Daras Petros, Zarpalas Dimitrios, Axenopoulos Apostolos, Tzovaras Dimitrios, Strintzis Michael Gerassimos
Informatics and Telematics Institute (ITI), 1st Km Thermi-Panorama Road, Thermi-Thessaloniki, PO Box 361, Greece.
IEEE/ACM Trans Comput Biol Bioinform. 2006 Jul-Sep;3(3):193-207. doi: 10.1109/TCBB.2006.43.
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.
本文提出了一种基于三维形状的方法，用于蛋白质分子的高效搜索、检索和分类。该方法主要依赖于从相应的蛋白质数据银行（PDB）文件生成的蛋白质几何三维结构，其次依赖于它们的一级和二级结构。在对三维结构进行适当的平移和缩放定位后，对其应用球面跟踪变换，以生成基于几何的描述符向量，这些向量完全旋转不变，能够完美地描述其三维形状。此外，提取蛋白质分子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，生成一个综合描述符向量。测试了三种分类方法。蛋白质结构分类数据库FSSP/DALI的一部分用作基准事实，以评估所提方法的分类准确性。实验结果表明，所提方法实现了超过99%的分类准确率，同时比DALI方法更简单、更快。
