Augmented Transitive Relationships in Direct Protein-Protein Interaction Prediction

Abstract

The prediction of new protein-protein interactions is important to the discovery of the currently unknown function of various biological pathways. In addition, many databases of protein-protein interactions contain different types of interactions, including protein associations, physical protein associations and direct protein interactions. There are only a few studies that consider the issues inherent to the prediction of direct protein-protein interactions, that is, interactions between proteins that are actually in direct physical contact and are listed in known protein interaction databases. Predicting these interactions is a crucial and challenging task. Therefore, it is increasingly important to discover not only protein associations but also direct interactions. Many studies have predicted protein-protein interactions directly, by using biological features such as Gene Ontology (GO) functions and protein structural domains of two proteins with unknown interactions. In this article, we proposed an augmented transitive relationships predictor (ATRP), a new method of predicting potential direct protein-protein interactions by using transitive relationships and annotations of protein interactions. Our results demonstrate that ATRP can effectively predict unknown direct protein-protein interactions from existing protein interaction relationships. The average accuracy of this method outperformed GO-based prediction methods by a factor ranging from 28% to 62%.