Structure-Based Computational Analysis of Interactions between Insulin Receptor and Insulin Inhibitory Receptor

Abstract

The recently discovered insulin inhibitory receptor (inceptor) plays a crucial role in insulin resistance and diabetes by reducing the insulin receptor count on cell membranes, resulting in higher blood glucose levels and decreased insulin sensitivity. Therefore, understanding the mechanism of how the inceptor insulin receptor complex interacts is exceedingly important. This study uses computational drug discovery to inhibit this interaction. Initially, we employed AlphaFold-Multimer to model the inceptor-insulin receptor protein complex and subsequently identified specific inceptor residues likely involved in binding to the insulin receptor. Through virtual screening, thousands of potential small molecules were found to bind to the inceptor, and 10 with the highest probability were chosen for docking. Beta-L-fucose, beta-D-fucose, and alpha-L-fucose showed the most promising binding energies, meaning these three small molecules can effectively interrupt the binding between the complex. We also computationally mutated the binding site of the insulin receptor and calculated the change in binding energy of the inceptor insulin receptor complex, the most dramatic being a 0.4 kcal mol^-1 change when Arginine mutated to Tryptophan at residue 926. Our study suggests that the mutations led to disease primarily due to the change in interactions of the inceptor insulin receptor complex.