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Elastic network models for RNA: a comparative assessment with molecular dynamics and SHAPE experiments

机译:RNA的弹性网络模型:分子动力学和SHAPE实验的比较评估

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Elastic network models (ENMs) are valuable and efficient tools for characterizing the collective internal dynamics of proteins based on the knowledge of their native structures. The increasing evidence that the biological functionality of RNAs is often linked to their innate internal motions poses the question of whether ENM approaches can be successfully extended to this class of biomolecules. This issue is tackled here by considering various families of elastic networks of increasing complexity applied to a representative set of RNAs. The fluctuations predicted by the alternative ENMs are stringently validated by comparison against extensive molecular dynamics simulations and SHAPE experiments. We find that simulations and experimental data are systematically best reproduced by either an all-atom or a three-beads-per-nucleotide representation (sugar-base-phosphate), with the latter arguably providing the best balance of accuracy and computational complexity.
机译:弹性网络模型(ENM)是有价值的有效工具,可基于对天然结构的了解来表征蛋白质的集体内部动力学。越来越多的证据表明,RNA的生物学功能通常与其固有的内部运动有关,这提出了一个问题,即ENM方法是否可以成功地扩展到此类生物分子。通过考虑将各种复杂性不断增加的弹性网络应用于代表性的RNA集来解决此问题。通过与广泛的分子动力学模拟和SHAPE实验进行比较,可以严格验证替代ENM预测的波动。我们发现,通过全原子或每个核苷酸三个珠子(糖基磷酸酯)表示,可以最好地重现模拟和实验数据,后者可以在准确性和计算复杂性之间取得最佳平衡。

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