Dynamic PPIs

Conflict-Sensitive Scheduling & Dynamics Prediction of PPI Networks

Abstract

An important issue in protein-protein interaction network studies is the identification of interaction dynamics. Two factors contribute to the dynamics. One, not all proteins may be expressed in a given cell, and two, competition may exist among multiple proteins for a particular protein domain. Taking into account these two factors, we propose a method for building scheduling of interactions based on an extended notion of mutually exclusive interactions (interactions having the same target). By integrating data from different sources on the HeLa cancer cells and Homo sapiens (human) cells, we find a number of conflicting interaction pairs in post-translational modifications and in phosphorylation, which we use as spatial constraints. We further extend the spatial constraints by exploring non-conflicting upstream interactions (which we call conflict-free upstream cascades) to build an extended conflict graph. By integrating coloring-based clustering of the extended-conflict graph and activation patterns generated by soft clustering of proteomic time profile data, we calculate the maximum likelihood conflictsensitive scheduling using maximum bipartite matching. We use the scheduling results to infer a hypergraph of protein-protein interactions. The hyperedges of the hypergraph correspond to dynamic network modules. Those hyperedges can be used to predict protein complexes.