Suppr超能文献

自噬化学反应网络模型的基础状态校准。

Basal State Calibration of a Chemical Reaction Network Model for Autophagy.

机构信息

Department of Molecular Biology at the Institute of Biochemistry and Molecular Biology, Semmelweis University, 1085 Budapest, Hungary.

Insititute of Materials and Environmental Chemistry, HUN-REN Research Centre for Natural Sciences, 1117 Budapest, Hungary.

出版信息

Int J Mol Sci. 2024 Oct 21;25(20):11316. doi: 10.3390/ijms252011316.

Abstract

The modulation of autophagy plays a dual role in tumor cells, with the potential to both promote and suppress tumor proliferation. In order to gain a deeper understanding of the nature of autophagy, we have developed a chemical reaction kinetic model of autophagy and apoptosis based on the mass action kinetic models that have been previously described in the literature. It is regrettable that the authors did not provide all of the information necessary to reconstruct their model, which made their simulation results irreproducible. In this study, based on an extensive literature review, we have identified concentrations for each species in the stress-free, homeostatic state. These ranges were randomly sampled to generate sets of initial concentrations, from which the simulations were run. In every case, abnormal behavior was observed, with apoptosis and autophagy being activated, even in the absence of stress. Consequently, the model failed to reproduce even the basal conditions. Detailed examination of the model revealed erroneous reactions, which were corrected. The influential kinetic parameters of the corrected model were identified and optimized using the Optima++ code. The model is now capable of simulating homeostatic states, and provides a suitable basis for further model development to describe cell response to various stresses.

摘要

自噬的调节在肿瘤细胞中起着双重作用,既可以促进也可以抑制肿瘤增殖。为了更深入地了解自噬的本质,我们根据文献中已描述的质量作用动力学模型,开发了一种自噬和细胞凋亡的化学反应动力学模型。遗憾的是,作者没有提供重建其模型所需的所有信息,这使得他们的模拟结果无法重现。在这项研究中,我们基于广泛的文献回顾,确定了无应激、稳态下每种物质的浓度。这些范围被随机抽样以生成一系列初始浓度,从这些初始浓度中运行模拟。在每种情况下,即使没有应激,也观察到了异常行为,即细胞凋亡和自噬被激活。因此,该模型甚至无法重现基础条件。对模型的详细检查揭示了错误的反应,这些反应已被纠正。使用 Optima++代码确定并优化了修正模型的影响动力学参数。该模型现在能够模拟稳态,并为进一步的模型开发提供合适的基础,以描述细胞对各种应激的反应。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b3c/11508741/80b15646a9dd/ijms-25-11316-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验