Identification of polyphenols from Broussonetia papyrifera as SARS CoV-2 main protease inhibitors using in silico docking and molecular dynamics simulation approaches
Λέξεις-κλειδιά
Αφηρημένη
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.
Keywords: Broussonetia papyrifera polyphenols; COVID-19; SARS CoV-2 main protease; docking; molecular dynamics simulation.
