Effects of All-Atom and Coarse-Grained Molecular Mechanics Force Fields on Amyloid Peptide Assembly: The Case of a Tau K18 Monomer.

IF 5.6 2区 化学 Q1 CHEMISTRY, MEDICINAL Journal of Chemical Information and Modeling Pub Date : 2024-11-23 DOI:10.1021/acs.jcim.4c01448
Xibing He, Viet Hoang Man, Jie Gao, Junmei Wang
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Abstract

To propose new mechanism-based therapeutics for Alzheimer's disease (AD), it is crucial to study the kinetics and oligomerization/aggregation mechanisms of the hallmark tau proteins, which have various isoforms and are intrinsically disordered. In this study, multiple all-atom (AA) and coarse-grained (CG) force fields (FFs) have been benchmarked on molecular dynamics (MD) simulations of K18 tau (M243-E372), which is a truncated form (130 residues) of full-length tau (441 residues). FF19SB is first excluded because the dynamics are too slow, and the conformations are too stable. All other benchmarked AAFFs (Charmm36m, FF14SB, Gromos54A7, and OPLS-AA) and CGFFs (Martini3 and Sirah2.0) exhibit a trend of shrinking K18 tau into compact structures with the radius of gyration (ROG) around 2.0 nm, which is much smaller than the experimental value of 3.8 nm, within 200 ns of AA-MD or 2000 ns of CG-MD. Gromos54A7, OPLS-AA, and Martini3 shrink much faster than the other FFs. To perform meaningful postanalysis of various properties, we propose a strategy of selecting snapshots with 2.5 < ROG < 4.5 nm, instead of using all sampled snapshots. The calculated chemical shifts of all C, CA, and CB atoms have very good and close root-mean-square error (RMSE) values, while Charmm36m and Sirah2.0 exhibit better chemical shifts of N than other FFs. Comparing the calculated distributions of the distance between the CA atoms of CYS291 and CYS322 with the results of the FRET experiment demonstrates that Charmm36m is a perfect match with the experiment while other FFs exhibit limitations. In summary, Charmm36m is recommended as the best AAFF, and Sirah2.0 is recommended as an excellent CGFF for simulating tau K18.

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全原子和粗粒度分子力学力场对淀粉样肽组装的影响:以 Tau K18 单体为例。
要针对阿尔茨海默病(AD)提出基于新机制的疗法,研究具有标志性特征的 tau 蛋白的动力学和寡聚/聚集机制至关重要。在本研究中,对 K18 tau(M243-E372)的分子动力学(MD)模拟进行了多个全原子(AA)和粗粒度(CG)力场(FF)基准测试,K18 tau 是全长 tau(441 个残基)的截短形式(130 个残基)。FF19SB 首先被排除在外,因为其动力学速度太慢,构象太稳定。所有其他基准 AAFFs(Charmm36m、FF14SB、Gromos54A7 和 OPLS-AA)和 CGFFs(Martini3 和 Sirah2.0)都显示出 K18 tau 在 AA-MD 的 200 ns 或 CG-MD 的 2000 ns 内收缩成紧凑结构的趋势,回旋半径(ROG)约为 2.0 nm,远小于实验值 3.8 nm。Gromos54A7、OPLS-AA 和 Martini3 的收缩速度比其他 FF 快得多。为了对各种特性进行有意义的后分析,我们提出了一种策略,即选择 2.5 < ROG < 4.5 nm 的快照,而不是使用所有采样快照。计算得出的所有 C、CA 和 CB 原子的化学位移都具有非常好且接近的均方根误差 (RMSE),而 Charmm36m 和 Sirah2.0 的 N 化学位移则优于其他 FF。将计算得出的 CYS291 和 CYS322 CA 原子间的距离分布与 FRET 实验结果进行比较,结果表明 Charmm36m 与实验结果完全吻合,而其他 FFs 则表现出局限性。总之,Charmm36m 被推荐为最佳 AAFF,Sirah2.0 被推荐为模拟 tau K18 的优秀 CGFF。
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来源期刊
CiteScore
9.80
自引率
10.70%
发文量
529
审稿时长
1.4 months
期刊介绍: The Journal of Chemical Information and Modeling publishes papers reporting new methodology and/or important applications in the fields of chemical informatics and molecular modeling. Specific topics include the representation and computer-based searching of chemical databases, molecular modeling, computer-aided molecular design of new materials, catalysts, or ligands, development of new computational methods or efficient algorithms for chemical software, and biopharmaceutical chemistry including analyses of biological activity and other issues related to drug discovery. Astute chemists, computer scientists, and information specialists look to this monthly’s insightful research studies, programming innovations, and software reviews to keep current with advances in this integral, multidisciplinary field. As a subscriber you’ll stay abreast of database search systems, use of graph theory in chemical problems, substructure search systems, pattern recognition and clustering, analysis of chemical and physical data, molecular modeling, graphics and natural language interfaces, bibliometric and citation analysis, and synthesis design and reactions databases.
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Issue Editorial Masthead Issue Publication Information Effects of All-Atom and Coarse-Grained Molecular Mechanics Force Fields on Amyloid Peptide Assembly: The Case of a Tau K18 Monomer. Effect of Water Networks On Ligand Binding: Computational Predictions vs Experiments. Pairing a Global Optimization Algorithm with EXAFS to Characterize Lanthanide Structure in Solution.
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