Probabilistic thermodynamic analysis of metabolic networks.

ABSTRACT:

Motivation

Random sampling of metabolic fluxes can provide a comprehensive description of the capabilities of a metabolic network. However, current sampling approaches do not model thermodynamics explicitly, leading to inaccurate predictions of an organism's potential or actual metabolic operations.

Results

We present a probabilistic framework combining thermodynamic quantities with steady-state flux constraints to analyze the properties of a metabolic network. It includes methods for probabilistic metabolic optimization and for joint sampling of thermodynamic and flux spaces. Applied to a model of Escherichia coli, we use the methods to reveal known and novel mechanisms of substrate channeling, and to accurately predict reaction directions and metabolite concentrations. Int

SUBMITTER: Gollub MG 

PROVIDER: S-EPMC8479673 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature