Integration of protein abundance and structure data reveals competition in the ErbB signaling network

The mechanisms of context-specific differences in signal transduction, such as those that occur among different cell types, are not fully understood. One possibility is that differences in the abundance of proteins change signaling outputs because these proteins compete for binding to hub proteins at critical network branch points. Focusing on the ErbB signaling, we created a protein interaction network that included information about protein domains and analyzed the role of competing protein interactions. By leveraging three-dimensional protein structures to infer steric interactions among binding partners for a common binding domain or linear motif (node) and including information about protein abundance and interaction affinities, we identified a large number of competitive, mutually exclusive (XOR) protein interactions. Modeling changes in protein abundance with different patterns of partner proteins and XOR nodes (XOR motifs) revealed that each motif conferred a different response. We experimentally investigated the XOR motif containing the hub protein Ras and its binding partners RIN1 (Ras and Rab interactor 1) and CRAF (v-raf-leukemia viral oncogene 1). Consistent with the computational prediction, overexpression of RIN1 in cultured cells decreased the phosphorylation of CRAF and its downstream targets. Thus, our analyses provide evidence that variation in the abundance of proteins that compete for binding to XOR nodes could contribute to context-specific signaling plasticity.