A global map of the protein shape universe
A global map of the protein shape universe
复制标题
DOI：
10.1371/journal.pcbi.1006969
复制
发表时间：
2019-04-01
影响因子：
4.3
通讯作者：
Kihara, Daisuke
中科院分区：
文献类型：
--
作者：
Han, Xusi;Sit, Atilla;Kihara, Daisuke
蛋白质几乎参与了活细胞的所有功能，蛋白质的功能是通过其三级结构来实现的。获得蛋白质结构的多样性和分布的全局视角为我们理解蛋白质结构的构建原理奠定了基础。鉴于电子断层扫描和低温电子显微镜的低分辨率结构数据的快速积累，我们在这里绘制和分类蛋白质的三维（3D）表面形状到一个相似空间。蛋白质的表面形状用三维Zernike描述符表示，这是一种基于数学矩的不变量，之前已被证明对生物分子结构相似性搜索有效。除了蛋白质的单链外，我们还分析了蛋白质复合物所占据的形状空间。从映射中，我们对形状、主链褶皱和复杂地层之间的关系获得了各种新的见解。从形状映射中获得的独特视角为理解蛋白质的设计原理、功能和进化开辟了新的途径。蛋白质是参与几乎所有细胞过程的主要分子。在这项工作中，我们提出了一种新的蛋白质形状映射，它代表了蛋白质及其组装的3D形状的多样性和相似性。这种映射为蛋白质形状提供了各种新的见解，包括蛋白质3D形状的决定因素，这增强了我们对蛋白质形状设计原则的理解。该图谱也将为人工蛋白的设计提供宝贵的资源，并为低温电子显微镜和层析成像的中低分辨率蛋白质结构图像的分类提供参考。
Proteins are involved in almost all functions in a living cell, and functions of proteins are realized by their tertiary structures. Obtaining a global perspective of the variety and distribution of protein structures lays a foundation for our understanding of the building principle of protein structures. In light of the rapid accumulation of low-resolution structure data from electron tomography and cryo-electron microscopy, here we map and classify three-dimensional (3D) surface shapes of proteins into a similarity space. Surface shapes of proteins were represented with 3D Zernike descriptors, mathematical moment-based invariants, which have previously been demonstrated effective for biomolecular structure similarity search. In addition to single chains of proteins, we have also analyzed the shape space occupied by protein complexes. From the mapping, we have obtained various new insights into the relationship between shapes, main-chain folds, and complex formation. The unique view obtained from shape mapping opens up new ways to understand design principles, functions, and evolution of proteins.Author summary Proteins are the major molecules involved in almost all cellular processes. In this work, we present a novel mapping of protein shapes that represents the variety and the similarities of 3D shapes of proteins and their assemblies. This mapping provides various novel insights into protein shapes including determinant factors of protein 3D shapes, which enhance our understanding of the design principles of protein shapes. The mapping will also be a valuable resource for artificial protein design as well as references for classifying medium- to low-resolution protein structure images of determined by cryo-electron microscopy and tomography.