Unravelling high-affinity binding compounds towards transmembrane protease serine 2 enzyme in treating SARS-CoV-2 infection using molecular modelling and docking studies.

The coronavirus disease-19 (COVID-19) outbreak that is caused by a highly contagious severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has become a zoonotic pandemic, with approximately 24.5 million positive cases and 8.3 lakhs deaths globally. The lack of effective drugs or vaccine provoked the research for drug candidates that can disrupt the spread and progression of the virus. The identification of drug molecules through experimental studies is time-consuming and expensive, so there is a need for developing alternative strategies like in silico approaches which can yield better outcomes in less time. Herein, we selected transmembrane protease serine 2 (TMPRSS2) enzyme, a potential pharmacological target against SARS-CoV-2, involved in the spread and pathogenesis of the virus. Since 3D structure is not available for this protein, the present study aims at homology modelling and validation of TMPRSS2 using Swiss-model server. Validation of the modelled TMPRSS2 using various online tools confirmed model accuracy, topology and stereochemical plausibility. The catalytic triad consisting of Serine-441, Histidine-296 and Aspartic acid-345 was identified as active binding site of TMPRSS2 using existing ligands. Molecular docking studies of various drugs and phytochemicals against the modelled TMPRSS2 were performed using camostat as a standard drug. The results revealed eight potential drug candidates, namely nafamostat, meloxicam, ganodermanontriol, columbin, myricetin, proanthocyanidin A2, jatrorrhizine and baicalein, which were further studied for ADME/T properties. In conclusion, the study unravelled eight high affinity binding compounds, which may serve as potent antagonists against TMPRSS2 to impact COVID-19 drug therapy.