Predicting Protein-Protein Interactions from the Molecular to the Proteome Level

Keskin O., Tunçbağ N., Gursoy A.

CHEMICAL REVIEWS, vol.116, pp.4884-4909, 2016 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Review
  • Volume: 116
  • Publication Date: 2016
  • Doi Number: 10.1021/acs.chemrev.5b00683
  • Journal Name: CHEMICAL REVIEWS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.4884-4909
  • Middle East Technical University Affiliated: Yes


Identification of protein protein interactions (PPIs) is at the center of molecular biology considering the unquestionable role of proteins in cells. Combinatorial interactions result in a repertoire of multiple functions; hence, knowledge of PPI and binding regions naturally serve to functional proteomics and drug discovery. Given experimental limitations to find all interactions in a proteome, computational prediction/modeling of protein interactions is a prerequisite to proceed on the way to complete interactions at the proteome level. This review aims to provide a background on PPIs and their types. Computational methods for PPI predictions can use a variety of biological data including sequence-, evolution-, expression-, and structure-based data. Physical and statistical modeling are commonly used to integrate these data and infer PPI predictions. We review and list the state-of-the-art methods, servers, databases, and tools for protein-protein interaction prediction.