Of integrated biochemical systems

M. Okamoto and K. Hayashi, Network study of integrated biochemical systems I. Connection of basic elements, BioSystems, 24, 39-52 (1990). 

From the results presented in this section, we conclude that the postulates of the Michaelis-Menten Formalism and the canons of good enzymological practice in vitro are not appropriate for characterizing the behavior of integrated biochemical systems. The very conditions that may have made it possible to identify important qualitative features of an enzymatic mechanism and produce a rate law in vitro tend to make the quantitative characterization of the reaction rate in vivo by this rate law invalid. 

There may be other formalisms, yet to be proposed, that will prove to be consistent with the systemic behavior of integrated biochemical systems. However,... 

The use of kinetics to characterize the behavior of integrated biochemical systems is a more recent and less developed practice. One of the more important issues in this integrative context is the selection of an appropriate formal representation. The most common approach is simply to adopt the Michaelis-Menten Formalism that has served so well for the elucidation of isolated reaction mechanisms. However, as the discussion above showed, there are difficulties in estimating the parameters of this formalism in general, and there is a combinatorial explosion in the amount of data required to characterize the rate law by kinetic means. Thus, even if the Michaelis-Menten Formalism were appropriate in principle, there... 

The Power-Law Formalism possesses a number of advantages that recommend it for the analysis of integrated biochemical systems. As discussed above, we saw that estimation of the kinetic parameters that characterize the molecular elements of a system in this representation reduces to the straightforward task of linear regression. Furthermore, the experimental data necessary for this estimation increase only as the number of interactions, not as an exponential function of the number of interactions, as is the case in other formalisms. The mathematical tractability of the local S-system representation is evident in the characterization of the intact system and in the ease with which the systemic behavior can be related to the underlying molecular determinants of the system (see above). Indeed, the mathematical tractability of this representation is the very feature that allowed proof of its consistency with experimentally observed growth laws and allometric relationships. It also allowed the diagnoses of deficiencies in the current model of the TCA cycle in Dictostelium and the prediction of modifications that led to an improved model (see above). 

Voit, E.O. (1992) Optimization of integrated biochemical systems. Biotech Bioeng 40 572-582. 

The terms bioinformatics and cheminformatics refer to the use of computational methods in the study of biology and chemistry. Information from DNA or protein sequences, protein structure, and chemical structure is used to build models of biochemical systems or models of the interaction of a biochemical system with a small molecule (e.g., a drug). There are mathematical and statistical methods for analysis, public databases, and literature associated with each of these disciplines. However, there is substantial value in considering the interaction between these areas and in building computational models that integrate data from both sources. In the most... 

In this chapter I shall examine some of the underlying assumptions and practical implications of enzymology as practiced in vitro, and contrast this approach with other complementary approaches for dealing with integrated biochemical systems in vivo. There is always a certain tension between these two approaches. This can... 

It is commonly assumed that enzymes are designed by natural selection for maximum molecular activity, and thus, that determining the conditions for maximal activity of an isolated enzyme in vitro will identify physiological values for the variables that affect it. However, this is not necessarily the case. The criteria for optimization of an isolated reaction (Albery and Knowles, 1977 Fersht, 1985 Kraut, 1988) are different from the criteria for optimization of the integrated biochemical system. Optimal behavior for the intact system may mean nonoptimal behavior for the isolated enzyme, and vice versa. 

Voit, E. O. Savageau, M, A. (1987). Accuracy of alternative representations for integrated biochemical systems. Biochem. 26,6869-6880. 

Finally, the integration of biochemical or biosensor methods with conventional chromatographic analyses should not be overlooked. For example, the use of im-munoaffinity columns prior to chemiluminescence or the use of biosensor detection systems following the chromatographic step may provide useful solutions to speciflc analytical needs. 

We have chosen animal cell cultures for that purpose, bearing in mind the following advantages of such system (i) the action of peptide results in a limited number of integral responses, when a variety of biochemical mechanisms gives rise to uniform effects, such as cell death or stimulation/inhibition of cell proliferation rate (ii) the test requires low, picomolar amounts of peptides (iii) the results are treated by simple and reliable statistic methods. 

Cytokines are peptides that are produced and secreted by cells of the immune system. They organise the immune response to invasion by a pathogen by communicating between the different cells. They are synthesised in the immune cells as precursor proteins (pro-proteins) from which a peptide is removed by a proteolytic enzyme to produce the active cytokine, prior to secretion. This enzyme is a serine protease. Perhaps surprisingly, some viruses are capable of synthesising serpins which inhibit this enzyme in the immune cells, so that secretion does not occur and communication and integration of the immune response to the viral infection is lost. This is one of many biochemical mechanisms by which pathogens can reduce or overcome the defence mechanisms of the host (Chapter 17). 

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