Ensemble-Based Precision Refinement of All-Atom Nucleic Acid Force Fields Guided by NMR NOE Pair-Distance Measurements.

IF 5.5 1区 化学 Q2 CHEMISTRY, PHYSICAL
Hyeonjun Kim,Youngshang Pak
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引用次数: 0

Abstract

Accurately modeling nucleic acid structure and dynamics remains challenging for all-atom simulations, especially for noncanonical motifs such as small loops and G-quadruplexes. Despite these advances, current all-atom classical force fields often fail to reproduce ensembles consistent with high-resolution experimental data. We present a systematic refinement strategy for AMBER-based force fields that incorporates nuclear Overhauser effect distance data from NMR experiments within an ensemble-averaged optimization framework. By selectively tuning van der Waals interaction pairs, this approach markedly reduces simulation-experiment discrepancies, removes persistent artifacts, and generates free energy landscapes that better reflect experimental observations. We demonstrate broad applicability across diverse DNA and RNA systems including flexible loops and G-quadruplexes. Overall, this transferable strategy significantly improves structural accuracy and predictive power, enabling more reliable modeling of complex nucleic acid conformational ensembles.
基于核磁共振NOE对距离测量的全原子核酸力场集成精确细化。
对于全原子模拟来说,准确地建模核酸结构和动力学仍然是一个挑战,特别是对于小环和g -四联体等非规范基序。尽管取得了这些进展,但目前的全原子经典力场往往无法再现与高分辨率实验数据一致的系综。我们提出了一种基于amber力场的系统改进策略,该策略将来自核磁共振实验的核Overhauser效应距离数据纳入集成平均优化框架中。通过选择性地调整范德华相互作用对,这种方法显著减少了模拟与实验的差异,消除了持久的伪影,并产生了更好地反映实验观察的自由能景观。我们展示了广泛的适用性在不同的DNA和RNA系统,包括柔性环和g -四联体。总的来说,这种可转移策略显著提高了结构精度和预测能力,使复杂核酸构象集合的建模更加可靠。
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来源期刊
Journal of Chemical Theory and Computation
Journal of Chemical Theory and Computation 化学-物理:原子、分子和化学物理
CiteScore
9.90
自引率
16.40%
发文量
568
审稿时长
1 months
期刊介绍: The Journal of Chemical Theory and Computation invites new and original contributions with the understanding that, if accepted, they will not be published elsewhere. Papers reporting new theories, methodology, and/or important applications in quantum electronic structure, molecular dynamics, and statistical mechanics are appropriate for submission to this Journal. Specific topics include advances in or applications of ab initio quantum mechanics, density functional theory, design and properties of new materials, surface science, Monte Carlo simulations, solvation models, QM/MM calculations, biomolecular structure prediction, and molecular dynamics in the broadest sense including gas-phase dynamics, ab initio dynamics, biomolecular dynamics, and protein folding. The Journal does not consider papers that are straightforward applications of known methods including DFT and molecular dynamics. The Journal favors submissions that include advances in theory or methodology with applications to compelling problems.
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