Constraint-based Modelling of Human Erythrocyte Glycolysis and Role of 3PG in Breast Cancer

• Published in: 2024 3rd International Conference for Innovation in Technology (INOCON) pp. 1 - 8
• Main Authors: Pradhan, Victor, Bhadra, Preetha, Pradhan, Ranjan K.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.03.2024
• Subjects: Biological system modeling; Breast cancer; Computational modeling; constraint-based modeling; Enzymes; erythrocyte metabolic network and 3PG; Glycolysis; Predictive models; Regulation; Technological innovation
• DOI: 10.1109/INOCON60754.2024.10512070

Glycolysis is an anaerobic metabolic pathway that evolves in nearly all types of organisms and occurs both in the presence and absence of oxygen. Understanding the regulation of glycolysis and its associated enzymes is a fundamental aspect of studying the complexity of cancer metabolism. Constraint-based modeling has been a powerful approach to study large-scale metabolic network and its regulation in various diseases. Therefore, in this work, we have applied constraint-based modelling tool to explore the role of feedforward activation phenomenon using a well-established model of erythrocyte glycolysis. We used an open-source computational software, which is basically a Java Web Simulation (JWS) platform, developed to model biochemical pathways functions using known enzyme kinetics. Erythrocyte glycolysis model is chosen to test the computational efficacy of this online tool in predicting in vivo observations of steady-state metabolite concentrations is various diseases, which is mainly concerned with feed-forward activation of specific enzyme. Using a series of model simulations, it was demonstrated that, a moderate increase in level of 3-phosphoglycerate (3PG), a key metabolite in glycolysis can trigger serine biosynthesis in cancer cells, which is mainly due to the existence of feed-forward activation. This is consistent with the finding that the Phosphoglycerate dehydrogenase (PHGDH), the rate-limiting enzyme in the first step of SSP is most common in breast cancer. Similarly, the model simulation of steady-state glycolysis fluxes gave several insights on glycolysis control in disease states (e.g., hypoxia, cancer). Thus, this preliminary analysis based on the constraint-based modeling of erythrocyte glycolysis can be extended to study the roles of other metabolites in regulating breast tumor metabolism.