Allison Jane R
Centre for Theoretical Chemistry and Physics, Institute of Natural Sciences, Massey University Albany, Albany Highway, Auckland, 0632, New Zealand.
Biophys Rev. 2012 Sep;4(3):189-203. doi: 10.1007/s12551-012-0087-6. Epub 2012 Sep 1.
The sophistication of the force fields, algorithms and hardware used for molecular dynamics (MD) simulations of proteins is continuously increasing. No matter how advanced the methodology, however, it is essential to evaluate the appropriateness of the structures sampled in a simulation by comparison with quantitative experimental data. Solution nuclear magnetic resonance (NMR) data are particularly useful for checking the quality of protein simulations, as they provide both structural and dynamic information on a variety of temporal and spatial scales. Here, various features and implications of using NMR data to validate and bias MD simulations are outlined, including an overview of the different types of NMR data that report directly on structural properties and of relevant simulation techniques. The focus throughout is on how to properly account for conformational averaging, particularly within the context of the assumptions inherent in the relationships that link NMR data to structural properties.
用于蛋白质分子动力学(MD)模拟的力场、算法和硬件的复杂性在不断提高。然而,无论方法多么先进,通过与定量实验数据进行比较来评估模拟中采样结构的适用性都是至关重要的。溶液核磁共振(NMR)数据对于检查蛋白质模拟的质量特别有用,因为它们在各种时间和空间尺度上提供了结构和动力学信息。本文概述了使用NMR数据验证和偏向MD模拟的各种特征和影响,包括直接报告结构性质的不同类型NMR数据和相关模拟技术的概述。始终关注的是如何恰当地考虑构象平均,特别是在将NMR数据与结构性质联系起来的关系中固有的假设背景下。