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用于代谢大规模模拟的混合动态/静态方法

Hybrid dynamic/static method for large-scale simulation of metabolism.

作者信息

Yugi Katsuyuki, Nakayama Yoichi, Kinoshita Ayako, Tomita Masaru

机构信息

Institute for Advanced Biosciences, Keio University, Fujisawa, Kanagawa, 252-8520, Japan.

出版信息

Theor Biol Med Model. 2005 Oct 4;2:42. doi: 10.1186/1742-4682-2-42.

Abstract

BACKGROUND

Many computer studies have employed either dynamic simulation or metabolic flux analysis (MFA) to predict the behaviour of biochemical pathways. Dynamic simulation determines the time evolution of pathway properties in response to environmental changes, whereas MFA provides only a snapshot of pathway properties within a particular set of environmental conditions. However, owing to the large amount of kinetic data required for dynamic simulation, MFA, which requires less information, has been used to manipulate large-scale pathways to determine metabolic outcomes.

RESULTS

Here we describe a simulation method based on cooperation between kinetics-based dynamic models and MFA-based static models. This hybrid method enables quasi-dynamic simulations of large-scale metabolic pathways, while drastically reducing the number of kinetics assays needed for dynamic simulations. The dynamic behaviour of metabolic pathways predicted by our method is almost identical to that determined by dynamic kinetic simulation.

CONCLUSION

The discrepancies between the dynamic and the hybrid models were sufficiently small to prove that an MFA-based static module is capable of performing dynamic simulations as accurately as kinetic models. Our hybrid method reduces the number of biochemical experiments required for dynamic models of large-scale metabolic pathways by replacing suitable enzyme reactions with a static module.

摘要

背景

许多计算机研究采用动态模拟或代谢通量分析(MFA)来预测生化途径的行为。动态模拟确定途径特性随环境变化的时间演变,而MFA仅提供特定环境条件下途径特性的一个快照。然而,由于动态模拟需要大量动力学数据,信息需求较少的MFA已被用于操纵大规模途径以确定代谢结果。

结果

在此,我们描述一种基于基于动力学的动态模型与基于MFA的静态模型之间协作的模拟方法。这种混合方法能够对大规模代谢途径进行准动态模拟,同时大幅减少动态模拟所需的动力学测定数量。我们的方法预测的代谢途径动态行为与动态动力学模拟确定的行为几乎相同。

结论

动态模型与混合模型之间的差异足够小,足以证明基于MFA的静态模块能够像动力学模型一样准确地进行动态模拟。我们的混合方法通过用静态模块替代合适的酶反应,减少了大规模代谢途径动态模型所需的生化实验数量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/56a2/1262783/5d2a938682cb/1742-4682-2-42-1.jpg

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