Energy Balance for Analysis of Complex Metabolic Networks

Abstract

Predicting behavior of large-scale biochemical networks represents one of the greatest challenges of bioinformatics and computational biology. Computational tools for predicting fluxes in biochemical networks are applied in the fields of integrated and systems biology, bioinformatics, and genomics, and to aid in drug discovery and identification of potential drug targets. Approaches, such as flux balance analysis (FBA), that account for the known stoichiometry of the reaction network while avoiding implementation of detailed reaction kinetics are promising tools for the analysis of large complex networks. Here we introduce energy balance analysis (EBA)--the theory and methodology for enforcing the laws of thermodynamics in such simulations--making the results more physically realistic and revealing greater insight into the regulatory and control mechanisms operating in complex large-scale systems. We show that EBA eliminates thermodynamically infeasible results associated with FBA.

Dissipation and maintenance of stable states in an enzymatic system: Analysis and simulation

“…Kinetic constraints [16,17] are conditions under which the reaction establishes stable states. Thermodynamic constraints restrict the direction of the reactions [1,[11][12][13][14][15]. Although thermodynamic and kinetic constraints restrict different aspects of the reaction, they can be closely related.…”

“…Energy conservation and dissipation in biochemical networks are important aspects for understanding biological functions [1,[11][12][13][14][15]26]. In particular, in nonlinear autonomous and forced reaction systems, thermodynamic efficiency and dissipation have been systematically studied [23][24][25].…”

“…Those constraints restrict different aspects of the network. Specifically, stoichiometric constraints restrict the molar relation of reactants; thermodynamic constraints confine the direction of reactions [1,[11][12][13][14][15]; and kinetic constraints guarantee the formation of stable states that are necessary for implementing biological functions [16,17]. In a network, each enzymatic reaction is an essential component for constructing the network, and it also has a boundary at which substrate is supplied and product is removed.…”

“…The total dissipation of those elementary reactions represents the thermodynamic dissipation of the enzyme reaction. Furthermore, dissipation is closely associated with the concept of thermodynamic constraints [1,[11][12][13][14][15]. Is the maintenance of a stable state related to other properties of the system?…”

The growing scope of applications of genome-scale metabolic reconstructions using Escherichia coli

“…Predictive capability is expected to improve through examining growth behavior across a greater number of environments (additional phenotyping screens will be necessary) and with an increase of integration of additional cellular processes. Genetic perturbations have played a key role in the study of the genotypephenotype relationship in biology and GEMs can be used to mechanistically interpret the results and predict the outcomes of such perturbations.Incorporating thermodynamic information into E. coli GEMs has shown promise in narrowing predictions of allowable physiological states in a given environment 19,40,47,49,52,54,55,57,61 and in identifying reactions likely to be subject to active allosteric or genetic regulation 49,54 . This field is progressing rapidly and should prove to increase the predictive capabilities of genome-scale modeling through the addition of governing thermodynamic physiochemical constrains.…”