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Three-Dimensional Shape-Structure Comparison Method for Protein Classification

机译：蛋白质分类的三维形状结构比较方法

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摘要

In this paper, a 3D shape-based approach is presented for the efficient search, retrieval, and classification of protein molecules. The method relies primarily on the geometric 3D structure of the proteins, which is produced from the corresponding PDB files and secondarily on their primary and secondary structure. After proper positioning of the 3D structures, in terms of translation and scaling, the Spherical Trace Transform is applied to them so as to produce geometry-based descriptor vectors, which are completely rotation invariant and perfectly describe their 3D shape. Additionally, characteristic attributes of the primary and secondary structure of the protein molecules are extracted, forming attribute-based descriptor vectors. The descriptor vectors are weighted and an integrated descriptor vector is produced. Three classification methods are tested. A part of the FSSP/DALI database, which provides a structural classification of the proteins, is used as the ground truth in order to evaluate the classification accuracy of the proposed method. The experimental results show that the proposed method achieves more than 99 percent classification accuracy while remaining much simpler and faster than the DALI method.
机译：在本文中，提出了一种基于3D形状的方法，可以有效地搜索，检索和分类蛋白质分子。该方法主要依靠蛋白质的几何3D结构，该结构是从相应的PDB文件生成的，其次是它们的一级和二级结构。在正确定位3D结构之后，就平移和缩放而言，将球面轨迹变换应用于它们，以生成基于几何的描述符向量，该向量完全旋转不变并完美地描述了其3D形状。另外，提取蛋白质分子的一级和二级结构的特征属性，形成基于属性的描述符向量。对描述符向量进行加权，并生成一个集成的描述符向量。测试了三种分类方法。 FSSP / DALI数据库的一部分提供了蛋白质的结构分类，被用作依据，以评估所提出方法的分类准确性。实验结果表明，与DALI方法相比，该方法可以实现99％以上的分类精度，同时又保持了简单，快速的分类效果。

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