Analysis and identification of toxin targets by topological properties in protein-protein interaction network

Abstract

Proteins do not exert their function in isolation of one another, but interact together in protein-protein interaction (PPI) networks. Analysis of topological properties of proteins in the PPI network is very helpful to understand the function of proteins. However, until recently, no one has ever undertaken to investigate toxin targets by topological properties. In this study, for the first time, 12 topological properties are used to investigate the characteristics of toxin targets in the PPI network. Most of the topological properties are found to be statistically discriminative between toxin targets and other proteins, and toxin targets tend to play more important roles in the PPI network. In addition, based on the topological properties and the sequence information, support vector machine (SVM) is used to predict toxin targets. The results obtained by the jackknife test and 10-fold cross validation are encouraging, indicating that SVM is a useful tool for predicting toxin targets, or at least can play complementary roles in relevant areas.

Keywords: Sequence information; Statistical test; Support vector machine; Topological features.