Protein-Protein Interface Residue Prediction with SVM Using Evolutionary Profiles and Accessible Surface Areas

Knowledge of protein-protein interaction sites is vital to determine proteins' function and involvement in different pathways. Though a wide variety of methods has been proposed over the recent years in order to predict protein-protein interface residues, mainly based on single amino acid sequence inputs, each has its own drawbacks and limitations. We propose to use support vector machines (SVM) to predict protein-protein interface residues by using the information derived from the position-specific scoring matrices (PSSMs) generated from PSI-BLAST profiles and accessible surface areas. The present approach achieved overall prediction accuracy of 73.8% for 77 individulal proteins collected from the Protein Data Bank, which is better than the previously reported accuracies