A brief history of amyloid aggregation simulations

IF 16.8 2区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY
Hebah Fatafta, Mohammed Khaled, Batuhan Kav, Olujide O. Olubiyi, Birgit Strodel
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Abstract

Amyloid proteins are characterized by their tendency to aggregate into amyloid fibrils, which are often associated with devastating diseases. Aggregation pathways typically involve unfolding or misfolding of monomeric proteins and formation of transient oligomers and protofibrils before the final aggregation product is formed. The conformational dynamics and polymorphic and volatile nature of these aggregation intermediates make their characterization by experimental techniques alone insufficient and also require computational approaches. Over the past 25 years, the size of simulated amyloid aggregation systems and the length of these simulations have increased significantly. These advances are discussed here. The review includes simulation approaches that model the aggregating peptides or proteins at both the all-atom and coarse-grained levels, use molecular dynamics simulations or Monte Carlo sampling to simulate the conformational changes, and present results for various amyloid peptides and proteins ranging from Lys-Phe-Phe-Glu (KFFE) as the smallest system to $$ \mathrm{A}\upbeta $$ as an intermediate-sized peptide to α-synuclein. The presentation of the history of amyloid aggregation simulations concludes with a discussion of where the future of these simulations may lie.

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Abstract Image

淀粉样蛋白聚集模拟简史
淀粉样蛋白的特点是容易聚集成淀粉样纤维,而淀粉样纤维往往与破坏性疾病相关。在形成最终聚集产物之前,聚集途径通常包括单体蛋白的解折或错误折叠以及瞬时低聚物和原纤维的形成。由于这些聚集中间产物的构象动态、多态性和易变性,仅靠实验技术不足以描述其特征,还需要计算方法。在过去的 25 年中,模拟淀粉样蛋白聚集系统的规模和这些模拟的长度都显著增加。本文将讨论这些进展。综述包括在全原子和粗粒度水平上对聚集肽或蛋白质进行建模的模拟方法,使用分子动力学模拟或蒙特卡洛采样模拟构象变化,并介绍了各种淀粉样肽和蛋白质的结果,从最小系统的Lys-Phe-Phe-Glu (KFFE)到中等大小肽Aβ $\mathrm{A}\upbeta $$,再到α-突触核蛋白。本文介绍了淀粉样蛋白聚集模拟的历史,最后讨论了这些模拟的未来发展方向:
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Wiley Interdisciplinary Reviews: Computational Molecular Science
Wiley Interdisciplinary Reviews: Computational Molecular Science CHEMISTRY, MULTIDISCIPLINARY-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
28.90
自引率
1.80%
发文量
52
审稿时长
6-12 weeks
期刊介绍: Computational molecular sciences harness the power of rigorous chemical and physical theories, employing computer-based modeling, specialized hardware, software development, algorithm design, and database management to explore and illuminate every facet of molecular sciences. These interdisciplinary approaches form a bridge between chemistry, biology, and materials sciences, establishing connections with adjacent application-driven fields in both chemistry and biology. WIREs Computational Molecular Science stands as a platform to comprehensively review and spotlight research from these dynamic and interconnected fields.
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