3D-QSAR studies, Pharmacophore modeling, Homology modeling and virtual screening approaches to discover novel sodium glucose co-transporter 2 inhibitors

Chhajed Priyanka N, Dr. Patil Ravindra B

A. R. A. College of Pharmacy, Nagaon, Dhule, KBC NMU, Jalgaon, Maharashtra, India

ABSTRACT

Diabetes mellitus is now becoming a global health problem. Because of its unique mode of action, SGLT2 has been a target of choice for type 2 diabetes mellitus for several decades. In this study, CoMFA was applied to generate 3D QSAR models. Statistically significant model was generated. Because there is no crystal structure for hSGLT2 in Protein Data Bank, we built and validated homology models of the protein. 3D Pharmacophore models were also created using known Gliflozins as the starting point. ZincPharmer and Asinex library databases were screened using the shared feature Pharmacophore model. The screened compounds were then filtered by applying Lipinski’s rule of five. Molecular docking of the screened Compounds was performed with homology modeled hSGLT2 protein using PyRx software to explore the binding mode of inhibitors followed by ADMET prediction. ZINC19575576, ZINC212074339, ZINC212074412, ZINC212086407 showed good docking score, close matching features with Pharmacophore model and ADMET properties.

Keywords:

Diabetes mellitus, SGLT2 inhibitors, Pharmacophore modeling, 3D-QSAR, Homology Modeling, Molecular docking study ADMET.