Modularity in protein complex and drug interactions reveals new polypharmacological properties

Abstract

Recent studies have highlighted the importance of interconnectivity in a large range of molecular and human disease-related systems. Network medicine has emerged as a new paradigm to deal with complex diseases. Connections between protein complexes and key diseases have been suggested for decades. However, it was not until recently that protein complexes were identified and classified in sufficient amounts to carry out a large-scale analysis of the human protein complex system. We here present the first systematic and comprehensive set of relationships between protein complexes and associated drugs and analyzed their topological features. The network structure is characterized by a high modularity, both in the bipartite graph and in its projections, indicating that its topology is highly distinct from a random network and that it contains a rich and heterogeneous internal modular structure. To unravel the relationships between modules of protein complexes, drugs and diseases, we investigated in depth the origins of this modular structure in examples of particular diseases. This analysis unveils new associations between diseases and protein complexes and highlights the potential role of polypharmacological drugs, which target multiple cellular functions to combat complex diseases driven by gain-of-function mutations.

Figure 1. Example of bipartite and projected networks.

(a) A bipartite sub-network extracted from the complex-drug network. (b) The drug and protein complex projected networks. Drugs are denoted by diamonds and complexes by circles.

Figure 2. Bipartite network of protein complexes and drugs, and associated modules.

A drug is connected to a protein complex if at least one protein target of the drug is also a subunit of the protein complex. Complexes are represented by circles and drugs by diamonds. Colors are attributed to modules on an arbitrary basis, so that each module has a specific color. Drugs and protein complexes are labeled by their DrugBank and CORUM identifier, respectively; mappings between these database identifiers and common names are provided in Information S2 and S3.

Figure 3. Projected network of complex modules.

Each module of the protein complex – drug bipartite network was shrunk into a node and the complex projection of the resulting network is represented. Modules are named according to a representative complex hub inside the module; only names of large modules are displayed for clarity. Colors are attributed to modules on an arbitrary basis, so that each module has a specific color. The size of nodes is proportional to the number of complexes in each module; a size scale is displayed on the right-hand side of the figure. To assign names to condensed nodes, we chose a representative member of each module by selecting the drug with the highest degree inside the module.

Figure 4. Projected network of drug modules.

Each module of the protein complex – drug bipartite network was shrunk into a node and the drug projection of the resulting network is represented. Modules are named according to a representative drug hub inside the module. Colors are attributed to modules on an arbitrary basis, so that each module has a specific color. The size of nodes is proportional to the number of drugs in each module; a size scale is displayed on the right-hand side of the figure. To assign names to condensed nodes, we chose a representative member of each module by selecting the complex with the highest degree inside the module. In the case of protein complex names formed by association of numerous protein names, we selected the protein occurring most frequently in complexes connected to the complex of highest degree.

Figure 5. Network metrics in projected networks of modules.

Top panels are from the drug projection and bottom panels from the complex projection. Left side panels represent betweenness centrality and right side panels closeness centrality.

Figure 6

(a) Distribution of shortest distances in the entire protein-protein interaction network (blue curve) and in interactions between all proteins involved in complexes (green curve); interactions between proteins involved in complexes and belonging to the same module are shown by the red curve, and these belonging to the same module but not to the same protein complex are shown by the orange curve. (b) Observed characteristic path length (red arrow) and distribution of characteristic path lengths for the random control (blue curve). We generated 100 independent samples by randomly shuffling protein associations while keeping each node degree unchanged.

Figure 7. Tripartite network of drugs and protein complexes connected to Leigh disease.

Links between the disease node and protein complexes represent associations between genes involved in these complexes and the named disease, as specified by the Disease Ontology. Links between protein complexes and drugs are the same as in our bipartite network, meaning that a drug is connected to a protein complex if at least one protein target of the drug is also a subunit of the protein complex. Complexes are represented by circles and drugs by diamonds. Colors are attributed to modules on an arbitrary basis, so that each module has a specific color. The disease node is represented by a yellow circle. The size of nodes is proportional to the degree of each node; a size scale is displayed on the right-hand side of the figure.

Figure 8. Tripartite network of drugs and complexes connected to Parkinson disease.

Links between the disease node and protein complexes represent associations between genes involved in these complexes and the named disease, as specified by the Disease Ontology. Links between protein complexes and drugs are the same as in our bipartite network, meaning that a drug is connected to a protein complex if at least one protein target of the drug is also a subunit of the protein complex. Complexes are represented by circles and drugs by diamonds. Colors are attributed to modules on an arbitrary basis, so that each module has a specific color. The disease node is represented by a yellow circle. The size of nodes is proportional to the degree of each node; a size scale is displayed on the right-hand side of the figure.