Dekker Maurice, van der Klok Mark L, Van der Giessen Erik, Onck Patrick R
Zernike Institute for Advanced Materials, University of Groningen, Groningen 9747 AG, The Netherlands.
J Chem Theory Comput. 2025 Aug 1. doi: 10.1021/acs.jctc.5c00384.
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.
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。
