Molecular design, molecular docking and ADMET study of cyclic sulfonamide derivatives as SARS-CoV-2 inhibitors

Severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) continues to spread globally with more than 172 million confirmed cases and 3.57 million deaths. Cyclic sulfonamide derivative is identified as a successful compound and showed anti-SARS-CoV-2 activity. In this study, the structure and activity relationships of 35 cyclic sulfonamide compound inhibitors are investigated by using three-dimensional quantitative structure-activity relationship (3D-QSAR) and holographic quantitative structure-activity relationship (HQSAR). Two models with good statistical parameters and reliable predictive ability are obtained from the same training set, including Topomer CoMFA ([Formula: see text] = 0.623, [Formula: see text] = 0.938, [Formula: see text] = 0.893) model and HQSAR ([Formula: see text] = 0.704, [Formula: see text] = 0.958, [Formula: see text]) model. The established models not only have good stability, but also show good external prediction ability for the test set. The contour and color code maps of the models provide a lot of useful information for determining the structural requirements which might affect the activity; this information paves the way for the design of four novel cyclic sulfonamide compounds, and predictes their pIC(50) values. We explore the interaction between the newly designed molecule and SARS-CoV-2 3CLpro by molecular docking. The docking results show that GLU166, GLN192, ALA194, and VAL186 may be the potential active residues of the SARS-CoV-2 inhibitor evaluated in this study. Finally, the oral bioavailability and toxicity of the newly designed cyclic sulfonamide compounds are evaluated and the results show that the four newly designed cyclic sulfonamide compounds have major ADMET properties and can be used as reliable inhibitors against COVID-19. These results may provide useful insights for the design of effective SARS-CoV-2 inhibitors.