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BMC Syst Biol. 2013;7 Suppl 6:S18. doi: 10.1186/1752-0509-7-S6-S18. Epub 2013 Dec 13.

Inferring protein domains associated with drug side effects based on drug-target interaction network.

Abstract

BACKGROUND:

Most phenotypic effects of drugs are involved in the interactions between drugs and their target proteins, however, our knowledge about the molecular mechanism of the drug-target interactions is very limited. One of challenging issues in recent pharmaceutical science is to identify the underlying molecular features which govern drug-target interactions.

RESULTS:

In this paper, we make a systematic analysis of the correlation between drug side effects and protein domains, which we call "pharmacogenomic features," based on the drug-target interaction network. We detect drug side effects and protein domains that appear jointly in known drug-target interactions, which is made possible by using classifiers with sparse models. It is shown that the inferred pharmacogenomic features can be used for predicting potential drug-target interactions. We also discuss advantages and limitations of the pharmacogenomic features, compared with the chemogenomic features that are the associations between drug chemical substructures and protein domains.

CONCLUSION:

The inferred side effect-domain association network is expected to be useful for estimating common drug side effects for different protein families and characteristic drug side effects for specific protein domains.

PMID:
24565527
PMCID:
PMC4029543
DOI:
10.1186/1752-0509-7-S6-S18
[Indexed for MEDLINE]
Free PMC Article

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