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基于计算机的磷酸化依赖和非依赖的 c-Myc 降解的建模。

In silico modeling of phosphorylation dependent and independent c-Myc degradation.

机构信息

Bioinformatics Centre, Bose Institute, Kolkata, India.

ARC CoE for Mathematical and Statistical Frontiers, School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia.

出版信息

BMC Bioinformatics. 2019 May 8;20(1):230. doi: 10.1186/s12859-019-2846-x.

DOI:10.1186/s12859-019-2846-x
PMID:31068129
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6505206/
Abstract

BACKGROUND

c-Myc plays an important role in cell proliferation, cell growth and in differentiation, making it a key regulator for carcinogenesis and pluripotency. Tight control of c-myc turnover is required by ubiquitin-mediated degradation. This is achieved in the system by two F-box proteins Skp2 and FBXW7.

RESULTS

Dynamic modelling technique was used to build two exclusive models for phosphorylation dependent degradation of Myc by FBXW7 (Model 1) and phosphorylation independent degradation by Skp2 (Model 2). Sensitivity analysis performed on these two models revealed that these models were corroborating experimental studies. It was also seen that Model 1 was more robust and perhaps more efficient in degrading c-Myc. These results questioned the existence of the two models in the system and to answer the question a combined model was hypothesised which had a decision making switch. The combined model had both Skp2 and FBXW7 mediated degradation where again the latter played a more important role. This model was able to achieve the lowest levels of ubiquitylated Myc and therefore functioned most efficiently in degradation of Myc.

CONCLUSION

In this report, c-Myc degradation by two F-box proteins was mathematically evaluated based on the importance of c-Myc turnover. The study was performed in a homeostatic system and therefore, prompts the exploration of c-Myc degradation in cancer state and in pluripotent state.

摘要

背景

c-Myc 在细胞增殖、细胞生长和分化中发挥重要作用,使其成为致癌和多能性的关键调节剂。c-Myc 的周转率需要通过泛素介导的降解来严格控制。这是通过两种 F-box 蛋白 Skp2 和 FBXW7 来实现的。

结果

使用动态建模技术为 FBXW7 依赖性磷酸化降解 Myc(模型 1)和 Skp2 非依赖性磷酸化降解 Myc(模型 2)分别构建了两个排他性模型。对这两个模型进行的敏感性分析表明,这些模型与实验研究相符。还可以看出,模型 1 更稳健,也许在降解 c-Myc 方面更有效。这些结果对系统中是否存在这两种模型提出了质疑,为了回答这个问题,假设了一个具有决策开关的组合模型。组合模型具有 Skp2 和 FBXW7 介导的降解,后者起着更重要的作用。该模型能够实现最低水平的泛素化 Myc,因此在降解 Myc 方面效率最高。

结论

在本报告中,基于 c-Myc 周转率的重要性,对两种 F-box 蛋白的 c-Myc 降解进行了数学评估。该研究是在一个稳态系统中进行的,因此提示了在癌症状态和多能状态下探索 c-Myc 降解的可能性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bd/6505206/601f51d834c4/12859_2019_2846_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bd/6505206/2089375b522f/12859_2019_2846_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bd/6505206/aa5f83ddf6d0/12859_2019_2846_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bd/6505206/1da6bfbff4e2/12859_2019_2846_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bd/6505206/227e431da017/12859_2019_2846_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bd/6505206/95a82d62aaea/12859_2019_2846_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bd/6505206/601f51d834c4/12859_2019_2846_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bd/6505206/2089375b522f/12859_2019_2846_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bd/6505206/aa5f83ddf6d0/12859_2019_2846_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bd/6505206/1da6bfbff4e2/12859_2019_2846_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bd/6505206/227e431da017/12859_2019_2846_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bd/6505206/95a82d62aaea/12859_2019_2846_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6bd/6505206/601f51d834c4/12859_2019_2846_Fig6_HTML.jpg

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