Getting to know each other: PPIMem, a novel approach for predicting transmembrane protein-protein complexes

Abstract

ABSTRACTBecause of their considerable number and diversity, membrane proteins and their macromolecular complexes represent the functional units of cells. Their quaternary structure may be stabilized by interactions between the α-helices of different proteins in the hydrophobic region of the cell membrane. Membrane proteins also represent potential pharmacological targets par excellence for various diseases. Unfortunately, their experimental 3D structure and that of their complexes with intramembrane interacting partners are scarce due to technical difficulties. To overcome this key problem, we devised PPIMem, a computational approach for the specific prediction of higher-order structures of α-helical transmembrane proteins. The novel approach involves identification of the amino acid residues at the interface of complexes with a 3D structure. The identified residues compose then interaction motifs that are conveniently expressed as mathematical regular expressions. These are used for motif search in databases, and for the prediction of intramembrane protein-protein complexes. Our template interface-based approach predicted 21, 544 binary complexes between 1, 504 eukaryotic plasma membrane proteins across 39 species. We compared our predictions to experimental datasets of protein-protein interactions as a first validation method. The PPIMem online database with the annotated predicted interactions is implemented as a web server and can be accessed directly at https://transint.shinyapps.io/transint/.