Identification of hot regions in protein-protein interactions based on SVM and DBSCAN

Abstract

Hot regions are the key factor to maintain stability and coordination of protein-protein interactions. In this paper, combining evolutionary information and support vector machine (SVM), we have developed an improved method for predicting binding sites in a protein sequence. The prediction models developed in this study have been trained and tested on binding protein chains and evaluated using fold cross validation technique. The performance of this SVM model further improved. Based on the predicted hot spots, DBSCAN method is used to predict the hot regions in protein-protein interactions. The experimental results demonstrate that the proposed method improves the predictive accuracy of hot regions and is more reliable compared with previous method.