Metabolic pathway analysis using a nash equilibrium approach

Angelo Lucia (), Peter A. DiMaggio and Diego Alonso-Martinez
Additional contact information
Angelo Lucia: University of Rhode Island
Peter A. DiMaggio: Imperial College London
Diego Alonso-Martinez: Imperial College London

Journal of Global Optimization, 2018, vol. 71, issue 3, No 7, 537-550

Abstract: Abstract A novel approach to metabolic network analysis using a Nash Equilibrium (NE) formulation is proposed in which enzymes are considered players in a multi-player game. Each player has its own payoff function with the objective of minimizing the Gibbs free energy associated with the biochemical reaction(s) it catalyzes subject to elemental mass balances while the network objective is to find the best solution to the sum of the player payoff functions. Consequently, any NE solution may not be best solution for all players. Key advantages of the NE approach include the ability to account for (1) aqueous electrolyte behavior, (2) the consumption/production of co-factors, and (3) charge balancing. However, the proposed Nash equilibrium formulation results in a set of nonlinear programming sub-problems that are more demanding to solve than conventional flux balance analysis (FBA) formulations which rely on linear programming. A direct substitution solution methodology for pathways with feedback is described. The Krebs cycle is used to demonstrate the efficacy of the NE approach while comparisons with both FBA and experimental data are used to show that it represents a paradigm shift in metabolic network analysis.

Keywords: Metabolic pathway analysis; Nash equilibrium; Flux balance analysis; Krebs cycle (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s10898-018-0605-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:jglopt:v:71:y:2018:i:3:d:10.1007_s10898-018-0605-6

Ordering information: This journal article can be ordered from
http://www.springer. ... search/journal/10898

DOI: 10.1007/s10898-018-0605-6

Access Statistics for this article

Journal of Global Optimization is currently edited by Sergiy Butenko

More articles in Journal of Global Optimization from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().