基于最大熵原理的可断裂淀粉样蛋白丝还原模型热力学

Xinyu Zhang, Haiyang Jia, Wuyue Yang, Liangrong Peng, Liu Hong
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引用次数: 0

摘要

淀粉样蛋白丝与神经退行性疾病(如阿尔茨海默氏症和帕金森氏症)有关。淀粉样蛋白聚集的简化模型至关重要,因为原始的质量-作用方程涉及众多变量,使分析和理解复杂化。虽然简化模型的动力学方面已被广泛研究,但对其热力学特性的了解却较少。在本研究中,我们从全新的热力学角度探讨了最初为动力学分析而开发的最大熵原理(MEP)简化模型。分析表达式和数值模拟证明,离散的 MEP 还原模型严格遵守热力学定律,即使当丝的长度从离散值转变为连续实数时也是如此。我们的发现不仅首次阐明了 MEP 还原模型与淀粉样蛋白丝原始模型之间的热力学一致性,而且为未来研究模型还原热力学提供了线索。
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Thermodynamics for Reduced Models of Breakable Amyloid Filaments Based on Maximum Entropy Principle
Amyloid filaments are associated with neurodegenerative diseases such as Alzheimer's and Parkinson's. Simplified models of amyloid aggregation are crucial because the original mass-action equations involve numerous variables, complicating analysis and understanding. While dynamical aspects of simplified models have been widely studied, their thermodynamic properties are less understood. In this study, we explore the Maximum Entropy Principle (MEP)-reduced models, initially developed for dynamical analysis, from a brand-new thermodynamic perspective. Analytical expressions along with numerical simulations demonstrate that the discrete MEP-reduced model strictly retains laws of thermodynamics, which holds true even when filament lengths transit from discrete values to continuous real numbers. Our findings not only clarify the thermodynamic consistency between the MEP-reduced models and the original models of amyloid filaments for the first time, but also suggest avenues for future research into the model-reduction thermodynamics.
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