RNA的弹性网络模型：分子动力学和SHAPE实验的比较评估
Elastic network models for RNA: a comparative assessment with molecular dynamics and SHAPE experiments
摘要：
弹性网络模型（ENM）是基于蛋白质天然结构的知识来表征蛋白质集体内部动力学的有价值和有效的工具。越来越多的证据表明，RNA的生物功能往往与其固有的内部运动有关，这就提出了ENM方法是否可以成功地扩展到这类生物分子的问题。这里通过考虑应用于一组代表性RNA的各种复杂性不断增加的弹性网络家族来解决这个问题。通过与广泛的分子动力学模拟和SHAPE实验的比较，严格验证了替代ENM预测的波动。我们发现，无论是全原子或三珠每核苷酸表示（糖-碱基-磷酸盐）的模拟和实验数据系统最好地再现，后者可以说提供了准确性和计算复杂性的最佳平衡。
英文摘要：
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.
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