In silico study reveals existing drugs as α-glucosidase inhibitors: Structure-based virtual screening validated by experimental investigation

Abstract

Drug repositioning is a popular method of making drug discovery less costly and more efficient. Computational methods such as pharmacophore-based virtual screening, molecular docking, and molecular dynamics (MD) simulations have been widely utilized to make the process of finding drugs more efficient and accurate. In this study, “in silico repositioning” was performed to identify promising α-glucosidase inhibitors among existing drugs. Based on molecular dynamics simulations analysis of 3TOP-acarbose and 6C9X-voglibose complexes, we built structure-based pharmacophore models, and then we screened FDA-approved drugs with good pharmacophore-fit scores. Subsequently, we performed a molecular docking study to understand the binding modes of α-glucosidase and virtual screening hits. We chose three hits to assess the stability of the protein-hit interactions in physiological conditions using molecular dynamics simulations. We calculated the binding free energy using the molecular mechanics generalized born surface area (MM-GBSA) method. We also performed toxicity prediction of the three hits to analyze their potential toxicities, and found that they were relatively safe. Finally, α-glucosidase inhibitory activity assays of the three hits in vitro revealed that benserazide exhibited inhibitory effects towards α-glucosidase, confirming the computational results. In summary, we identified a method for further research on the “in silico repositioning” of existing drugs that may affect a specific molecular target.