Computational insights into lipid assisted peptide misfolding and aggregation in neurodegeneration
Computational insights into lipid assisted peptide misfolding and aggregation in neurodegeneration
复制标题
神经退行性疾病中脂质辅助肽错误折叠和聚集的计算见解
DOI：
10.1039/c9cp02765c
复制
发表时间：
2019
影响因子：
3.3
通讯作者：
Matysiak, Silvina
中科院分区：
文献类型：
--
作者：
Sahoo, Abhilash;Matysiak, Silvina
膜微环境中的肽错误折叠和异常组装与许多神经退行性疾病有关。这些淀粉样膜相互作用的生物分子机制和生物物理意义已经得到了广泛的研究，有助于了解疾病的发病机制和潜在的合理治疗方法的开发。但是，生物分子相互作用的复杂性和多样性，结构转变，以及对当地环境条件的依赖，使得准确的微观表征具有挑战性。在这篇综述中，我们使用阿尔茨海默病(淀粉样β蛋白)、帕金森病(α-突触核蛋白)和亨廷顿病(亨廷顿蛋白)的病例说明了实验研究中存在的挑战，并总结了最近对淀粉样蛋白致病多肽-膜相互作用的相关数值模拟研究。此外，我们还预测了未来计算机研究的方向，并讨论了当前计算方法的不足。
Peptide misfolding and aberrant assembly in membranous micro-environments have been associated with numerous neurodegenerative diseases. The biomolecular mechanisms and biophysical implications of these amyloid membrane interactions have been under extensive research and can assist in understanding disease pathogenesis and potential development of rational therapeutics. But, the complex nature and diversity of biomolecular interactions, structural transitions, and dependence on local environmental conditions have made accurate microscopic characterization challenging. In this review, using cases of Alzheimer's disease (amyloid-beta peptide), Parkinson's disease (alpha-synuclein peptide) and Huntington's disease (huntingtin protein), we illustrate existing challenges in experimental investigations and summarize recent relevant numerical simulation studies into amyloidogenic peptide–membrane interactions. In addition we project directions for future in silico studies and discuss shortcomings of current computational approaches.