Suppr超能文献

用于多聚谷氨酰胺聚集过程中无序到有序转变的粗粒度分子动力学模型。

A Coarse-Grained MD Model for Disorder-To-Order Transitions in PolyQ Aggregation.

作者信息

Dekker Maurice, van der Klok Mark L, Van der Giessen Erik, Onck Patrick R

机构信息

Zernike Institute for Advanced Materials, University of Groningen, Groningen 9747 AG, The Netherlands.

出版信息

J Chem Theory Comput. 2025 Aug 1. doi: 10.1021/acs.jctc.5c00384.

Abstract

Polyglutamine (polyQ) aggregation plays a central role in several neurodegenerative diseases, including Huntington's disease. To investigate the underlying mechanisms of polyQ aggregation, we developed a coarse-grained molecular dynamics model calibrated using atomistic simulations and experimental data. To assess the model's predictive power beyond the calibrated parameter set, we systematically varied side chain interaction strength and hydrogen bonding strength to explore a broader range of aggregation pathways. These pathways ranged from nucleated growth to liquid-to-solid phase transitions. Through seeded aggregation simulations, we observed that amyloid growth occurs primarily in the β-sheet elongation direction, although growth through steric zippering was also observed. Longer polyQ sequences (Q48) exhibited significantly faster growth compared to shorter sequences (Q23), underscoring the role of chain length in aggregation kinetics. Our model provides a versatile framework for studying polyQ aggregation and offers a foundation for investigating broader aggregation mechanisms and sequence variations.

摘要

聚谷氨酰胺(polyQ)聚集在包括亨廷顿舞蹈症在内的多种神经退行性疾病中起着核心作用。为了探究polyQ聚集的潜在机制,我们开发了一种粗粒度分子动力学模型,该模型使用原子模拟和实验数据进行了校准。为了评估该模型在校准参数集之外的预测能力,我们系统地改变了侧链相互作用强度和氢键强度,以探索更广泛的聚集途径。这些途径从成核生长到液-固相变。通过种子聚集模拟,我们观察到淀粉样生长主要发生在β-折叠延伸方向,尽管也观察到了通过空间拉链的生长。与较短序列(Q23)相比,较长的polyQ序列(Q48)表现出明显更快的生长速度,这突出了链长在聚集动力学中的作用。我们的模型为研究polyQ聚集提供了一个通用框架,并为研究更广泛的聚集机制和序列变异奠定了基础。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验