An Effective Algorithm Based on Curve Fitting for Measuring Protein Structure Similarity

It is almost believed that the function of one protein is determined by its structure. The more similar two protein structures are, the more similar their functions are. The distance RMSD (Root Mean Square Deviation) is a popular method used by most researchers to measure the distance (or similarity) between two protein structures, usually one is the predicted structure and the other is its real structure. In this paper, we propose a new algorithm to compare two protein structures, which is the combination of sequence alignment and the B-spline curve fitting in the space. To test and verify our method, we randomly choose some families in the CATH database and try to identify them. Experimental results show that our method outperforms the distance RMSD method. Furthermore, we apply the SVM (Support Vector Machine) tool to help us obtain the better classifications.