Comparative Analysis of Kinetic Realizations of Insulin Signaling
Patrick Vincent N. Lubenia, Eduardo R. Mendoza, Angelyn R. Lao

TL;DR
This study compares insulin signaling in healthy and diabetic states using reaction network analysis, revealing differences in network complexity, species involvement, and robustness that shed light on insulin resistance mechanisms.
Contribution
It introduces a network decomposition approach to analyze and compare insulin signaling pathways in health and disease, highlighting key differences related to insulin resistance.
Findings
INSMS and INRES share some network properties.
Insulin resistance involves increased species involvement.
GLUT4 loses concentration robustness in INRES.
Abstract
Several studies have developed dynamical models to understand the underlying mechanisms of insulin signaling, a signaling cascade that leads to the translocation of glucose, the human body's main source of energy. Fortunately, reaction network analysis allows us to extract properties of dynamical systems without depending on their model parameter values. This study focuses on the comparison of insulin signaling in healthy state (INSMS or INSulin Metabolic Signaling) and in type 2 diabetes (INRES or INsulin RESistance) using reaction network analysis. The analysis uses network decomposition to identify the different subsystems involved in insulin signaling (e.g., insulin receptor binding and recycling, GLUT4 translocation, and ERK signaling pathway, among others). Furthermore, results show that INSMS and INRES are similar with respect to some network, structo-kinetic, and kinetic…
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Taxonomy
TopicsGene Regulatory Network Analysis · Microbial Metabolic Engineering and Bioproduction · Bioinformatics and Genomic Networks
