Abstract
HEPNet is an electronic representation of metabolic reactions occurring within human cellular organization focusing on inflow and outflow of the energy currency ATP, GTP and other energy associated moieties. The backbone of HEPNet consists of primary bio-molecules such as carbohydrates, proteins and fats which ultimately constitute the chief source for the synthesis and obliteration of energy currencies in a cell. A series of biochemical pathways and reactions constituting the catabolism and anabolism of various metabolites are portrayed through cellular compartmentalization. The depicted pathways function synchronously toward an overarching goal of producing ATP and other energy associated moieties to bring into play a variety of cellular functions. HEPNet is manually curated with raw data from experiments and is also connected to KEGG and Reactome databases. This model has been validated by simulating it with physiological states like fasting, starvation, exercise and disease conditions like glycaemia, uremia and dihydrolipoamide dehydrogenase deficiency (DLDD). The results clearly indicate that ATP is the master regulator under different metabolic conditions and physiological states. The results also highlight that energy currencies play a minor role. However, the moiety creatine phosphate has a unique character, since it is a ready-made source of phosphoryl groups for the rapid synthesis of ATP from ADP. HEPNet provides a framework for further expanding the network diverse age groups of both the sexes, followed by the understanding of energetics in more complex metabolic pathways that are related to human disorders.
Highlights
A comprehensive knowledge of metabolism is fundamental to study and analyze the phenotypic and physiological attributes of all biological system [1]
Evaluation and validation of stress conditions have been monitored by human energy pool network (HEPNet) with time-course simulation providing an added explanation to the various stress factors given by the Ordinary Differential Equations (ODEs)
To check the workability of HEPNet, we studied two disease conditions, which are due to metabolic perturbations namely uremia and Dihydrolipoamide dehydrogenase deficiency(DLDD)
Summary
A comprehensive knowledge of metabolism is fundamental to study and analyze the phenotypic and physiological attributes of all biological system [1]. In 2002, Palsson et al presented an excellent study focusing on mitochondrial processes involved in ATP production This was followed by a large number of studies where metabolic models were reconstructed and used as a device to assess and understand different physiological conditions [10]. ATP and other energy currencies like GTP, NADH are vital for a number of important cellular processes that maintain the homeostasis of the human body and it is the need of the hour to model a whole pool where energy currencies play and replay their metabolic roles through anabolism and catabolism. We represent a metabolic model of the human energy pool network (HEPNet) using constraint based approach. Structural features of proteins play a vital role and the needs a well defined genetic information of the person HEPNet version 2.0 would cater to both genes and metabolites
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