Literature DB >> 2520168

A comparison of variant theories of intact biochemical systems. I. Enzyme-enzyme interactions and biochemical systems theory.

A Sorribas, M A Savageau.   

Abstract

The need for a well-structured theory of intact biochemical systems becomes increasingly evident as one attempts to integrate the vast knowledge of individual molecular constituents, which has been expanding for several decades. In recent years, several apparently different approaches to the development of such a theory have been proposed. Unfortunately, the resulting theories have not been distinguished from each other, and this has led to considerable confusion with numerous duplications and rediscoveries. Detailed comparisons and critical tests of alternative theories are badly needed to reverse these unfortunate developments. In this paper we (1) characterize a specific system involving enzyme-enzyme interactions for reference in comparing alternative theories, and (2) analyze the reference system by applying the explicit S-system variant within biochemical systems theory (BST), which represents a fundamental framework based upon the power-law formalism and includes several variants. The results provide the first complete and rigorous numerical analysis within the power-law formalism of a specific biochemical system and further evidence for the accuracy of the explicit S-system variant within BST. This theory is shown to represent enzyme-enzyme interactions in a systematically structured fashion that facilitates analysis of complex biochemical systems in which these interactions play a prominent role. This representation also captures the essential character of the underlying nonlinear processes over a wide range of variation (on average 20-fold) in the independent variables of the system. In the companion paper in this issue the same reference system is analyzed by other variants within BST as well as by two additional theories within the same power-law formalism--flux-oriented and metabolic control theories. The results show how all these theories are related to one another.

Mesh:

Substances:

Year:  1989        PMID: 2520168     DOI: 10.1016/0025-5564(89)90064-3

Source DB:  PubMed          Journal:  Math Biosci        ISSN: 0025-5564            Impact factor:   2.144


  13 in total

1.  Quantitative analysis of metabolic regulation. A graph-theoretic approach using spanning trees.

Authors:  A K Sen
Journal:  Biochem J       Date:  1991-04-01       Impact factor: 3.857

2.  Calculation of control coefficients of metabolic pathways. A flux-oriented graph-theoretic approach.

Authors:  A K Sen
Journal:  Biochem J       Date:  1991-10-01       Impact factor: 3.857

3.  Algorithms for the derivation of Flux and Concentration Control Coefficients.

Authors:  A R Schulz
Journal:  Biochem J       Date:  1991-08-15       Impact factor: 3.857

4.  Structure identifiability in metabolic pathways: parameter estimation in models based on the power-law formalism.

Authors:  A Sorribas; M Cascante
Journal:  Biochem J       Date:  1994-03-01       Impact factor: 3.857

5.  Enzyme-enzyme interactions and metabolite channelling: alternative mechanisms and their evolutionary significance.

Authors:  M Cascante; A Sorribas; E I Canela
Journal:  Biochem J       Date:  1994-03-01       Impact factor: 3.857

6.  Analysis of systems influencing renal hemodynamics and sodium excretion. I. Biochemical systems theory.

Authors:  S L Reilly; C F Sing; M A Savageau; S T Turner
Journal:  Integr Physiol Behav Sci       Date:  1994 Jan-Mar

7.  Modelization and experimental studies on the control of the glycolytic-glycogenolytic pathway in rat liver.

Authors:  N V Torres
Journal:  Mol Cell Biochem       Date:  1994-03-30       Impact factor: 3.396

Review 8.  The best models of metabolism.

Authors:  Eberhard O Voit
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2017-05-19

Review 9.  Systems pathology--taking molecular pathology into a new dimension.

Authors:  Dana Faratian; Robert G Clyde; John W Crawford; David J Harrison
Journal:  Nat Rev Clin Oncol       Date:  2009-07-07       Impact factor: 66.675

10.  Use of physiological constraints to identify quantitative design principles for gene expression in yeast adaptation to heat shock.

Authors:  Ester Vilaprinyo; Rui Alves; Albert Sorribas
Journal:  BMC Bioinformatics       Date:  2006-04-03       Impact factor: 3.169

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.