Assessment of Interaction of Human OCT 1-3 Proteins and Metformin using Silico Analyses

Abstract

Metformin, a drug frequently used by diabetic patients as the first-line treatment worldwide, is positively charged and is transported into the cell through human organic cation transporter (hOCT 1-3) proteins. We aimed to mimic the cellular uptake of metformin by hOCT1-3 with various bioinformatics methods and tools. 3D structure of OCT1-3 proteins was predicted by considering the structures and function of these proteins. We predicted functional regions (active and ligand binding sites) of OCT1-3 and performed comparative bioinformatics analysis. The predicted structure of hOCT1-3 was then analyzed in the Blind Docking server and the results were confirmed with predicted binding site residues and conserved domain regions. We simulated the OCT1-3 and metformin docking and also validated the docking procedure with other substrates of HOCT1-3 proteins. We selected the best poses of metformin docking simulations as per binding energy (-5.27 to -4.60 kcal/mol). Lastly, we validated the static description of protein-ligand (OCT-Metformin) interactions by performing molecular dynamics simulation. Eventually, we obtained stable stimulation of OCT-metformin interaction.

Keywords

• organic cation transporters
• metformin
• protein structure prediction
• model validation
• docking