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Inferring Chemogenomic Features from Drug‐Target Interaction Networks
Author(s) -
Yamanishi Yoshihiro
Publication year - 2013
Publication title -
molecular informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.481
H-Index - 68
eISSN - 1868-1751
pISSN - 1868-1743
DOI - 10.1002/minf.201300079
Subject(s) - cheminformatics , drug target , computer science , drug discovery , computational biology , drug , artificial intelligence , drug repositioning , machine learning , bioinformatics , biology , pharmacology
Drug effects are mainly caused by the interactions between drug molecules and target proteins including primary targets and off‐targets. Understanding of the molecular mechanisms behind overall drugtarget interactions is crucial in the drug design process. In this paper we review recently developed methods to infer chemogenomic features (the underlying associations between drug chemical substructures and protein domains) which are strongly involved in drug‐target interaction networks. We show the usefulness of the methods to detect ligand chemical fragments specific for each protein domain and ligand core substructures important for a wide range of protein families. We also discuss how to use the chemogenomic features for predicting unknown drug‐target interactions on a large scale.