Disease associated protein-protein interaction network reconstruction based on comprehensive influence analysis

Abstract

Proteins and their interactions are fundamental to biological system. With the scientific paradigm shifting to systems biology, functional study of proteins from a network viewpoint to get a deep understanding of their roles in human life and diseases being increasingly essential. Although several methods already existed for protein-protein interaction (PPI) network building, the precise reconstruction of disease associated PPI network remains a challenge. In this paper we introduce a novel concept of comprehensive influence of proteins in network, in which direct and indirect connections are adopted for the calculation of influential effects of a protein with different weights. With the optimized weights, we calculate and select the important proteins and their interactions to reconstruct the PPI network for further validation and confirmation. To evaluate the performance of the method, we compared our model with the six existed ones by using five standard data sets. The results indicated that our method outperforms the existed ones. We then applied our model to prostate cancer and Parkinsons disease to predict novel disease associated proteins for the future experimental validation. Author SummaryThe diverse protein-protein interaction networks have dramatic effects on biological system. The disease associated PPI networks are generally reconstructed from experimental data with computational models but with limited accuracy. We developed a novel concept of comprehensive influence of proteins in network for reconstructing the PPI network. Our model outperforms the state-of-the-art ones and we then applied our model to identify novel interactions for further validation.