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

Chem Rev. 2016 Apr 27;116(8):4884-909. doi: 10.1021/acs.chemrev.5b00683. Epub 2016 Apr 13.

Abstract

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.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Amino Acid Sequence
  • Binding Sites
  • Data Mining*
  • Databases, Protein / statistics & numerical data*
  • Gene Expression
  • Humans
  • Molecular Docking Simulation
  • Molecular Dynamics Simulation
  • Protein Binding
  • Protein Interaction Domains and Motifs*
  • Protein Interaction Mapping / methods*
  • Protein Interaction Mapping / statistics & numerical data
  • Proteome / chemistry*
  • Proteome / genetics
  • Proteome / metabolism
  • Proteomics
  • Sequence Homology, Amino Acid
  • Software

Substances

  • Proteome