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评估淀粉样纤维和无定形聚集体:综述

Assessing amyloid fibrils and amorphous aggregates: A review.

作者信息

Basha Shaik, Mukunda Darshan Chikkanayakanahalli, Pai Aparna Ramakrishna, Mahato Krishna Kishore

机构信息

Department of Biophysics, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal 576104, Karnataka, India.

Department of Neurology, Kasturba Medical College Manipal, Manipal Academy of Higher Education, Manipal 576104, Karnataka, India.

出版信息

Int J Biol Macromol. 2025 Jun;311(Pt 3):143725. doi: 10.1016/j.ijbiomac.2025.143725. Epub 2025 May 3.

Abstract

Protein misfolding and aggregation play a central role in the progression of neurodegenerative diseases such as Alzheimer's and Parkinson's. These aggregates manifest either as structured amyloid fibrils enriched in β-sheet conformations or as irregular amorphous aggregates with diverse morphologies. Understanding their formation, structure, and behavior is critical for deciphering disease mechanisms and developing targeted diagnostics and therapeutics. This review presents an integrated overview of both conventional and advanced techniques used to detect, distinguish, and structurally characterize these protein aggregates. It covers a range of spectroscopic and spectrometric tools, such as fluorescence, Raman, and mass spectrometry that facilitate aggregate identification. Microscopy methods, including atomic force and electron microscopy, are highlighted for morphological analysis. The review also discusses in situ detection strategies using fluorescent dyes, conformation-specific antibodies, enzymatic reporters, and real-time imaging. Separation methods like centrifugation, electrophoresis, and chromatography are outlined alongside structural analysis tools such as X-ray diffraction. Furthermore, the growing utility of computational approaches and artificial intelligence in predicting aggregation propensities and integrating biological data is emphasized. By critically evaluating each method's capabilities and limitations, this review provides a practical and forward-looking resource for researchers studying the complex landscape of protein aggregation.

摘要

蛋白质错误折叠和聚集在阿尔茨海默病和帕金森病等神经退行性疾病的进展中起着核心作用。这些聚集体表现为富含β-折叠构象的结构化淀粉样纤维,或表现为具有不同形态的不规则无定形聚集体。了解它们的形成、结构和行为对于解读疾病机制以及开发靶向诊断和治疗方法至关重要。本综述对用于检测、区分和对这些蛋白质聚集体进行结构表征的传统技术和先进技术进行了综合概述。它涵盖了一系列光谱和光谱分析工具,如荧光、拉曼光谱和质谱,这些工具有助于聚集体的鉴定。重点介绍了包括原子力显微镜和电子显微镜在内的显微镜方法用于形态分析。本综述还讨论了使用荧光染料、构象特异性抗体、酶报告分子和实时成像的原位检测策略。概述了诸如离心、电泳和色谱等分离方法以及诸如X射线衍射等结构分析工具。此外,强调了计算方法和人工智能在预测聚集倾向和整合生物数据方面日益增长的效用。通过批判性地评估每种方法的能力和局限性,本综述为研究蛋白质聚集复杂情况的研究人员提供了实用且具有前瞻性的资源。

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