Bioinformatic analysis

For bioinformatic analysis, MS hit list was curated and annotated with both UniProt IDs and Entrez GeneIDs.

Gene ontology (GO) and Functional annotation clustering analysis was performed using DAVID v6.8 [30,31]. The degree of common genes between annotations was measured using Kappa statistics with a similarity term overlap of 4 and a similarity threshold of 0.7. Group of similar annotations were classified based on Kappa values and according to the following parameters: initial group membership of 2, final group membership of 3 and a multiple linkage threshold of 0.3. Finally, an enrichment threshold of 1.0 was used.

The interaction network for proteins of interest was obtained by using STRING v10 [32]. High confidence interactions (minimum score: 0.7) were determined using the following four sources: text mining, experiments, databases or co-expression and the network was solidified adding up to five second shell interactors–proteins which were not identified but connect identified proteins. Finally, the network was visualized with Cytoscape [33].