Protein-protein interactions (PPIs) are the physical connections between two or more proteins
via electrostatic forces or hydrophobic effects. Identification of the PPIs is pivotal, which contributes
to many biological processes including protein function, disease incidence, and therapy design.
The experimental identification of PPIs via high-throughput technology is time-consuming and
expensive. Bioinformatics approaches are expected to solve such restrictions. In this review, our main
goal is to provide an inclusive view of the existing sequence-based computational prediction of PPIs.
Initially, we briefly introduce the currently available PPI databases and then review the state-of-the-art
bioinformatics approaches, working principles, and their performances. Finally, we discuss the caveats
and future perspective of the next generation algorithms for the prediction of PPIs.
Keywords: Protein-protein interactions, PPIs database, sequence features, feature selection, machine learning, bioinformatics.
Rights & PermissionsPrintExport