With the explosion of normal mode analyses (NMAs) based on elastic network models (ENMs) in the last decade, and the proven precision of MD simulations for visualizing interactions at atomic scale, many hybrid methods have been proposed in recent years. These aim at exploiting the best of both worlds: the atomic precision of MD that often fall short of exploring time and length scales of biological interest, and the capability of ENM-NMA to predict the cooperative and often functional rearrangements of large structures and assemblies, albeit at low resolution. We present an overview of recent progress in the field with examples of successful applications highlighting the utility of such hybrid methods and pointing to emerging future directions guided by advances in experimental characterization of biomolecular systems structure and dynamics.

中文翻译：

---

获得多尺度事件的视野：在混合方法中利用网络模型和正常模式。

随着过去十年基于弹性网络模型 (ENM) 的正态模式分析 (NMA) 的爆炸式增长，以及在原子尺度上可视化相互作用的 MD 模拟已被证明的精度，近年来已经提出了许多混合方法。这些旨在利用两全其美：MD 的原子精度通常无法探索生物兴趣的时间和长度尺度，以及 ENM-NMA 预测大型结构和组件的协作和功能重排的能力，虽然分辨率很低。我们概述了该领域的最新进展，并通过成功应用的例子强调了这种混合方法的实用性，并指出了在生物分子系统结构和动力学的实验表征方面的进展指导下的新兴未来方向。