Kerkhoven Eduard J
Department of Biology and Biological Engineering, Chalmers University of Technology, Kemivägen 10, SE412 96 Gothenburg, Sweden; Novo Nordisk Foundation Center for Biosustainability, Chalmers University of Technology, Kemivägen 10, SE-412 96 Gothenburg, Sweden.
Curr Opin Microbiol. 2022 Aug;68:102168. doi: 10.1016/j.mib.2022.102168. Epub 2022 Jun 9.
The concept of metabolic models with resource allocation constraints has been around for over a decade and has clear advantages even when implementation is relatively rudimentary. Nonetheless, the number of organisms for which such a model is reconstructed is low. Various approaches exist, from coarse-grained consideration of enzyme usage to fine-grained description of protein translation. These approaches are reviewed here, with a particular focus on user-friendly solutions that can introduce resource allocation constraints to metabolic models of any organism. The availability of k data is a major hurdle, where recent advances might help to fill in the numerous gaps that exist for this data, especially for nonmodel organisms.
具有资源分配约束的代谢模型概念已经存在了十多年，即使在实现相对初级的情况下也具有明显优势。尽管如此，重建了此类模型的生物体数量仍然很少。存在各种方法，从对酶使用的粗粒度考虑到对蛋白质翻译的细粒度描述。本文对这些方法进行了综述，特别关注可以将资源分配约束引入任何生物体代谢模型的用户友好型解决方案。k数据的可用性是一个主要障碍，而最近的进展可能有助于填补该数据存在的众多空白，尤其是对于非模式生物。
