Protein interface complementarity and gene duplication improve link prediction of protein-protein interaction network

Abstract

Protein-protein interactions are the foundations of cellular life activities. At present, the already known protein-protein interactions only account for a small part of the total. With the development of experimental and computing technology, more and more PPI data are mined, PPI networks are more and more dense. It is possible to predict protein-protein interaction from the perspective of network structure. Although there are many high-throughput experimental methods to detect protein-protein interactions, the cost of experiments is high, time-consuming, and there is a certain error rate meanwhile. Network-based approaches can provide candidates of protein pairs for high-throughput experiments and improve the accuracy rate. This paper presents a new link prediction approach “Sim” for PPI networks from the perspectives of proteins’ complementary interfaces and gene duplication. By integrating our approach “Sim” with the state-of-art network-based approach “L3,” the prediction accuracy and robustness are improved.