摘要 : The objective of this research work is to identify molecules through an advanced computational screening technique from a database of approved drugs/nutraceuticals that would inhibit transmembrane protease serine 2 (TMPRSS2) and t... 展开 The objective of this research work is to identify molecules through an advanced computational screening technique from a database of approved drugs/nutraceuticals that would inhibit transmembrane protease serine 2 (TMPRSS2) and thereby prevent SARS-CoV-2's entry into human host cells. A homology model was built for TMPRSS2 and the standard inhibitors nafamostat and camostat were docked on the model. Ligand-based screening, flexible ligand docking and induced-fit docking followed by free binding energy calculations were carried out as part of the screening technique to generate hits. Eventually, molecular dynamics (MD) simulation was done for all the hits, and the results were compared with that of the standard inhibitors to validate our claims. From our computational study, we determined that streptomycin, doxorubicin and tetrahydrofolic acid are potential inhibitors of TMPRSS2. By analysing the MD simulation results, we also propose that streptomycin had the highest potential to inhibit TMPRSS2 among the three molecules. The three molecules we identified are most likely to show the efficacy when tested in vitro by prevention of entry of SARS-CoV-2 into human cells. These molecules can be taken further for clinical trials, and we expect fast processing since they are already approved by FDA and EMA for other diseases. 收起