The transduction of free energy in metabolic networks represents a thermodynamic mechanism by which the free energy derived from nutrients is converted to drive nonspontaneous, energy-requiring metabolic reactions. This transduction is typically observed in processes that generate energy-rich molecules such as ATP and NAD(P)H, which, in turn, power specific reactions, particularly biosynthetic reactions. This property establishes a pivotal connection between the intricate topology of metabolic networks and their ability to redirect energy for functional purposes. The present study proposes a dedicated framework aimed at exploring the relationship between free-energy dissipation, network topology, and metabolic objectives. The starting point is that, regardless of the network topology, nonequilibrium chemostatting conditions impose stringent thermodynamic constraints on the feasible flux steady states to satisfy energy and entropy balances. An analysis of randomly sampled reaction networks shows that the network topology imposes additional constraints that restrict the accessible flux solution space, depending on key structural features such as the reaction’s molecularity, reaction cycles, and conservation laws. Notably, topologies featuring multimolecular reactions that implement free-energy transduction mechanisms tend to extend the accessible flux domains, facilitating the achievement of metabolic objectives such as anabolic flux maximization or flux rerouting capacity. This approach is applied to a coarse-grained model of carbohydrate metabolism, highlighting the structural requirements for optimal biomass yield.

中文翻译：

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自由能转导机制塑造代谢网络的通量空间


代谢网络中自由能的转导代表了一种热力学机制，通过该机制，从营养物质中获得的自由能被转化为驱动非自发的、需要能量的代谢反应。这种转导通常在产生富含能量的分子（如 ATP 和 NAD（P）H））的过程中观察到，而这些分子反过来又为特定反应提供动力，尤其是生物合成反应。这一特性在代谢网络的复杂拓扑结构与其为功能目的重定向能量的能力之间建立了关键联系。本研究提出了一个专门的框架，旨在探索自由能耗散、网络拓扑和代谢目标之间的关系。首先，无论网络拓扑如何，非平衡化学静化条件都会对可行的磁通量稳态施加严格的热力学约束，以满足能量和熵平衡。对随机采样反应网络的分析表明，网络拓扑施加了额外的约束，这些约束限制了可访问的通量溶液空间，具体取决于反应的分子、反应循环和守恒定律等关键结构特征。值得注意的是，具有实现自由能转导机制的多分子反应的拓扑结构往往会扩展可接近的通量结构域，从而促进实现代谢目标，例如合成代谢通量最大化或通量重路由能力。这种方法应用于碳水化合物代谢的粗粒度模型，突出了最佳生物质产量的结构要求。