Abstract:
Insulin is an animal hormone that regulates the glucose levels in blood. It is medically used to treat diabetic patients. Diabetes is characterized by the failure of synthesizing, secreting or responding to insulin and it is the third most prevalent disease in the world. In order to understand the reasons underlying Type-2 diabetes, the insulin signaling network should be analyzed in detail as signaling through the insulin pathway is critical for the regulation of intracellular and blood glucose levels and for the avoidance of diabetes. Moreover, the topological structure of the insulin signaling pathway is still incomplete. Thus in the present study, a protein interaction network consisting of proteins that have statistically high probability of being biologically related to insulin signaling pathway was reconstructed using SPA algorithm and Gene Ontology (GO) annotations. The 27 insulin signaling annotated proteins in humans were used as the input and a candidate network of 416 proteins and 895 interactions was obtained. The graph theoretic analysis of this reconstructed insulin signaling network whose degree distribution approximates the power law model, yielded the common topological features of the biological networks, i.e. it has small world characteristics with scale free topology. An important response of the muscle cell to insulin stimulation is known to be the translocation of intracellular vesicles containing a glucose transporter (GLUT4) to the cell surface. Therefore, beside the reconstructed insulin signaling network, the metabolic insulin network was also investigated by dynamic modeling approaches. The controlling reactions of the metabolic model were determined as the phosphorylation of PI3-kinase (a lipid kinase) and AKT (protein kinase B) proteins. In agreement with the literature reports, the present study also indicates that the insulin receptor, PKC, PI3K and Akt have important roles in regulating insulin signaling. In addition to these molecules, GRB2 protein is determined to be a hub with high connectivity and must therefore be assessed with special care in drug targeting.
