Computational Methods for Predicting Protein-Protein Interactions Using Various Protein Features

Curr Protoc Protein Sci. 2018 Aug;93(1):e62. doi: 10.1002/cpps.62. Epub 2018 Jun 21.


Understanding protein-protein interactions (PPIs) in a cell is essential for learning protein functions, pathways, and mechanism of diseases. PPIs are also important targets for developing drugs. Experimental methods, both small-scale and large-scale, have identified PPIs in several model organisms. However, results cover only a part of PPIs of organisms; moreover, there are many organisms whose PPIs have not yet been investigated. To complement experimental methods, many computational methods have been developed that predict PPIs from various characteristics of proteins. Here we provide an overview of literature reports to classify computational PPI prediction methods that consider different features of proteins, including protein sequence, genomes, protein structure, function, PPI network topology, and those which integrate multiple methods. © 2018 by John Wiley & Sons, Inc.

Keywords: bioinformatics; computational methods; protein docking; protein interaction network; protein-protein interactions, PPI.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Computer Simulation*
  • Proteins / chemistry*
  • Proteins / metabolism*
  • Sequence Analysis, Protein / methods*


  • Proteins