Affordable Access

deepdyve-link
Publisher Website

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

Authors
  • Khazen, Georges1
  • Gyulkhandanian, Aram2
  • Issa, Tina1
  • Maroun, Rachid C.2
  • 1 Computer Science and Mathematics Department, Lebanese American University, Byblos, Lebanon
  • 2 Inserm U1204/Université d’Evry/Université Paris-Saclay, Structure-Activité des Biomolécules Normales et Pathologiques, 91025 Evry, France
Type
Published Article
Journal
Computational and Structural Biotechnology Journal
Publisher
Elsevier
Publication Date
Sep 17, 2021
Volume
19
Pages
5184–5197
Identifiers
DOI: 10.1016/j.csbj.2021.09.013
PMCID: PMC8476896
Source
PubMed Central
Keywords
Disciplines
  • Research Article
License
Unknown

Abstract

Because 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 equally represent potential pharmacological targets par excellence for various diseases. Unfortunately, their experimental 3D structure and that of their complexes with other intramembrane protein 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 proper identification of the amino acid residues at the interface of molecular complexes with a 3D structure. The identified residues compose then nonlinear interaction motifs that are conveniently expressed as mathematical regular expressions. These are efficiently implemented for motif search in amino acid sequence databases, and for the accurate 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 compare our predictions to experimental datasets of protein-protein interactions as a first validation method. The online database that results from the PPIMem algorithm with the annotated predicted interactions are implemented as a web server and can be accessed directly at https://transint.univ-evry.fr .

Report this publication

Statistics

Seen <100 times