Computational Methods for Predicting Protein‐Protein Interactions Using Various Protein Features
Author(s) -
Ding Ziyun,
Kihara Daisuke
Publication year - 2018
Publication title -
current protocols in protein science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.409
H-Index - 32
eISSN - 1934-3663
pISSN - 1934-3655
DOI - 10.1002/cpps.62
Subject(s) - chemistry , protein–protein interaction , computational biology , biophysics , biological system , biochemistry , biology
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.
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