ABSTRACT
BACKGROUND: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), is currently posing significant threats to public health worldwide. It is notable that a substantial proportion of patients with sever COVID-19 have coexisting diabetic conditions, indicating the progression and outcome of COVID-19 may relate to diabetes. However, it is still unclear whether diabetic treatment principles can be used for the treatment of COVID-19. METHODS: We conducted a computational approach to screen all commonly used clinical oral hypoglycemic drugs to identify the potential inhibitors for the main protease (Mpro ) of SARS-CoV-2, which is one of the key drug targets for anti-COVID-19 drug discovery. RESULTS: Six antidiabetic drugs with docking scores higher than 8.0 (cutoff value), including repaglinide, canagliflozin, glipizide, gliquidone, glimepiride, and linagliptin, were predicted as the promising inhibitors of Mpro . Interestingly, repaglinide, one of the six antidiabetic drugs with the highest docking score for Mpro , was similar to a previously predicted active molecule nelfinavir, which is a potential anti-HIV and anti-COVID-19 drug. Moreover, we found repaglinide shared similar docking pose and pharmacophores with a reported ligand (N3 inhibitor) and nelfinavir, demonstrating that repaglinide would interact with Mpro in a similar way. CONCLUSION: These results indicated that these six antidiabetic drugs may have an extra effect on the treatment of COVID-19, although further studies are necessary to confirm these findings.
Subject(s)
COVID-19 Drug Treatment , Hypoglycemic Agents/pharmacology , Viral Matrix Proteins/antagonists & inhibitors , A549 Cells , Antiviral Agents/pharmacology , Binding Sites , Drug Discovery , Humans , Models, Molecular , Molecular Docking Simulation , Molecular Dynamics Simulation , Nelfinavir/pharmacology , Protease Inhibitors/pharmacologyABSTRACT
The coronavirus disease 2019 (COVID-19) has attracted extensive attention all around the world recently. Early screening, early diagnosis, early isolation, and early treatment remain the most effective prevention and control measures. Computed tomography (CT) plays a vital role in the screening, diagnosis, treatment, and follow-up of COVID-19, especially in the early screening, with a higher sensitivity than that of real-time fluorescence RT-PCR. The combination of CT and artificial intelligence has the potential to help clinicians in improving the diagnostic accuracy and working efficiency.