Faculty of Materials Science and Technology, University of Science-VNU HCM, 227 Nguyen Van Cu Street, District 5, Ho Chi Minh City 700000, Vietnam.
Institute for Computational Science and Technology, SBI Building, Quang Trung Software City, Tan Chanh Hiep Ward, District 12, Ho Chi Minh City, Viet Nam.
J Chem Phys. 2022 Aug 7;157(5):055101. doi: 10.1063/5.0088689.
The formation of the fibrillar structure of amyloid proteins/peptides is believed to be associated with neurodegenerative diseases, such as Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis. Since the rate of aggregation can influence neurotoxicity, finding the key factors that control this rate is of paramount importance. It was recently found that the rate of protein aggregation is related to the mechanical stability of the fibrillar structure such that the higher the mechanical stability, the faster the fibril is formed. However, this conclusion was supported by a limited dataset. In this work, we expand the previous study to a larger dataset, including the wild type of Aβ42 peptide and its 20 mutants, the aggregation rate of which was measured experimentally. By using all-atom steered molecular dynamics (SMD) simulations, we can assess the mechanical stability of the fibril structure, which is characterized by the rupture force, pulling work, and unbinding free energy barrier. Our result confirms that mechanical stability is indeed related to the aggregation rate. Since the estimation of the aggregation rate using all-atom simulations is almost forbidden by the current computational capabilities, our result is useful for predicting it based on information obtained from fast SMD simulations for fibrils.
纤维状结构的淀粉样蛋白/肽的形成被认为与神经退行性疾病有关，如阿尔茨海默病、帕金森病和肌萎缩侧索硬化症。由于聚集速度会影响神经毒性，因此找到控制这一速度的关键因素至关重要。最近发现，蛋白质聚集的速度与纤维状结构的机械稳定性有关，即机械稳定性越高，纤维形成的速度就越快。然而，这一结论仅基于有限的数据集。在这项工作中，我们将之前的研究扩展到了更大的数据集，包括 Aβ42 肽的野生型及其 20 个突变体，这些突变体的聚集速度已经通过实验进行了测量。通过使用全原子定向分子动力学（SMD）模拟，我们可以评估纤维状结构的机械稳定性，这一特性由断裂力、拉伸功和非结合自由能势垒来表征。我们的结果证实，机械稳定性确实与聚集速度有关。由于全原子模拟对聚集速度的估计几乎被当前的计算能力所禁止，因此我们的结果对于基于快速 SMD 模拟获得的纤维信息来预测聚集速度是有用的。
