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

International audienceBecause of their considerable number and diversity, membrane proteins and their macromolecular complexesrepresent the functional units of cells. Their quaternary structure may be stabilized by interactionsbetween the a-helices of different proteins in the hydrophobic region of the cell membrane. Membraneproteins equally represent potential pharmacological targets par excellence for various diseases.Unfortunately, their experimental 3D structure and that of their complexes with other intramembraneprotein partners are scarce due to technical difficulties. To overcome this key problem, we devisedPPIMem, a computational approach for the specific prediction of higher-order structures of a-helicaltransmembrane proteins. The novel approach involves proper identification of the amino acid residuesat the interface of molecular complexes with a 3D structure. The identified residues compose then nonlinearinteraction motifs that are conveniently expressed as mathematical regular expressions. These areefficiently implemented for motif search in amino acid sequence databases, and for the accurate predictionof intramembrane protein-protein complexes. Our template interface-based approach predicted21,544 binary complexes between 1,504 eukaryotic plasma membrane proteins across 39 species. Wecompare our predictions to experimental datasets of protein-protein interactions as a first validationmethod