Screening of SGLT2 inhibitors based on virtual screening and cellular experiments.

This study aims at find hit compounds as SGLT2 inhibitors through the methods of virtual screening, biological experiment, Structural similarity search and molecular docking. Computer-aided drug design techniques were used to build modelling of quantitative construct validity relationships. Three-dimensional pharmacophore model and the principle of drug properties were used to screen the compounds. The effects of lead compounds on glucose uptake were observed in 293 T cells. Further, structural similarity searches were conducted on 13 hit compounds, then molecular docking the compounds with proteins was performed. Based on virtual screening, 20 highly rated compounds as potential lead candidates for diabetes treatment were selected. Combining the results in glucose uptake assays, 13 hit compounds were identified with strong inhibitory properties against SGLT2, especially, compound 2 had the lowest glucose uptake and the best inhibition of SGLT2. The compounds were classified into 5 classes and each class has the same core skeleton. Molecular docking cleared and definite that the hit compounds had stable and efficient hydrogen-bonding interactions with SGLT2, and their binding to SGLT2 was specific. 13 hit compounds were identified with strong inhibitory properties against SGLT2, and they are likely to become new SGLT2 inhibitors to treat diabetes.