Similarity Comparison of 3D Protein Structure Based on Riemannian Manifold

As the representative technology of protein spatial structure exploration, NMR technology provides an unprecedented opportunity for modern life science research. But subsequent large data analysis has become a major problem. It is an important means to study protein structure and functional relationship by known information proteins’ three-dimensional structures to predict the unknown spatial structure of proteins. A method for similarity comparison of 3D protein structures based on Riemannian manifold theory is proposed in this paper. By constructing Cα frames and extracting geometric feature of protein, 3D coordinates of proteins are converted into one dimension sequences with rotation and translation invariance. The Riemann distance is used as the three-dimensional structure similarity degree index. Spatial transformation on protein structure is not needed in this method, which avoiding errors when matching two proteins in the traditional method for registration by the least squares fitting. This method is independent of sequence information completely. It has realistic significance for proteins which do not have a similarity between sequences. Three experiments are designed according to 3 sets of data: proteins of different similarity, ten pairs whose protein structures are more difficult to identify proposed by Fischer, 700 proteins in the HOMSTRAD database. Compared with the traditional method, the experiment results show that the matching accuracy of this method has been greatly enhanced.