Molecular modeling, dynamics simulation and characterization of human inositol hexakisphosphate kinase 1 (IP6K1) related to diabetes

Abstract

Inositol hexakisphosphate kinase-1 (IP6K1) protein plays an important role in insulin signaling producing IP7 that inhibit the action of protein kinase B (Akt). Inhibition of IP6K1 has been proposed as a novel way to enhance insulin signaling. Characterization and binding interaction of IP6K1 is essential for rational anti-diabetic drug development targeting this protein. Computational tools were used to analyze the physicochemical characteristics of IP6K1. Homology modelling reliably predicts the tertiary structure of IP6K1. Derived three-dimensional models were
then used to predict the binding mode and interacting amino acid residues. MD simulation (30 ns) was employed to investigate the protein dynamics. The modeled IP6K1 exhibited secondary characteristics comprising of 63.3% helixes, 30.2% sheets and 13.4% turns with an aliphatic index of 65.83 and instability index 50.53 showing that the protein is relatively unstable without its appropriate environment. The extinction coefficient was 34560 while the grand average of hydropathicity was −0.724. Homology modelling was performed by SWISS-MODEL program and the proposed model was evaluated as reliable based on RAMPAGE’s Ramachandran plot, and ProSA analyses. RMSD, RMSF, Rg revealed that the protein attained stability around 20ns. This appeared to be the first attempt to portray molecular dynamic simulation of IP6K1 coupled with modeling and thorough characteristic analysis of the protein using parameters like Ramachandran plot, Chou and Fasman Secondary Structure prediction and Protparam. Studies like protein engineering, structure and function as well as activity analysis are suggested. Our computational studies reavealed the binding pocket and critical amino acid residues that can be exploited in the design of inhibitors of IP6K1 as antidiabetic drugs.

Keywords: Insulin signaling, physicochemical characteristics, homology modelling, diabetes