Literature DB >> 27481144

Inferring Chemogenomic Features from Drug-Target Interaction Networks.

Yoshihiro Yamanishi1,2.   

Abstract

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 drugtarget 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.
Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Keywords:  Chemical substructures; Chemogenomics; Drug-target interactions; Feature extraction; Protein domains

Year:  2013        PMID: 27481144     DOI: 10.1002/minf.201300079

Source DB:  PubMed          Journal:  Mol Inform        ISSN: 1868-1743            Impact factor:   3.353


  3 in total

1.  Evaluation of deep and shallow learning methods in chemogenomics for the prediction of drugs specificity.

Authors:  Benoit Playe; Veronique Stoven
Journal:  J Cheminform       Date:  2020-02-10       Impact factor: 5.514

2.  Efficient multi-task chemogenomics for drug specificity prediction.

Authors:  Benoit Playe; Chloé-Agathe Azencott; Véronique Stoven
Journal:  PLoS One       Date:  2018-10-04       Impact factor: 3.240

3.  Prediction of Protein-Ligand Interaction Based on the Positional Similarity Scores Derived from Amino Acid Sequences.

Authors:  Dmitry Karasev; Boris Sobolev; Alexey Lagunin; Dmitry Filimonov; Vladimir Poroikov
Journal:  Int J Mol Sci       Date:  2019-12-18       Impact factor: 5.923

  3 in total

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