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Bioinformatics. 2012 Sep 15;28(18):i611-i618. doi: 10.1093/bioinformatics/bts413.

Drug target prediction using adverse event report systems: a pharmacogenomic approach.

Author information

1
Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan.

Abstract

MOTIVATION:

Unexpected drug activities derived from off-targets are usually undesired and harmful; however, they can occasionally be beneficial for different therapeutic indications. There are many uncharacterized drugs whose target proteins (including the primary target and off-targets) remain unknown. The identification of all potential drug targets has become an important issue in drug repositioning to reuse known drugs for new therapeutic indications.

RESULTS:

We defined pharmacological similarity for all possible drugs using the US Food and Drug Administration's (FDA's) adverse event reporting system (AERS) and developed a new method to predict unknown drug-target interactions on a large scale from the integration of pharmacological similarity of drugs and genomic sequence similarity of target proteins in the framework of a pharmacogenomic approach. The proposed method was applicable to a large number of drugs and it was useful especially for predicting unknown drug-target interactions that could not be expected from drug chemical structures. We made a comprehensive prediction for potential off-targets of 1874 drugs with known targets and potential target profiles of 2519 drugs without known targets, which suggests many potential drug-target interactions that were not predicted by previous chemogenomic or pharmacogenomic approaches.

AVAILABILITY:

Softwares are available upon request.

CONTACT:

yamanishi@bioreg.kyushu-u.ac.jp

SUPPLEMENTARY INFORMATION:

Datasets and all results are available at http://cbio.ensmp.fr/~yyamanishi/aers/.

PMID:
22962489
PMCID:
PMC3436840
DOI:
10.1093/bioinformatics/bts413
[Indexed for MEDLINE]
Free PMC Article

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