Ab initio prediction of thermodynamically feasible reaction directions from biochemical network stoichiometry.
ABSTRACT Analysis of the stoichiometric structure of metabolic networks provides insights into the relationships between structure, function, and regulation of metabolic systems. Based on knowledge of only reaction stoichiometry, certain aspects of network functionality and robustness can be predicted. Current theories focus on breaking a metabolic network down into non-decomposable pathways able to operate in steady state. The physics underlying these theories is based on mass balance and the laws of thermodynamics. However, due to the inherent nonlinearity of the thermodynamic constraints on metabolic fluxes, computational analysis of large-scale biochemical systems can be expensive. In this study, it is shown how the feasible reaction directions may be determined by either computing the allowable ranges under the mass-balance and thermodynamic constraints or by analyzing the stoichiometric structure of the network. The computed reaction directions translate into a set of linear constraints necessary for thermodynamic feasibility. This set of necessary linear constraints is shown to be sufficient to guarantee feasibility in certain cases, thus translating the nonlinear thermodynamic constraints to linear. We show that for a reaction network of 44 internal reactions representing energy metabolism, the computed linear inequality constraints represent necessary and sufficient conditions for thermodynamic feasibility.
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ABSTRACT: The constraint-based approach to analysis of biochemical systems has emerged as a useful tool for rational metabolic engineering. Flux balance analysis (FBA) is based on the constraint of mass conservation; energy balance analysis (EBA) is based on non-equilibrium thermodynamics. The power of these approaches lies in the fact that the constraints are based on physical laws, and do not make use of unknown parameters. Here, we show that the network structure (i.e. the stoichiometric matrix) alone provides a system of constraints on the fluxes in a biochemical network which are feasible according to both mass balance and the laws of thermodynamics. A realistic example shows that these constraints can be sufficient for deriving unambiguous, biologically meaningful results. The thermodynamic constraints are obtained by comparing of the sign pattern of the flux vector to the sign patterns of the cycles of the internal cycle space via connection between stoichiometric network theory (SNT) and the mathematical theory of oriented matroids.Journal of Theoretical Biology 07/2004; 228(3):327-33. · 2.35 Impact Factor
- Environmental Microbiology 04/2002; 4(3):133-40. · 5.76 Impact Factor
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ABSTRACT: Bioinformatics is yielding extensive, and in some cases complete, genetic and biochemical information about individual cell types and cellular processes, providing the composition of living cells and the molecular structure of its components. These components together perform integrated cellular functions that now need to be analyzed. In particular, the functional definition of biochemical pathways and their role in the context of the whole cell is lacking. In this study, we show how the mass balance constraints that govern the function of biochemical reaction networks lead to the translation of this problem into the realm of linear algebra. The functional capabilities of biochemical reaction networks, and thus the choices that cells can make, are reflected in the null space of their stoichiometric matrix. The null space is spanned by a finite number of basis vectors. We present an algorithm for the synthesis of a set of basis vectors for spanning the null space of the stoichiometric matrix, in which these basis vectors represent the underlying biochemical pathways that are fundamental to the corresponding biochemical reaction network. In other words, all possible flux distributions achievable by a defined set of biochemical reactions are represented by a linear combination of these basis pathways. These basis pathways thus represent the underlying pathway structure of the defined biochemical reaction network. This development is significant from a fundamental and conceptual standpoint because it yields a holistic definition of biochemical pathways in contrast to definitions that have arisen from the historical development of our knowledge about biochemical processes. Additionally, this new conceptual framework will be important in defining, characterizing, and studying biochemical pathways from the rapidly growing information on cellular function.Proceedings of the National Academy of Sciences 04/1998; 95(8):4193-8. · 9.74 Impact Factor