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Metabolic reaction networks regulation

In a linear chemical reaction system, there is a unique steady state determined by the chemical constraints that establish the NESS. For nonlinear reactions, however, there can be multiple steady states [6]. A network comprised of many nonlinear reactions can have many steady states consistent with a given set of chemical constraints. This fact leads to the suggestion that a specific stable cellular phenotypic state can result from a specific NESS in which the steady operation of metabolic reactions maintains a balance of cellular components and products with the expenditure of biochemical energy [4]. Similarly, the network of chemical and mechanical signals that regulate the metabolic network must also be in a steady state. Important problems, then, are to determine the variety of steady states available to a system under a given set of chemical constraints and the mechanisms by which cells undergo... [Pg.120]

It is evident that the complex network of metabolic reactions must be rigorously regulated. At the same time, metabolic control must be flexible, to adjust metabolic activity to the constantly changing external environments of cells. Metabolism is regulated through control of (1) the amounts oj enzymes, (2) their catalytic activities, and (3) the accessibility of substrates. [Pg.428]

Genes, compartments, and catalysts are regulatory structures that must be built from free energy and materials made available by metabolic reactions. The metabolites are smaller and simpler than the regulators, more of them are present in the ambient environment, and the possible reaction networks among them are more densely sampled than the possible networks producing complex structures. Thus, the reaction network of core metabolism is expected to be more nearly a bulk chemical process [50] than the combinatorics of either nucleic acid or amino acid polymers. [Pg.395]

In this chapter we present an experimental test case of the deduction of a reaction pathway and mechanism by means of correlation metric construction from time-series measurements of the concentrations of chemical species [1], We choose as the system an enzymatic reaction network, the initial steps of glycolysis (fig. 8.1). Glycolysis is central in intermediary metabolism and has a high degree of regulation [2]. The reaction pathway has been well studied and thus it is a good test for the theory. Further, the reaction mechanism of this part of glycolysis has been modeled extensively [3]. [Pg.87]

The Systems Biology Markup Language (SBML, http //sbml.org) is a widely used standard for annotating a reaction network with dynamics and biology-specific semantics. It is applicable to static and dynamic models of, for example, cell-signaling pathways, metabolic pathways, biochemical reactions, gene regulation, and many others. An SBML document contains a detailed specification of a biochemical model (e.g., the initial quantities for the entities, kinetic laws for the reactions, etc.). [Pg.329]

Biological reaction systems, such as metabolic, gene regulation, molecular signal transduction and cell cycle reaction networks are usually simulated as constant temperature, spatially homogeneous chemical kinetic reaction systems. This is a... [Pg.344]

Biochemical pathways consist of networks of individual reactions that have many feedback mechanisms. This makes their study and the elucidation of kinetics of individual reaction steps and their regulation so difficult. Nevertheless, important inroads have already been achieved. Much of this has been done by studying the metabolism of microorganisms in fermentation reactors. [Pg.562]

One of the most distinguishing features of metabolic networks is that the flux through a biochemical reaction is controlled and regulated by a number of effectors other than its substrates and products. For example, as already discovered in the mid-1950s, the first enzyme in the pathway of isoleucine biosynthesis (threonine dehydratase) in E. coli is strongly inhibited by its end product, despite isoleucine having little structural resemblance to the substrate or product of the reaction [140,166,167]. Since then, a vast number of related... [Pg.137]

To investigate these two questions, a parametric model of the Jacobian of human erythrocytes was constructed, based on the earlier explicit kinetic model of Schuster and Holzhiitter [119]. The model consists of 30 metabolites and 31 reactions, thus representing a metabolic network of reasonable complexity. Parameters and intervals were defined as described in Section VIII, with approximately 90 saturation parameters encoding the (unknown) dependencies on substrates and products and 10 additional saturation parameters encoding the (unknown) allosteric regulation. The metabolic state is described by the concentration and fluxes given in Ref. [119] for standard conditions and is consistent with thermodynamic constraints. [Pg.227]

The examples of phosphorylase kinase and protein phosphatase I illustrate some important principles of regulation of enzyme activity by phosphorylation and dephosphorylation events. They clearly indicate how different signal transduction paths can meet in key reactions of metabolism, how signals can be coordinated with one another and how common components of a regulation network can be activated by different signals. The following principles are highlighted ... [Pg.282]

All life processes are the result of enzyme activity. In fact, life itself, whether plant or animal, involves a complex network of enzymatic reactions. An enzyme is a protein that is synthesized in a living cell. It catalyzes a thermodynamically possible reaction so that the rate of the reaction is compatible with the numerous biochemical processes essential for the growth and maintenance of a cell. The synthesis of an enzyme thus is under tight metabolic regulations and controls that can be genetically or environmentally manipulated sometimes to cause the overproduction of an enzyme by the cell. An enzyme, like chemical catalysts, in no way modifies the equilibrium constant or the free energy change of a reaction. [Pg.1375]

Thus, Nature has integrated thiol/disulfide exchange reactions in the regulation of its metabolic and antioxidant networks. The potentially cytotoxic effects of protein S-thiolation will remain controversial until the relationship between the systems of glutathione reductase, thioredoxin, glutaredoxin and thioltransferase are better understood. [Pg.57]

Aside from the inordinately dominant light of molecular genetics, the new wave in biochemistry today is, what has come to be called, metabolic control analysis (MCA) (Comish-Bowden and Cardenas, 1990). The impetus behind this wave is the desire to achieve a holistic view of the control of metabolic systems, with emphasis on the notion of system. The classical, singular focus on individual, feedback-modulated (e.g., allosteric), rate-limiting enzymes entails a naive and myopic view of metabolic regulation. It has become increasingly evident that control of metabolic pathways is distributive, rather than localized to one reaction. MCA places a given enzyme reaction into the kinetic context of the network of substrate-product connections, effector relationships, etc., as supposedly exist in situ, it shows that control of fluxes, metabolite concentrations, inter alia, is a systemic function and not an inherent property of individual enzymes. Such... [Pg.89]

A reasonable ambition for model reactions is that their mechanisms ought to contain some dues about the mechanism of the enzyme-catalyzed reaction also. It has long been realized that it is fruitless simply to buUd the model-reaction mechanism into an enzyme active site. Such a procedure would entail the view that the factors present and at work in the model system render a complete account of the biological history of the enzyme. There is no reason to expect this to be so, and many reasons to think it would not be so. In the simplest sense, a given enzyme must occupy a niche in a metabolic network that may require its regulation and may influence its structure and mechanistic potentialities in ways that cannot be derived from non-enzymic studies. [Pg.1047]


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See also in sourсe #XX -- [ Pg.450 ]




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