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通过建模与优化理解病毒蛋白对I型干扰素信号通路的抑制作用。

Understanding inhibition of viral proteins on type I IFN signaling pathways with modeling and optimization.

作者信息

Zou Xiufen, Xiang Xueshuang, Chen Yan, Peng Tao, Luo Xuelian, Pan Zishu

机构信息

School of Mathematics and Statistics, Wuhan University, Wuhan, China.

出版信息

J Theor Biol. 2010 Aug 21;265(4):691-703. doi: 10.1016/j.jtbi.2010.05.001. Epub 2010 May 27.

Abstract

The interferon system provides a powerful and universal intracellular defense mechanism against viruses. As one part of their survival strategies, many viruses have evolved mechanisms to counteract the host type I interferon (IFN-alpha/beta) responses. In this study, we attempt to investigate virus- and double-strand RNA (dsRNA)-triggered type I IFN signaling pathways and understand the inhibition of IFN-alpha/beta induction by viral proteins using mathematical modeling and quantitative analysis. Based on available literature and our experimental data, we develop a mathematical model of virus- and dsRNA-triggered signaling pathways leading to type I IFN gene expression during the primary response, and use the genetic algorithm to optimize all rate constants in the model. The consistency between numerical simulation results and biological experimental data demonstrates that our model is reasonable. Further, we use the model to predict the following phenomena: (1) the dose-dependent inhibition by classical swine fever virus (CSFV) N(pro) or E(rns) protein is observed at a low dose and can reach a saturation above a certain dose, not an increase; (2) E(rns) and N(pro) have no synergic inhibitory effects on IFN-beta induction; (3) the different characters in an important transcription factor, phosphorylated IRF3 (IRF3p), are exhibited because N(pro) or E(rns) counteracted dsRNA- and virus-triggered IFN-beta induction by targeting the different molecules in the signaling pathways and (4) N(pro) inhibits the IFN-beta expression not only by interacting with IFR3 but also by affecting its complex with MITA. Our approaches help to gain insight into system properties and rational therapy design, as well as to generate hypotheses for further research.

摘要

干扰素系统为抵抗病毒提供了一种强大且通用的细胞内防御机制。作为其生存策略的一部分,许多病毒已经进化出对抗宿主I型干扰素(IFN-α/β)反应的机制。在本研究中,我们试图利用数学建模和定量分析来研究病毒和双链RNA(dsRNA)触发的I型干扰素信号通路,并了解病毒蛋白对IFN-α/β诱导的抑制作用。基于现有文献和我们的实验数据,我们建立了一个在初次反应期间导致I型干扰素基因表达的病毒和dsRNA触发信号通路的数学模型,并使用遗传算法优化模型中的所有速率常数。数值模拟结果与生物学实验数据之间的一致性表明我们的模型是合理的。此外,我们使用该模型预测以下现象:(1)经典猪瘟病毒(CSFV)N(pro)或E(rns)蛋白在低剂量时观察到剂量依赖性抑制,在一定剂量以上可达到饱和,而非增加;(2)E(rns)和N(pro)对IFN-β诱导没有协同抑制作用;(3)重要转录因子磷酸化IRF3(IRF3p)表现出不同特征,因为N(pro)或E(rns)通过靶向信号通路中的不同分子来对抗dsRNA和病毒触发的IFN-β诱导;以及(4)N(pro)不仅通过与IFR3相互作用抑制IFN-β表达,还通过影响其与MITA的复合物来抑制。我们的方法有助于深入了解系统特性和合理的治疗设计,以及为进一步研究提出假设。

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