Computational estimation of potential inhibitors from known drugs against the main protease of SARS-CoV-2. Issue 28 (12th May 2021)

• Record Type: Journal Article
• Authors: Tam, Nguyen Minh; Pham, Minh Quan; Ha, Nguyen Xuan; Nam, Pham Cam; Phung, Huong Thi Thu
• Is Part Of: RSC advances. Volume 11:Issue 28(2021)
• Page Start: 17478
• Page End: 17486
• Publication Date: 2021-05-12
• Subjects: Chemistry -- Periodicals; 540.5
• DOI: 10.1039/d1ra02529e
• Languages: English
• ISSNs: 2046-2069

Abstract

Abstract : Approved drugs predicted to interact with critical residues in the substrate-binding site of SARS-CoV-2 Mpro can be promising inhibitors. Abstract : The coronavirus disease (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has rapidly spread worldwide recently, leading to global social and economic disruption. Although the emergently approved vaccine programs against SARS-CoV-2 have been rolled out globally, the number of COVID-19 daily cases and deaths has remained significantly high. Here, we attempt to computationally screen for possible medications for COVID-19 via rapidly estimating the highly potential inhibitors from an FDA-approved drug database against the main protease (Mpro) of SARS-CoV-2. The approach combined molecular docking and fast pulling of ligand (FPL) simulations that were demonstrated to be accurate and suitable for quick prediction of SARS-CoV-2 Mpro inhibitors. The results suggested that twenty-seven compounds were capable of strongly associating with SARS-CoV-2 Mpro. Among them, the seven top leads are daclatasvir, teniposide, etoposide, levoleucovorin, naldemedine, cabozantinib, and irinotecan. The potential application of these drugs in COVID-19 therapy has thus been discussed.