IBB-Institute for Biotechnology and Bioengineering/Centre of Biological Engineering, University of Minho, Campus de Gualtar, Braga, Portugal.
Metab Eng. 2012 Mar;14(2):112-9. doi: 10.1016/j.ymben.2012.01.003. Epub 2012 Jan 28.
Systems biology provides new approaches for metabolic engineering through the development of models and methods for simulation and optimization of microbial metabolism. Here we explore the relationship between two modeling frameworks in common use namely, dynamic models with kinetic rate laws and constraint-based flux models. We compare and analyze dynamic and constraint-based formulations of the same model of the central carbon metabolism of Escherichia coli. Our results show that, if unconstrained, the space of steady states described by both formulations is the same. However, the imposition of parameter-range constraints can be mapped into kinetically feasible regions of the solution space for the dynamic formulation that is not readily transferable to the constraint-based formulation. Therefore, with partial kinetic parameter knowledge, dynamic models can be used to generate constraints that reduce the solution space below that identified by constraint-based models, eliminating infeasible solutions and increasing the accuracy of simulation and optimization methods.
系统生物学通过开发模拟和优化微生物代谢的模型和方法，为代谢工程提供了新的方法。在这里，我们探讨了两种常用建模框架之间的关系，即具有动力学速率定律的动态模型和基于约束的通量模型。我们比较和分析了大肠杆菌中心碳代谢的相同模型的动态和基于约束的公式。我们的结果表明，如果没有约束，两种公式描述的稳定状态空间是相同的。然而，参数范围约束的施加可以映射到动态公式的解决方案空间的动力学可行区域，而不能轻易转换为基于约束的公式。因此，具有部分动力学参数知识的动态模型可以用于生成约束，从而缩小基于约束的模型确定的解决方案空间，消除不可行的解决方案，并提高模拟和优化方法的准确性。
