Primary Simulate For Inherited Hypertrophic Ardiomyopathy

This article focuses on the collection of biological information from database and published reports and the modeling of biological networks for the studying the mechanism and systematic behaviors under normal and pathological conditions.A biological system, such as a whole cell, could be considered as a'complex systems', from which various'complex'behaviors emerge because of the large number of interior elements and their interactions. The understanding of such mechanism is pretty different under the condition of recent experimental techniques. Computational systems biology was further developed in this field, and has attracted more and more attention.My principle study is to model and simulate biological network in silico for the purpose of further understanding the pathological mechanism of Familial hypertrophic cardiomyopathy, which is an autosomal dominant cardiac disease characterized as asymmetrical interventricular and left ventricular hypertrophy and myocellular disarray. The extent of this disease can be ranged from benign to severe, and often causes sudden death in young athletes. FHC is also genetically heterogeneous, resulting from mo2re than one thousand of mutation sites in at least seven genes. Several biological networks in myocardia are affected by this disease, such as metabolic network, gene regulation network and signal transduction network. As metabolism is one of the most important characteristic of living life, my work is focused on modeling the behaviors of metabolic network in hypertrophic myocardia.The simulation for metabolic networks is a hot point in systems biology. There are several kinds of approaches, such as cybernetic modeling, metabolic control analysis, flux balance analysis, and so on. The former methods are based on kinetic descriptions, while the latter is based on stoichiometry. In fact, despite current developments in experimental technology, it is difficult to obtain a uniform dataset of all reaction kinetics and molecular concentrations in a complex metabolic network. Stoichiometry-based approaches, such as FBA, can be used to reconstruct complex metabolic networks in the absence of detailed information on biochemical reactions.Based on FBA and other stoichiometric analysis approaches, we build a modeling platform for metabolic networks analysis use C++, and rebuild the energy metabolic network in mammalian myocardia. To better understand the dynamic regulation of optimality in metabolic networks under perturbed conditions, we reconstruct the energetic metabolic network in mammalian myocardia using dynamic flux balance analysis (DFBA), and then modify the optimal objective from the maximization of ATP production to the minimization of metabolite concentration fluctuation under ischemic conditions, according to the hypothesis of minimization of metabolic adjustment (MOMA). The simulation results are more consistent with experimental data than those of the DFBA model, particularly the retentive predominant contribution of fatty acid to oxidative ATP synthesis, the exact mechanism of which has not been elucidated and seems to be unpredictable by the DFBA model. These results suggest that the systemic states of metabolic networks do not always remain optimal, but may become suboptimal when a transient perturbation occurs. This finding supports the relevance of the MOMA hypothesis and might contribute to the further exploration of the underlying mechanism of dynamic regulation in metabolic networks.We also use the extended model of the action potential in ventricular myocyte to explore the transition of various ion channels under pathological conditions. In this model, both the buffering of Ca²⁺ and Mg²⁺ and transport of ATP and ADP are considered. The results indicate that falling in ATP/ADP ratio significantly reduces sarcoplasmic Ca²⁺ concentration and systolic Ca²⁺ concentration, increases diastolic Ca²⁺ concentration and Ca²⁺ influx through L-type channels, and decreases the efficiency of the Na+/Ca²⁺ exchanger in extruding Ca²⁺ during periodic voltage-clamp stimulation. This analysis suggests that the most important reason for these changes during metabolic inhibition is the down-regulation of the sarcoplasmic Ca²⁺-ATPase pump by reducing diastolic MgATP levels. High Ca²⁺ concentrations accumulating near the membrane might have a greater influence on Mg²⁺, ATP, and ADP concentrations than that of lower Ca²⁺ concentrations in the bulk myoplasm. The model predictions are in general agreement with experimental observations measured under normal and pathological conditionsIn conclusion, we model the metabolic network and action potential in myocardia under normal and pathological conditions, for the purpose of providing helpful suggestion for the deeper study of molecular mechanism and pathological characters of Familial hypertrophic cardiomyopathy. As the modeling case is a pretty complex genetic disease, it is very difficult to understand its pathological process and mechanism only by biological experiments. The integration of computational simulation and traditional experiments may give an access to the further research and therapy of this family disease.