Laboratory of Structural Biology, National Institute for Arthritis, Musculoskeletal and Skin Diseases, National Institutes of Health, Bethesda, MD 20892, USA.
J Struct Biol. 2013 Nov;184(2):226-36. doi: 10.1016/j.jsb.2013.08.002. Epub 2013 Aug 14.
The resolution of density maps from single particle analysis is usually measured in terms of the highest spatial frequency to which consistent information has been obtained. This calculation represents an average over the entire reconstructed volume. In practice, however, substantial local variations in resolution may occur, either from intrinsic properties of the specimen or for technical reasons such as a non-isotropic distribution of viewing orientations. To address this issue, we propose the use of a space-frequency representation, the short-space Fourier transform, to assess the quality of a density map, voxel-by-voxel, i.e. by local resolution mapping. In this approach, the experimental volume is divided into small subvolumes and the resolution determined for each of them. It is illustrated in applications both to model data and to experimental density maps. Regions with lower-than-average resolution may be mobile components or ones with incomplete occupancy or result from multiple conformational states. To improve the interpretability of reconstructions, we propose an adaptive filtering approach that reconciles the resolution to which individual features are calculated with the results of the local resolution map.
从单颗粒分析得到的密度图的分辨率通常用可以获得一致信息的最高空间频率来衡量。这个计算是在整个重构体积上的平均值。然而,实际上,分辨率可能会有很大的局部变化,这可能是由于标本的固有特性,也可能是由于观察方向的非各向同性分布等技术原因。为了解决这个问题,我们提出使用空间频率表示法,即短空间傅里叶变换,逐体素评估密度图的质量,即通过局部分辨率映射。在这种方法中,实验体积被分成小的子体积,并确定它们中的每一个的分辨率。该方法在模型数据和实验密度图的应用中都得到了说明。分辨率低于平均值的区域可能是移动组件或不完全占据的区域,或者是由多个构象状态引起的。为了提高重构的可解释性,我们提出了一种自适应滤波方法,该方法将个体特征的计算分辨率与局部分辨率图的结果相协调。