Cell physiology is governed by an intricate mesh of physical and functional links among proteins, nucleic acids and other metabolites. The recent information flood coming from large-scale genomic and proteomic approaches allows us to foresee the possibility of compiling an exhaustive list of the molecules present within a cell, enriched with quantitative information on concentration and cellular localization. Moreover, several high-throughput experimental and computational techniques have been devised to map all the protein interactions occurring in a living cell. So far, such maps have been drawn as graphs where nodes represent proteins and edges represent interactions. However, this representation does not take into account the intrinsically modular nature of proteins and thus fails in providing an effective description of the determinants of binding. Since proteins are composed of domains that often confer on proteins their binding capabilities, a more informative description of the interaction network would detail, for each pair of interacting proteins in the network, which domains mediate the binding. Understanding how protein domains combine to mediate protein interactions would allow one to add important features to the protein interaction network, making it possible to discriminate between simultaneously occurring and mutually exclusive interactions. This objective can be achieved by experimentally characterizing domain recognition specificity or by analyzing the frequency of co-occurring domains in proteins that do interact. Such approaches allow gaining insights on the topology of complexes with unknown three-dimensional structure, thus opening the prospect of adopting a more rational strategy in developing drugs designed to selectively target specific protein interactions.