Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States.
Department of Neuroscience, The Ohio State University Wexner Medical Center, Columbus, Ohio 43210, United States.
J Chem Theory Comput. 2021 Oct 12;17(10):6458-6471. doi: 10.1021/acs.jctc.1c00028. Epub 2021 Sep 7.
Molecular dynamics (MD) simulations play a vital role in revealing the mechanism of amyloid aggregation that is crucial to the therapeutic agent development for Alzheimer's Disease. However, the accuracy of MD simulation results strongly depends on the force field employed. In our previous benchmark for 17 all-atom force fields on modeling of amyloid aggregation using the Aβ dimer, we showed that AMBER14SB and CHARMM36m are suitable force fields for amyloid aggregation simulation, while GROMOS54a7 and OPLSAA are not good for the task. In this work, we continue assessing the applicability of atomistic force fields on amyloid aggregation using the VQIVYK (PHF6) peptide which is essential for tau-protein aggregation. Although, both Aβ and PHF6 peptides formed fibrils , the PHF6 fibrils are parallel β-sheets, while the Aβ fibrils are antiparallel β-sheets. We performed an all-atom large-scale MD simulation in explicit water on the PHF6 dimer and octa-peptides systems using five mainstream force fields, including AMBER99SB-disp, AMBER14SB, CHARMM36m, GROMOS54a7, and OPLSAA. The accumulated simulation time is 0.2 ms. Our result showed that the β-sheet structures of PHF6 peptides sampled by AMBER99SB-disp, AMBER14SB, GROMOS54a7, and OPLSAA are in favor of the antiparallel β-sheets, while the dominant type of β-sheet structures is parallel β-sheet by using CHARMM36m. Among the five force fields, CHARMM36m provides the strongest CH-π interaction that was observed in an NMR study. The comparison between our results and experimental observation indicates that CHARMM36m achieved the best performance on modeling the aggregation of PHF6 peptides. In summary, CHARMM36m is currently the most suitable force field for studying the aggregation of both amyloid-β and Tau through MD simulations.
分子动力学（MD）模拟在揭示淀粉样蛋白聚集的机制方面发挥着至关重要的作用，而这对于阿尔茨海默病治疗药物的开发至关重要。然而，MD 模拟结果的准确性在很大程度上取决于所使用的力场。在我们之前使用 Aβ二聚体对淀粉样蛋白聚集进行建模的 17 种全原子力场的基准测试中，我们表明 AMBER14SB 和 CHARMM36m 是适合淀粉样蛋白聚集模拟的力场，而 GROMOS54a7 和 OPLSAA 则不适合该任务。在这项工作中，我们继续使用对于 tau 蛋白聚集至关重要的 VQIVYK（PHF6）肽评估原子力场在淀粉样蛋白聚集中的适用性。尽管 Aβ 和 PHF6 肽都形成了纤维，但 PHF6 纤维是平行的β-折叠，而 Aβ 纤维是反平行的β-折叠。我们使用五种主流力场（包括 AMBER99SB-disp、AMBER14SB、CHARMM36m、GROMOS54a7 和 OPLSAA）在明水环境中对 PHF6 二聚体和八肽系统进行了全原子大规模 MD 模拟。累计模拟时间为 0.2 毫秒。我们的结果表明，AMBER99SB-disp、AMBER14SB、GROMOS54a7 和 OPLSAA 采样的 PHF6 肽的β-折叠结构有利于反平行β-折叠，而 CHARMM36m 的主导β-折叠结构类型是平行β-折叠。在这五种力场中，CHARMM36m 提供了在 NMR 研究中观察到的最强的 CH-π 相互作用。我们的结果与实验观察结果的比较表明，CHARMM36m 在模拟 PHF6 肽的聚集方面表现最佳。总之，CHARMM36m 是目前最适合通过 MD 模拟研究淀粉样蛋白-β 和 Tau 聚集的力场。
