ASSESSING OPTIMAL DESIGNS IN METABOLIC PATHWAYS

1995 ◽  
Vol 03 (01) ◽  
pp. 197-206 ◽  
Author(s):  
J. PUIGJANER ◽  
M. CASCANTE ◽  
A. SORRIBAS
Keyword(s):  
Metabolic Pathways ◽  
Reaction Network ◽  
Metabolic Control Analysis ◽  
Optimal Designs ◽  
Control Analysis ◽  
Chemical Transformations ◽  
Evolution Of Metabolic Pathways ◽  
Biochemical Systems ◽  
Optimum Reaction ◽  
Alternative Designs

The evolution of metabolic pathways is characterized by the search of the optimum reaction network, both as for chemical transformations and for the associated pattern of regulation. Understanding this process requires the evaluation of alternative designs for a given function. After this evaluation, we would be in a good situation for drawing general conclusions on the evolution of the considered system. This goal can be undertaken by means of different complementary approaches. The method of Control Comparisons, first developed within Biochemical Systems Analysis, has produced some valuable insights on this kind of problems. In this contribution, we present this method within the context of Metabolic Control Analysis.

Deterministic Modeling in Medicine

2009 ◽  
pp. 74-96
Author(s):  
Elisabeth Maschke-Dutz
Keyword(s):  
Metabolic Control ◽  
Data Exchange ◽  
Time Course ◽  
Metabolic Control Analysis ◽  
Test Case ◽  
Control Analysis ◽  
Mathematical Methods ◽  
Apoptosis Pathway ◽  
Biochemical Systems ◽  
Extrinsic Apoptosis

In this chapter basic mathematical methods for the deterministic kinetic modeling of biochemical systems are described. Mathematical analysis methods, the respective algorithms, and appropriate tools and resources, as well as established standards for data exchange, model representations and definitions are presented. The methods comprise time-course simulations, steady state search, parameter scanning, and metabolic control analysis among others. An application is demonstrated using a test case model that describes parts of the extrinsic apoptosis pathway and a small example network demonstrates an implementation of metabolic control analysis.

scholarly journals Thermodynamic constraints on the regulation of metabolic fluxes

2018 ◽  
Author(s):  
Ziwei Dai ◽  
Jason W. Locasale
Keyword(s):  
Metabolic Control ◽  
Metabolic Pathways ◽  
Metabolic Control Analysis ◽  
Control Analysis ◽  
Specific Enzyme ◽  
Metabolic Fluxes ◽  
Activity Of Enzymes ◽  
Far From Equilibrium ◽  
Physical Variables ◽  
The Given

AbstractNutrition and metabolism are fundamental to cellular function in physiological and pathological contexts. Metabolic activity (i.e. rates, flow, or most commonly referred to as flux) is constrained by thermodynamics and regulated by the activity of enzymes. The general principles that relate biological and physical variables to metabolic control are incompletely understood. Using metabolic control analysis in several representative topological structures of metabolic pathways as models, we derive exact results and conduct computer simulations that define relationships between thermodynamics, enzyme activity, and flux control. We confirm that metabolic pathways that are very far from equilibrium are controlled by the activity of upstream enzymes. However, in general, metabolic pathways have a more adaptable pattern of regulation, controlled minimally by thermodynamics and not necessarily by the specific enzyme that generates the given reaction. These findings show how the control of metabolic pathways, which are rarely very far from equilibrium, is largely set by the overall flux through a pathway rather than by the enzyme which generates the flux or by thermodynamics.

Drug Target Selection for Trypanosoma cruzi Metabolism by Metabolic Control Analysis and Kinetic Modeling

2019 ◽  
Vol 26 (36) ◽  
pp. 6652-6671 ◽  
Author(s):  
Emma Saavedra ◽  
Zabdi González-Chávez ◽  
Rafael Moreno-Sánchez ◽  
Paul A.M. Michels
Keyword(s):  
Trypanosoma Cruzi ◽  
Metabolic Control ◽  
Kinetic Modeling ◽  
Metabolic Pathways ◽  
Drug Target ◽  
Metabolic Modeling ◽  
Metabolic Control Analysis ◽  
Control Analysis ◽  
Control Coefficient ◽  
Flux Control

In the search for therapeutic targets in the intermediary metabolism of trypanosomatids the gene essentiality criterion as determined by using knock-out and knock-down genetic strategies is commonly applied. As most of the evaluated enzymes/transporters have turned out to be essential for parasite survival, additional criteria and approaches are clearly required for suitable drug target prioritization. The fundamentals of Metabolic Control Analysis (MCA; an approach in the study of control and regulation of metabolism) and kinetic modeling of metabolic pathways (a bottom-up systems biology approach) allow quantification of the degree of control that each enzyme exerts on the pathway flux (flux control coefficient) and metabolic intermediate concentrations (concentration control coefficient). MCA studies have demonstrated that metabolic pathways usually have two or three enzymes with the highest control of flux; their inhibition has more negative effects on the pathway function than inhibition of enzymes exerting low flux control. Therefore, the enzymes with the highest pathway control are the most convenient targets for therapeutic intervention. In this review, the fundamentals of MCA as well as experimental strategies to determine the flux control coefficients and metabolic modeling are analyzed. MCA and kinetic modeling have been applied to trypanothione metabolism in Trypanosoma cruzi and the model predictions subsequently validated in vivo. The results showed that three out of ten enzyme reactions analyzed in the T. cruzi anti-oxidant metabolism were the most controlling enzymes. Hence, MCA and metabolic modeling allow a further step in target prioritization for drug development against trypanosomatids and other parasites.

Synthesis and Breakdown of the Universal Precursors to Biological Metabolism Promoted by Ferrous Iron

2018 ◽  
Author(s):  
Kamila B. Muchowska ◽  
Sreejith Jayasree VARMA ◽  
Joseph Moran
Keyword(s):  
Amino Acids ◽  
Chemical Reaction ◽  
Metabolic Pathways ◽  
Ferrous Iron ◽  
Reaction Network ◽  
Tca Cycle ◽  
Chemical Reaction Network ◽  
Metabolic Precursors ◽  
Tca Cycle Intermediates

How core biological metabolism initiated and why it uses the intermediates, reactions and pathways that it does remains unclear. Life builds its molecules from CO<sub>2 </sub>and breaks them down to CO<sub>2 </sub>again through the intermediacy of just five metabolites that act as the hubs of biochemistry. Here, we describe a purely chemical reaction network promoted by Fe<sup>2+ </sup>in which aqueous pyruvate and glyoxylate, two products of abiotic CO<sub>2 </sub>reduction, build up nine of the eleven TCA cycle intermediates, including all five universal metabolic precursors. The intermediates simultaneously break down to CO<sub>2 </sub>in a life-like regime resembling biological anabolism and catabolism. Introduction of hydroxylamine and Fe<sup>0 </sup>produces four biological amino acids. The network significantly overlaps the TCA/rTCA and glyoxylate cycles and may represent a prebiotic precursor to these core metabolic pathways.

scholarly journals Constraint-based metabolic control analysis for rational strain engineering

2021 ◽  
Author(s):  
Sophia Tsouka ◽  
Meric Ataman ◽  
Tuure Hameri ◽  
Ljubisa Miskovic ◽  
Vassily Hatzimanikatis
Keyword(s):  
Metabolic Control ◽  
Strain Engineering ◽  
Metabolic Control Analysis ◽  
Control Analysis
Sign in / Sign up

Export Citation Format

Share Document