Esquivel-Rodríguez Juan, Xiong Yi, Han Xusi, Guang Shuomeng, Christoffer Charles, Kihara Daisuke
Department of Computer Science, Purdue University, West Lafayette, IN, 47907, USA.
Department of Biological Sciences, Purdue University, West Lafayette, IN, 47907, USA.
BMC Bioinformatics. 2015 May 30;16:181. doi: 10.1186/s12859-015-0580-6.
The Electron Microscopy DataBank (EMDB) is growing rapidly, accumulating biological structural data obtained mainly by electron microscopy and tomography, which are emerging techniques for determining large biomolecular complex and subcellular structures. Together with the Protein Data Bank (PDB), EMDB is becoming a fundamental resource of the tertiary structures of biological macromolecules. To take full advantage of this indispensable resource, the ability to search the database by structural similarity is essential. However, unlike high-resolution structures stored in PDB, methods for comparing low-resolution electron microscopy (EM) density maps in EMDB are not well established.
We developed a computational method for efficiently searching low-resolution EM maps. The method uses a compact fingerprint representation of EM maps based on the 3D Zernike descriptor, which is derived from a mathematical series expansion for EM maps that are considered as 3D functions. The method is implemented in a web server named EM-SURFER, which allows users to search against the entire EMDB in real-time. EM-SURFER compares the global shapes of EM maps. Examples of search results from different types of query structures are discussed.
We developed EM-SURFER, which retrieves structurally relevant matches for query EM maps from EMDB within seconds. The unique capability of EM-SURFER to detect 3D shape similarity of low-resolution EM maps should prove invaluable in structural biology.
电子显微镜数据库（EMDB）正在迅速增长，积累了主要通过电子显微镜和断层扫描获得的生物结构数据，这些都是用于确定大型生物分子复合物和亚细胞结构的新兴技术。与蛋白质数据库（PDB）一起，EMDB正成为生物大分子三级结构的重要资源。为了充分利用这一不可或缺的资源，通过结构相似性搜索数据库的能力至关重要。然而，与存储在PDB中的高分辨率结构不同，EMDB中比较低分辨率电子显微镜（EM）密度图的方法尚未完善。
我们开发了一种用于高效搜索低分辨率EM图的计算方法。该方法基于3D泽尼克描述符使用EM图的紧凑指纹表示，该描述符源自将EM图视为3D函数的数学级数展开。该方法在名为EM-SURFER的网络服务器中实现，允许用户实时搜索整个EMDB。EM-SURFER比较EM图的全局形状。讨论了来自不同类型查询结构的搜索结果示例。
我们开发了EM-SURFER，它能在几秒钟内从EMDB中检索出与查询EM图结构相关的匹配项。EM-SURFER检测低分辨率EM图3D形状相似性的独特能力在结构生物学中应具有极高价值。
