Analysis of Signal Transduction Network for Insulin Signaling Pathways

Abstract

Glucose homeostasis in the body is taken care by the regulation of insulin signaling pathways. Any disruptions result in the onset of serious metabolic disorders like diabetes which has raised the global health burden. Type 1 diabetes is a genetical disorder based disease which is yet to be cured. However, many studies show that type 2 diabetes can be avoided if a healthy lifestyle is followed. According to the International Diabetes Federation, 783 million people worldwide will have diabetes by 2045, with 541 million adults at high risk of type 2 diabetes and 6.7 million deaths expected in 2021, potentially turning the world into a diabetes pandemic. In the long run, the antidiabetic drugs currently used have substantial negative effects. As a result, multiple alternative therapies are used, which have a better result in diabetes management. In comparison to in vivo and in vitro approaches, the medical and pharmaceutical sectors have entered an era in which trials are conducted using a computer-based model simulation known as in silico to expedite the outcomes. This transformation will undoubtedly promote the healthcare industry's innovations by delivering solutions at a faster rate and at a lower cost. With the development of insulin resistance in type 2 diabetes, the complex insulin signal transduction pathways that are important for glucose regulation are disturbed. Utilizing the Cell Designer software, a type 2 diabetic state is modeled in silico using the available information about the underlying mechanisms. The presence of enough GLUT4 on the plasma membrane is crucial for glucose regulation. An in silico model has been built to examine the effects of alternative therapies such as physical activity and Olive Leaf Extract, oleuropein in combination with the allopathic medicine metformin via activation of AMPK pathways. The effect of various intensities of exercise on insulin resistance via GLUT4 translocation was studied in conjunction with various doses of the standard prescribed drug metformin (500mg and 2000mg). The result shows that a 2% improvement in the surface GLUT4 concentration was observed with a combination of various exercise intensities and metformin dosage of 500mg or 2000mg. This study also provides the insight of the effect of exercise on GLUT4 translocations. In light of the promising results, the in silico model was developed to assess the effect of oleuropein (500mg) on insulin resistance improvement in combination with various metformin doses (100-500mg). The findings revealed that the recommended dose of oleuropein (500mg) in combination with a reduction in metformin dosages by a certain amount (300mg) could show significant improvement in type 2 diabetes while lowering side effects. As a result, a comprehensive in silico model of the influence of alternative therapies (exercise and oleuropein) along with the v allopathic medicine metformin on the reduction of insulin resistance in type 2 diabetes was developed and examined. From a systems biology perspective, the properties of the insulin signal transduction pathway represented in silico under normal conditions in Cell Designer were chosen to be examined. The success of homeostatic glucose regulation is due to the robustness of biological systems that ignore disruptions or errors in the pathway. A variety of feedback and feedforward loops make up the pathway. The concentration of insulin receptor substrate-1 (IRS1) acts as the setpoint, while the deviation of IRS1 from its homeostatic level acts as the error to the pathway. The mathematical realization of the integral controller, which is known to be critical for the pathway's robust adaptation, was carried out with the presence of integrating process and negative feedback. Global Sensitivity analysis was then applied to the insulin signal transduction pathway and the essential parameter were determined using Sobol indices. By introducing perturbation or error of ±1%, ±2% and ±5% in terms of crucial parameters and inputs, the robustness of the PKC ζ-IRS1 pathway was tested. The Mann-Whitney statistical test was performed in Minitab software, and the findings confirmed the presence of robustness with p-values greater than the significance level of 0.05. Although there are a variety of alternative therapies and allopathic medications explored by the researchers to treat type 2 diabetes, there is no optimal dosage for the therapies when used in combination for different severity levels of diabetes, such as very low, low, moderate, high, and very high. On the basis of the in silico model, an optimization problem was formulated in MATLAB with the administration of metformin, oleuropein, and exercise intensity for various diabetes severity levels. The goal was to achieve the highest possible surface GLUT4 concentration using various dosage combinations of metformin, oleuropein, and exercise intensity. The optimization problem was addressed at several levels using the global search technique of the optimization solver fmincon in MATLAB. As a consequence, the optimal dosage combination for very high levels was 1810mg metformin, 1465mg oleuropein, and 7.52 metabolic equivalent of task (MET). Similarly, the solver found optimum dosages that increased the surface GLUT4 concentration for other severity levels. As a result, the proposed optimization technique for determining the optimal dosage for improving insulin resistance at various levels of type 2 diabetes severity led to substantial improvements. As a result, the in silico dynamic model of the insulin signal transduction pathway with the influence of alternative therapies and allopathic drugs has been shown to reduce the time and effort required to conduct studies in vivo or in vitro. For other metabolic disorders, various other dosage vi combinations could be investigated with various alternative therapies and allopathic drugs. The proposed approach could aid in the creation of drugs as well as the identification of pharmacological targets, thereby transforming the medical and pharmaceutical industries.