic Sciences, Indian Institute of Technology Bhubaneswar, Bhubaneswar, India.School of Basic Sciences, Indian Institute of Technology Bhubaneswar, Bhubaneswar, India.School of Basic Sciences, Indian Institute of Technology Bhubaneswar, Bhubaneswar, India.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

32762411

Citation

Ghosh, Rajesh, et al. "Identification of Polyphenols From Broussonetia Papyrifera as SARS CoV-2 Main Protease Inhibitors Using in Silico Docking and Molecular Dynamics Simulation Approaches." Journal of Biomolecular Structure & Dynamics, 2020, pp. 1-14.
Ghosh R, Chakraborty A, Biswas A, et al. Identification of polyphenols from Broussonetia papyrifera as SARS CoV-2 main protease inhibitors using in silico docking and molecular dynamics simulation approaches. J Biomol Struct Dyn. 2020.
Ghosh, R., Chakraborty, A., Biswas, A., & Chowdhuri, S. (2020). Identification of polyphenols from Broussonetia papyrifera as SARS CoV-2 main protease inhibitors using in silico docking and molecular dynamics simulation approaches. Journal of Biomolecular Structure & Dynamics, 1-14. https://doi.org/10.1080/07391102.2020.1802347
Ghosh R, et al. Identification of Polyphenols From Broussonetia Papyrifera as SARS CoV-2 Main Protease Inhibitors Using in Silico Docking and Molecular Dynamics Simulation Approaches. J Biomol Struct Dyn. 2020 Aug 7;1-14. PubMed PMID: 32762411.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Identification of polyphenols from Broussonetia papyrifera as SARS CoV-2 main protease inhibitors using in silico docking and molecular dynamics simulation approaches. AU - Ghosh,Rajesh, AU - Chakraborty,Ayon, AU - Biswas,Ashis, AU - Chowdhuri,Snehasis, Y1 - 2020/08/07/ PY - 2020/8/9/entrez PY - 2020/8/9/pubmed PY - 2020/8/9/medline KW - Broussonetia papyrifera polyphenols KW - COVID-19 KW - SARS CoV-2 main protease KW - docking KW - molecular dynamics simulation SP - 1 EP - 14 JF - Journal of biomolecular structure & dynamics JO - J. Biomol. Struct. Dyn. N2 - The current COVID-19 pandemic is caused by SARS CoV-2. To date, ∼463,000 people died worldwide due to this disease. Several attempts have been taken in search of effective drugs to control the spread of SARS CoV-2 infection. The main protease (Mpro) from SARS CoV-2 plays a vital role in viral replication and thus serves as an important drug target. This Mpro shares a high degree of sequence similarity (>96%) with the same protease from SARS CoV-1 and MERS. It was already reported that Broussonetia papyrifera polyphenols efficiently inhibit the catalytic activity of SARS CoV-1 and MERS Mpro. But whether these polyphenols exhibit any inhibitory effect on SARS CoV-2 Mpro is far from clear. To understand this fact, here we have adopted computational approaches. Polyphenols having proper drug-likeness properties and two repurposed drugs (lopinavir and darunavir; having binding affinity -7.3 to -7.4 kcal/mol) were docked against SARS CoV-2 Mpro to study their binding properties. Only six polyphenols (broussochalcone A, papyriflavonol A, 3'-(3-methylbut-2-enyl)-3',4',7-trihydroxyflavane, broussoflavan A, kazinol F and kazinol J) had interaction with both the catalytic residues (His41 and Cys145) of Mpro and exhibited good binding affinity (-7.6 to -8.2 kcal/mol). Molecular dynamic simulations (100 ns) revealed that all Mpro-polyphenol complexes are more stable, conformationally less fluctuated; slightly less compact and marginally expanded than Mpro-darunavir/lopinavir complex. Even the number of intermolecular H-bond and MM-GBSA analysis suggested that these six polyphenols are more potent Mpro inhibitors than the two repurposed drugs (lopinavir and darunavir) and may serve as promising anti-COVID-19 drugs. Communicated by Ramaswamy H. Sarma. SN - 1538-0254 UR - https://www.unboundmedicine.com/medline/citation/32762411/Identification_of_polyphenols_from_Broussonetia_papyrifera_as_SARS_CoV_2_main_protease_inhibitors_using_in_silico_docking_and_molecular_dynamics_simulation_approaches_ L2 - http://www.tandfonline.com/doi/full/10.1080/07391102.2020.1802347 DB - PRIME DP - Unbound Medicine ER -
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