淀粉样蛋白的异常聚集是多种蛋白质构象病（如阿尔茨海默病等）的特征性病理标志物。淀粉样蛋白因错误折叠形成富含β-片层的高度有序纤维状聚集体，导致细胞功能受损和组织病变。淀粉样蛋白聚集体的构象多态性为疾病机制的理解和治疗带来了挑战。认识聚集体的构象多态性对于揭示疾病机制和开发治疗策略至关重要。

本研究旨在解析淀粉样蛋白聚集体的构象多态性，揭示其调控机制。通过使用不依赖于采集大样本获得平均化信号的扫描隧道显微术（STM），原位实空间测量蛋白质聚集体的单分子影像。测定聚集体内β-链长度分布及残基排布特征，构建构象亚稳态分布，建立蛋白聚集体异质性结构的非平均化结构表征方法。结合统计热力学理论，建立构象亚稳态的自由能分布谱。统计各构象亚稳态间相互作用概率，重构异质性构象相互作用的能量景观图，揭示聚集体形成的热力学机制。编写脚本程序，实现单分子图像的特征提取与数据可视化。该方法为解析淀粉样蛋白聚集体的构象多态性提供了可行方法。通过应用该非平均化结构解析方法，阐明淀粉样聚集体构象多态性的调控机制。围绕多个淀粉样聚集体体系，研究氨基酸序列改变、聚集时间、药物小分子及溶液环境对淀粉样蛋白聚集体构象多态性的调控规律。研究表明蛋白序列变化调控聚集体的构象亚稳态的布居分布，改变共存的构象亚稳态数量及分子间相互作用模式。微观尺度的构象亚稳态变化与宏观尺度蛋白质聚集体的热稳定性及聚集动力学特征密切相关。阐明聚集体内的共存构象随聚集时间的重排效应。伴随聚集过程，各构象亚稳态间的特异性识别作用增强，聚集体的异质性构象同步化演变，构象异质性降低。发现药物小分子干扰聚集过程，通过降低分子间特异性相互作用，调控多态性构象的微观分布。此外，聚集体的构象多态性特征也受到溶液环境调控。上述结果为理解淀粉样蛋白聚集体的构象多态性调控机制提供了重要科学依据。在此基础上，发现来自不同疾病表型捐献者的脑组织的内源性蛋白质聚集体的构象多态性存在显著性差异，为理解不同病理状态下蛋白聚集体结构的多样性和复杂性提供了新的视角。

综上所述，本论文聚焦于病理性聚集体的构象多态性，发展了基于STM技术的非平均化结构解析方法，认识了构象多态性的调控机制，揭示了构象多态性与病理表型的关联性，为认识淀粉样蛋白聚集体的结构与表型之间的内在联系提供了重要的理论基础和技术支持。

Abnormal aggregation of amyloid proteins is a characteristic pathological marker of various protein conformational diseases (such as Alzheimer's disease). Amyloid proteins form highly ordered fibrillar aggregates rich in β-sheets due to misfolding, leading to impaired cell function and tissue pathology. The conformational polymorphism of amyloid aggregates poses a huge challenge to the understanding and treatment of disease mechanisms. Understanding of the conformational polymorphism of aggregates is crucial to revealing disease mechanisms and developing therapeutic strategies.

This study aims to analyze the conformational polymorphism of amyloid aggregates and reveal their regulatory mechanisms. By using scanning tunneling microscopy (STM), which does not rely on collecting large samples to obtain averaged signals, single-molecule images of protein aggregates are measured in situ in real space. The distribution of β-chain lengths and residue arrangement characteristics in the aggregates were determined, revealing the conformational substates distribution and establishing a non-averaged structural characterization for the heterogeneous structures formed by protein aggregates. Combined with statistical thermodynamics theory, the free energy distribution landscape of conformational substates was constructed. The probability of inter-conformational interactions was analyzed, and the energy landscape of heterogeneous conformational interactions was reconstructed to reveal the thermodynamic mechanism underlying aggregation. We also independently developed a script program for automating feature extraction and data visualization. This method provides a feasible method for in-depth analysis of the conformational polymorphism of amyloid aggregates. By applying this non-averaged structural analysis method, the regulatory mechanism of amyloid aggregate conformational polymorphism was elucidated. Focusing on multiple amyloid aggregate systems, the regulation of amino acid sequence changes, aggregation time, small molecule drugs and solution environment on the conformational polymorphism of amyloid aggregates was investigated. The study shows that changes in protein sequences regulate the distribution of conformational substates within an aggregate, altering the number of coexisting conformational substates and the inter-conformational interaction modes. The conformational substate changes at the microscopic scale are closely related to the thermal stability and aggregation kinetics of macroscopic protein aggregates. The rearrangement effect of coexisting conformations in aggregates with aggregation time was elucidated. With the aggregation process, the specific recognitions between each conformational substates were enhanced. In parallel, the co-existing conformational substates within an aggregate evolved synchronously, reducing conformational heterogeneity. Small molecule drugs interfered with the aggregation process and regulated the microscopic distribution of polymorphic conformations by reducing the specific interpeptide interactions. In addition, the conformational polymorphism characteristics of aggregates are also regulated by the solution environment. The above results provide an important scientific basis for understanding the regulatory mechanism underlying the conformational polymorphism of amyloid aggregates. On this basis, it was found that there were significant differences in the conformational polymorphism of endogenous protein aggregates derived from brain tissues of donors with different disease phenotypes, which provided a new perspective for understanding the diversity and complexity of protein aggregate structures under different pathological conditions.

In summary, this thesis focuses on the conformational polymorphism of pathological aggregates, develops a non-averaged structural analysis method based on STM technology, recognizes the regulatory mechanism of conformational polymorphism, and reveals the correlation between conformational polymorphism and pathological phenotype, which provides an important theoretical basis and technical support for understanding the intrinsic connection between the structure and phenotype of amyloid aggregates.