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通过数学建模理解mTOR信号通路。

Understanding the mTOR signaling pathway via mathematical modeling.

作者信息

Sulaimanov Nurgazy, Klose Martin, Busch Hauke, Boerries Melanie

机构信息

Department of Electrical Engineering and Information Technology, Technische Universität Darmstadt, Darmstadt, Germany.

Department of Biology, Technische Universitat Darmstadt, Darmstadt, Germany.

出版信息

Wiley Interdiscip Rev Syst Biol Med. 2017 Jul;9(4). doi: 10.1002/wsbm.1379. Epub 2017 Feb 10.

DOI:10.1002/wsbm.1379
PMID:28186392
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5573916/
Abstract

The mechanistic target of rapamycin (mTOR) is a central regulatory pathway that integrates a variety of environmental cues to control cellular growth and homeostasis by intricate molecular feedbacks. In spite of extensive knowledge about its components, the molecular understanding of how these function together in space and time remains poor and there is a need for Systems Biology approaches to perform systematic analyses. In this work, we review the recent progress how the combined efforts of mathematical models and quantitative experiments shed new light on our understanding of the mTOR signaling pathway. In particular, we discuss the modeling concepts applied in mTOR signaling, the role of multiple feedbacks and the crosstalk mechanisms of mTOR with other signaling pathways. We also discuss the contribution of principles from information and network theory that have been successfully applied in dissecting design principles of the mTOR signaling network. We finally propose to classify the mTOR models in terms of the time scale and network complexity, and outline the importance of the classification toward the development of highly comprehensive and predictive models. WIREs Syst Biol Med 2017, 9:e1379. doi: 10.1002/wsbm.1379 For further resources related to this article, please visit the WIREs website.

摘要

雷帕霉素的作用机制靶点(mTOR)是一条核心调控通路,它整合多种环境信号,通过复杂的分子反馈来控制细胞生长和内环境稳定。尽管对其组成部分已有广泛了解,但对于这些组成部分如何在空间和时间上协同发挥作用的分子层面理解仍很匮乏,因此需要采用系统生物学方法进行系统分析。在这项工作中,我们回顾了数学模型与定量实验的联合研究如何为我们理解mTOR信号通路带来新的启示。特别地,我们讨论了应用于mTOR信号传导的建模概念、多重反馈的作用以及mTOR与其他信号通路的串扰机制。我们还讨论了信息和网络理论原理在剖析mTOR信号网络设计原理方面的贡献。最后,我们建议根据时间尺度和网络复杂性对mTOR模型进行分类,并概述这种分类对于开发高度全面且具有预测性的模型的重要性。《WIREs系统生物学与医学》2017年第9卷,e1379。doi: 10.1002/wsbm.1379 有关本文的更多资源,请访问WIREs网站。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d0c/5573916/bfea4ab4a3f5/WSBM-9-na-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d0c/5573916/7356fbbcbdc1/WSBM-9-na-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d0c/5573916/8a93b4cb1a30/WSBM-9-na-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d0c/5573916/55813acfc445/WSBM-9-na-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d0c/5573916/bfea4ab4a3f5/WSBM-9-na-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d0c/5573916/7356fbbcbdc1/WSBM-9-na-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d0c/5573916/8a93b4cb1a30/WSBM-9-na-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d0c/5573916/55813acfc445/WSBM-9-na-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d0c/5573916/bfea4ab4a3f5/WSBM-9-na-g004.jpg

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