Searching for three-dimensional secondary structural patterns in proteins with ProSMoS
Searching for three-dimensional secondary structural patterns in proteins with ProSMoS
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DOI：
10.1093/bioinformatics/btm121
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发表时间：
2007-06-01
期刊：
影响因子：
5.8
通讯作者：
Grishin, Nick V.
中科院分区：
文献类型：
--
作者：
Shi, Shuoyong;Zhong, Yi;Grishin, Nick V.
动机：通过空间结构的比较，蛋白质之间的许多进化上遥远但功能上有意义的联系被揭示出来。大多数评估结构相似性的程序将两个蛋白质相互比较，并找到它们之间的共同区域。结构分类专家会寻找一个特定的结构基序。程序基于笛卡尔坐标或残基间接触的叠加或接近程度的相似性得分。专家们更关注主链的总体朝向和次级结构要素的相互空间安排。需要一种计算工具来发现具有相同二级结构、拓扑连接和空间结构的蛋白质，而不考虑三维坐标的细微差异。结果：我们开发了prosmos -一个模拟专家的蛋白质结构Motif搜索程序。从空间结构开始，该方案使用了先前描述的次要结构元素。在搜索之前或搜索过程中构建元素（平行或反平行）之间相互作用的元矩阵，考虑连接的手性（左或右）和其他特征（例如元素长度和氢键）。所有的结构都被简化为包含足够信息来定义蛋白质折叠的元矩阵，但这个定义仍然是非常一般的，并且在3D坐标上的偏差是可以容忍的。用户为感兴趣的结构基序提供元矩阵，ProSMoS在蛋白质数据库（PDB）中查找与元矩阵匹配的所有蛋白质。将ProSMoS的性能与其他程序进行了比较，并在beta-Grasp motif上进行了说明。简要分析了所有含有β - grip的蛋白质。
Motivation: Many evolutionarily distant, but functionally meaningful links between proteins come to light through comparison of spatial structures. Most programs that assess structural similarity compare two proteins to each other and find regions in common between them. Structural classification experts look for a particular structural motif instead. Programs base similarity scores on superposition or closeness of either Cartesian coordinates or inter-residue contacts. Experts pay more attention to the general orientation of the main chain and mutual spatial arrangement of secondary structural elements. There is a need for a computational tool to find proteins with the same secondary structures, topological connections and spatial architecture, regardless of subtle differences in 3D coordinates.Results: We developed ProSMoS-a Protein Structure Motif Search program that emulates an expert. Starting from a spatial structure, the program uses previously delineated secondary structural elements. A meta-matrix of interactions between the elements (parallel or antiparallel) minding handedness of connections (left or right) and other features (e.g. element lengths and hydrogen bonds) is constructed prior to or during the searches. All structures are reduced to such meta-matrices that contain just enough information to define a protein fold, but this definition remains very general and deviations in 3D coordinates are tolerated. User supplies a metamatrix for a structural motif of interest, and ProSMoS finds all proteins in the protein data bank (PDB) that match the meta-matrix. ProSMoS performance is compared to other programs and is illustrated on a beta-Grasp motif. A brief analysis of all beta-Grasp-containing proteins is presented.