Computational estimation of potential inhibitors from known drugs against the main protease of SARS-CoV-2
Nguyễn Minh Tâm, Phạm Minh Quân, Nguyen Xuan Ha, Pham Cam Nam, Hường Thị Thu Phùng
Abstract
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.
Topics & Concepts
Coronavirus disease 2019 (COVID-19)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Drug repositioning2019-20 coronavirus outbreakProteaseVirologyPharmacologyPandemicMedicineCoronavirusEtoposideDrugInfectious disease (medical specialty)BiologyDiseaseInternal medicineEnzymeBiochemistryChemotherapyOutbreakComputational Drug Discovery MethodsSynthesis and biological activitySARS-CoV-2 and COVID-19 Research