An Outer Approximation Algorithm for the Global Optimization of Regulated Metabolic Systems

Abstract Understanding the evolution of cellular metabolism requires a number of techniques able to deal with its complexity. Adaptive responses observed in evolutive studies are expected to consist of an optimal set of changes in enzymes activities fulfilling important physiological constraints. Within this context, we present a novel approach to identify enzyme activity regions that contain feasible biological responses in evolution. The framework presented also allows to optimize the enzyme activity changes required to maximize certain fluxes in biotechnological applications. The method relies on solving nonlinear programming models via global optimization techniques.