Prediction of Protein-Protein Interaction Sites Using Support Vector Machine

Identification of protein-protein interaction sites is essential for the mutant design and prediction of protein-protein networks.This paper proposes a method for predicting protein-protein interaction sites by combining support vector machine(SVM) and the sequence profiles,the accessible surface area(ASA) and the evolution rate of a residue.The dataset is trained and tested using 10-fold cross-validation.Accuracy of the proposed method is 72.91%,5.71% higher than that of the method only using the sequence profiles and the evolution rate of a residue.