3D shape-based techniques for protein classification

In this paper a 3D shape-based approach is presented for the efficient search, retrieval and classification of protein molecules. The method relies on the geometric 3D appearance of the proteins, which is produced from the corresponding PDB files. After proper positioning and alignment of the 3D structures, in terms of translation and scaling, the 3D structures are decomposed into planes. Then, the polar Fourier transform is applied to the planes creating a new domain of concentric spheres. In this new domain a set of functionals is applied so as to produce descriptor vectors, which are completely invariant to rotation and perfectly describe their 3D shape. Experimental results performed using a portion of the FSSP/DALI database shoed that the proposed method achieves more than 98% classification accuracy with less complexity and much simplicity and it is very fast comparing with the DALI method.