Revisiting the earliest signatures of amyloidogenesis: Roadmaps emerging from computational modeling and experiment

内在无序蛋白质 计算生物学 淀粉样纤维 机制(生物学) 淀粉样蛋白(真菌学) 化学 构象集合 淀粉样β 药物发现 计算机科学 纳米技术 生物物理学 分子动力学 神经科学 生物 疾病 物理 生物化学 计算化学 材料科学 医学 病理 无机化学 量子力学
作者
Shayon Bhattacharya,Liang Xu,Damien Thompson
出处
期刊:Wiley Interdisciplinary Reviews: Computational Molecular Science [Wiley]
卷期号:8 (4) 被引量:15
标识
DOI:10.1002/wcms.1359
摘要

Neurodegenerative amyloidogenesis begins with the aggregation of intrinsically disordered proteins (IDPs), which is the first step in a cascade of assembly events that can lead to insoluble fibrous deposits in brain tissue. IDP conformations that promote formation of toxic oligomers remain poorly understood, and are the most fundamental target of putative treatments for neurodegenerative disease. Rapid advances in theory, simulation and experimental methods, hold the promise of reversing protein aggregation by identifying and developing inhibitors of the transient amyloidogenic IDP conformations. To make meaningful progress it is important to appreciate the benefits and limitations of the latest developments in computational methods of conformational and ensemble modeling, and their integration and validation with experiments. Integrated studies are beginning to provide significant conceptual and mechanistic insights, including identification of the properties of amyloidogenic IDPs in their free, unbound form. At the same time, contradicting viewpoints have emerged concerning convergence of IDP ensemble signatures and properties from parallel studies, and there also remains a pressing need to develop physical models that can deliver reliable predictions across different IDP families. Focussing on the four most common amyloidogenic IDPs of Amyloid β, Tau, α‐synuclein and Prions, improvements are proposed for next‐generation models and experiments that can potentially identify drug treatments for neurodegenerative disease via incorporation of the extended cellular environment. This article is categorized under: Molecular and Statistical Mechanics > Molecular Mechanics Structure and Mechanism > Computational Biochemistry and Biophysics Structure and Mechanism > Molecular Structures
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