Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 3501 Fifth Ave, Suite 3064 BST3, Pittsburgh, PA 15260, USA.
Laboratory of Bioinformatics and Computational Biology, Federal University of ABC, Santo André, SP, Brazil.
Curr Opin Struct Biol. 2020 Oct;64:34-41. doi: 10.1016/j.sbi.2020.05.013. Epub 2020 Jul 1.
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.
在过去十年中，基于弹性网络模型（ENM）的正常模式分析（NMA）的爆炸式增长，以及 MD 模拟在原子尺度上可视化相互作用的精确性已得到证实，近年来已经提出了许多混合方法。这些方法旨在充分利用两者的优势：MD 的原子精度通常无法探索生物感兴趣的时间和长度尺度，而 ENM-NMA 能够预测大结构和组装体的协同和功能重排，尽管分辨率较低。我们通过成功应用的示例展示了该领域的最新进展，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取得的进展所指导的新兴未来方向。
