Protein fragment clustering and canonical local shapes
Protein fragment clustering and canonical local shapes
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DOI：
10.1002/prot.10309
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发表时间：
2003-03-01
期刊：
影响因子：
--
通讯作者：
Subramaniam, S
中科院分区：
文献类型：
--
作者：
Hunter, CG;Subramaniam, S
提出了一种新的蛋白质片段形状聚类方法。质心（每个簇的平均碎片）形成一个基本的结构基元集。使用了一个包含156643个7残基片段的数据库，生成了8个不同分辨率的基集。粗基集包含数十个质心，提供有意义的局部形状，比传统的二级结构类别更详细。高分辨率基集包含数千个质心，可用于模拟较长片段的三级结构。基集生成符合预期精度的非训练集蛋白质。(C) 2003 Wiley-Liss, Inc。
A novel clustering method is used to cluster protein fragments by shape. The centroids (mean fragments from each cluster) form a basis set of structural motifs. A database of 156,643 seven-residue fragments is used, and eight different basis sets with varying levels of resolution are generated. Coarse basis sets contain tens of centroids and provide meaningful local shapes, which are more detailed than the traditional secondary structure categories. High-resolution basis sets contain thousands of centroids and can be used to model tertiary structure of longer segments. The basis sets generated fit nontraining set proteins with the expected accuracy. (C) 2003 Wiley-Liss, Inc.