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Motional timescale predictions by molecular dynamics simulations: Case study using proline and hydroxyproline sidechain dynamics

机译:通过分子动力学模拟预测运动时标:使用脯氨酸和羟脯氨酸侧链动力学的案例研究

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摘要

We propose a new approach for force field optimizations which aims at reproducing dynamics characteristics using biomolecular MD simulations, in addition to improved prediction of motionally averaged structural properties available from experiment. As the source of experimental data for dynamics fittings, we use 13C NMR spin-lattice relaxation times T1 of backbone and sidechain carbons, which allow to determine correlation times of both overall molecular and intramolecular motions. For structural fittings, we use motionally averaged experimental values of NMR J couplings. The proline residue and its derivative 4-hydroxyproline with relatively simple cyclic structure and sidechain dynamics were chosen for the assessment of the new approach in this work. Initially, grid search and simplexed MD simulations identified large number of parameter sets which fit equally well experimental J couplings. Using the Arrhenius-type relationship between the force constant and the correlation time, the available MD data for a series of parameter sets were analyzed to predict the value of the force constant that best reproduces experimental timescale of the sidechain dynamics. Verification of the new force-field (termed as AMBER99SB-ILDNP) against NMR J couplings and correlation times showed consistent and significant improvements compared to the original force field in reproducing both structural and dynamics properties. The results suggest that matching experimental timescales of motions together with motionally averaged characteristics is the valid approach for force field parameter optimization. Such a comprehensive approach is not restricted to cyclic residues and can be extended to other amino acid residues, as well as to the backbone. Proteins 2014; 82:195–215. © 2013 Wiley Periodicals, Inc.
机译:我们提出了一种用于力场优化的新方法,该方法旨在利用生物分子MD模拟来重现动力学特性,此外还可以改进实验中对运动平均结构特性的预测。作为动力学拟合实验数据的来源,我们使用主链和侧链碳的 13 C NMR自旋晶格弛豫时间T1,这可以确定总体分子运动和分子内运动的相关时间。对于结构拟合,我们使用NMR J耦合的运动平均实验值。选择脯氨酸残基及其具有相对简单的环状结构和侧链动力学的4-羟基脯氨酸来评估这项工作中的新方法。最初,网格搜索和简单的MD模拟确定了大量参数集,这些参数集同样适合实验J耦合。使用力常数和相关时间之间的Arrhenius型关系,分析了一系列参数集的可用MD数据,以预测力常数的值,该值最能重现侧链动力学的实验时间尺度。对新的力场(称为AMBER99SB-ILDNP)针对NMR J耦合和相关时间的验证显示,与原始力场相比,在再现结构和动力学特性方面均具有一致且显着的改进。结果表明,将运动的实验时间尺度与运动平均特征相匹配是力场参数优化的有效方法。这种全面的方法不限于环状残基,并且可以扩展到其他氨基酸残基以及主链。蛋白质2014; 82:195–215。 ©2013 Wiley Periodicals,Inc.

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