Protein interactions

Protein-protein interactions are essential for many processes in cellular life, such as cell signaling, gene expression and control and antibody–antigen binding, and they are often blocked or altered in disease. Knowledge about interaction networks can therefore help in understanding disease mechanisms and in developing diagnostic and therapeutic strategies.

The Interaction section presents interaction networks for 15038 genes based on protein-protein interaction data from IntAct, BioGRID, BioPlex and OpenCell that has been integrated with data related to protein expression, location and classification. More information about the specific content and the generation of the data in this section can be found in the Methods summary.

Learn about:

the interaction partners of proteins
the predicted and subcellular location of the proteins in the network
the expression specificity of the proteins in the network
the interaction partners expressed in the same cell type for genes with specific expression

The protein-protein interaction network plots for each gene is based on data from IntAct, BioPlex, OpenCell and BioGRID and enables exploration of the interaction partners in each dataset separately and, if applicable, in a consensus network showing only interactions present in more than one of the datasets. More information about the genes in the network is displayed by mouse-over and the network can be extended by clicking on a gene of interest.

Figure 1. First-level consensus interactions for the nuclear protein AURKB colored according to subcellular location (left) and cell type specificity (right). The edge colors represent the number of datasets for the interacting pair and datasets involved are shown by mouse-over.

To allow for deeper understanding of the interaction partners and their context the genes in a network can be colored according to experimental subcellular location based on data in the Subcellular resource, predicted location based on signal peptide and transmembrane region predictors, tissue specificity based on RNA tissue expression profiles or protein class. This is exemplified by the first-level consensus network for the AURKB gene colored according to subcellular location and cell type specificity, respectively, in Figure 1. There is also a highlight option for genes categorised as cell type enriched that will show interaction partners expressed in the same cell type(s) and thus indicate the most probable interactors in the particular cell type(s). Custom highlighting of genes is possible using the query builder in the Filter option.

Figure 2. The distribution of the number of consensus interactions. The exact number of genes can be shown using mouse-over

About half of the genes with interaction data (n=7712) have at least one consensus interaction. The bar plot in Figure 2 shows the distribution of the number of consensus interactions for these genes.

Figure 3. Single cell type specificity across the groups with different numbers of consensus interactions. The fraction of genes classified as Cell type enriched is shown in red, Group enriched in orange, Cell type enhanced in purple and Low cell type specificity in dark grey. The number of genes in each category is shown using mouse-over.

Among the 2378 genes with a single consensus interaction 421 are tissue or group enriched, while corresponding number for genes having more than five consensus interactions is 156 out of 2229. The bar plot in Figure 3 shows the fraction of the single cell type specificity categories in all different groups.