Protein-protein interactions (PPI) play a key role in predicting the function of a target protein and drug ability to affect an entire biological system. Prediction of PPI networks greatly contributes to determine a target protein and signal pathways related to its function. Polyadenylation of mRNA 3'-end is essential for gene expression regulation and several polyadenylation factors have been shown as valuable targets for controlling protozoan parasites that affect human health. Here, by using a computational strategy based on sequence-based prediction approaches, phylogenetic analyses, and computational prediction of PPI networks, we compared interactomes of polyadenylation factors in relevant protozoan parasites and the human host, to identify key proteins and define potential targets for pathogen control. Then, we used Entamoeba histolytica as a working model to validate our computational results. RT-qPCR assays confirmed the coordinated modulation of connected proteins in the PPI network and evidenced that silencing of the bottleneck protein EhCFIm25 affects the expression of interacting proteins. In addition, molecular dynamics simulations and docking approaches allowed to characterize the relationships between EhCFIm25 and Ehnopp34, two connected bottleneck proteins. Interestingly, the experimental identification of EhCFIm25 interactome confirmed the close relationships among proteins involved in gene expression regulation and evidenced new links with moonlight proteins in E. histolytica, suggesting a connection between RNA biology and metabolism as described in other organisms. Altogether, our results strengthened the relevance of comparative genomics and interactomics of polyadenylation factors for the prediction of new targets for the control of these human pathogens.
Keywords: bioinformatics; mRNA processing; protein-protein interactions; protozoa; therapeutic markers.
© 2023 The Author(s).