Metabolic engineering (ME) strategies have been implemented over the last few years, in order to improve microbial strains of interest in industrial biotechnology. With the advent of experimental data concerning to regulatory aspects, several efforts have been conducted to incorporate this information in genome-scale metabolic models, aiming at the improvement of phenotype simulation methods. However, most of these methods can be used only by computer science experts, since they are not available in user-friendly software ME frameworks. This work presents Reg40ptFlux, a computational framework for ME, that integrates methods for phenotype simulation and optimization strain design, relying on integrated metabolic and regulatory models. Meta-heuristic approaches such as Evolutionary Algorithms and Simulated Annealing were appropriately modified to accommodate the optimization tasks, and were applied to study the optimization of ethanol and succinic acid production using an integrated model of the E.coli host. The framework was implemented as a plug-in for OptFlux, an open-source software for ME, and it is available in the OptFlux web site (www.optftux.org).