Computational Modeling of the Metabolic States Regulated by the Kinase Akt

Abstract

Signal transduction and gene regulation determine a major reorganization of metabolic activities in order to support cell proliferation. Protein Kinase B (PKB), also known as Akt, participates in the PI3K/Akt/mTOR pathway, a master regulator of aerobic glycolysis and cellular biosynthesis, two activities shown by both normal and cancer proliferating cells. Not surprisingly considering its relevance for cellular metabolism, Akt/PKB is often found hyperactive in cancer cells. In the last decade, many efforts have been made to improve the understanding of the control of glucose metabolism and the identification of a therapeutic window between proliferating cancer cells and proliferating normal cells. In this context, we have modeled the link between the PI3K/Akt/mTOR pathway, glycolysis, lactic acid production, and nucleotide biosynthesis. We used a computational model to compare two metabolic states generated by two different levels of signaling through the PI3K/Akt/mTOR pathway: one of the two states represents the metabolism of a growing cancer cell characterized by aerobic glycolysis and cellular biosynthesis, while the other state represents the same metabolic network with a reduced glycolytic rate and a higher mitochondrial pyruvate metabolism. Biochemical reactions that link glycolysis and pentose phosphate pathway revealed their importance for controlling the dynamics of cancer glucose metabolism.

Inferring biochemical routes from biochemical networks

“…To study the applicability of the above described approach in real case scenarios, two studies are performed to study the metabolic alteration upon lactose shift in E.coli [14] and to identify metabolic shifts that occur in a cancer cell [15]. C. E.coli stress response E.coli cells are known to best grow on glucose medium and undergo stress when the medium is shifted to lactose.…”

“…To understand this phenomenon, human metabolic network consisting of Glycolysis, TCA cycle, PPP and Pyruvate metabolism is reconstructed, consisting of 44 metabolites and 42 connections. Due to the lack of experimental metabolomics data for cancer cells, data obtained by insilico models [15] are integrated into the network.…”

Formate induces a metabolic switch in nucleotide and energy metabolism

“…The computational model used for the simulations of glycolysis is a reduced version of the one in Ref. [2]. It consists of ten ordinary differential equations for the dynamics of the concentrations of the glycolytic intermediates, starting from glucose transport into the cell and ending in the conversion of pyruvate to lactate: where V m = 107.6M/s, K atp = 0.021mM , = 0.98, ↵ = 0.32, K f 26bp = 0.00084mM , K f 6p = 1mM , L = 4.1mM , K cit = 6.8mM , K i,atp = 20mM , K adp = 5mM , K fbp = 5mM , K app = 247 [4].…”

Understanding the mTOR signaling pathway via mathematical modeling

“…Their model proposed that GLUT4 translocation is more sensitive to higher amino acid concentrations and produced a bistable behavior under various insulin concentrations at steady state. The insulin stimulated PI3K/AKT/mTOR pathway model was linked to metabolic pathways to study how metabolic processes are regulated by the mTOR pathway . mTOR models have been successfully applied in untangling complex mechanisms of insulin resistance, which is the main cause of Type 2 diabetes.…”

“…The insulin stimulated PI3K/AKT/mTOR pathway model was linked to metabolic pathways to study how metabolic processes are regulated by the mTOR pathway. 47,64 mTOR models have been successfully applied in untangling complex mechanisms of insulin resistance, which is the main cause of Type 2 diabetes. Insulin resistance is characterized by dysfunction in the insulin control that involves several layers of regulation, different cell types and different organs.…”