Recent advances in the field of protein structure determination using liquid-state NMR enable the elucidation of multi-state protein conformations that can provide insight into correlated and non-correlated protein dynamics at atomic resolution. So far, NMR-derived multi-state structures were typically evaluated by means of visual inspection of structure superpositions, target function values that quantify the violation of experimented restraints and root-mean-square deviations that quantify similarity between conformers. As an alternative or complementary approach, we present here the use of a recently introduced structural correlation measure, PDBcor, that quantifies the clustering of protein states as an additional measure for multi-state protein structure analysis. It can be used for various assays including the validation of experimental distance restraints, optimization of the number of protein states, estimation of protein state populations, identification of key distance restraints, NOE network analysis and semiquantitative analysis of the protein correlation network. We present applications for the final quality analysis stages of typical multi-state protein structure calculations.

使用液态 NMR 确定蛋白质结构领域的最新进展能够阐明多态蛋白质构象，从而可以深入了解原子分辨率下的相关和非相关蛋白质动力学。到目前为止，NMR 衍生的多态结构通常通过结构叠加的目视检查、量化实验约束违反的目标函数值和量化构象异构体之间相似性的均方根偏差来评估。作为一种替代或补充方法，我们在此展示了使用最近引入的结构相关性度量 PDBcor，该度量将蛋白质状态的聚类量化为多状态蛋白质结构分析的附加度量。它可用于各种测定，包括实验距离约束的验证、蛋白质状态数量的优化、蛋​​白质状态种群的估计、关键距离约束的识别、NOE 网络分析和蛋白质相关网络的半定​​量分析。我们介绍了典型多态蛋白质结构计算的最终质量分析阶段的应用。