Augmented Transitive Relationships in Direct Protein-Protein Interaction Prediction

The prediction of new protein¡Vprotein interactions is important to the discovery of the currently unknown function of various biological pathways. In addition, many databases of protein¡Vprotein 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¡Vprotein 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¡Vprotein 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¡Vprotein interactions by using transitive relationships and annotations of protein interactions. Our results demonstrate that ATRP can effectively predict unknown direct protein¡Vprotein 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%.