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Issue 5, 2012
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Predicting drug targets based on protein domains

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Abstract

The identification of interactions between drugs and proteins plays key roles in understanding mechanisms underlying drug actions and can lead to new drug design strategies. Here, we present a novel statistical approach, namely PDTD (Predicting Drug Targets with Domains), to predict potential target proteins of new drugs based on derived interactions between drugs and protein domains. The known target proteins of those drugs that have similar therapeutic effects allow us to infer interactions between drugs and protein domains which in turn leads to identification of potential drug–protein interactions. Benchmarking with known drug–protein interactions shows that our proposed methodology outperforms previous methods that exploit either protein sequences or compound structures to predict drug targets, which demonstrates the predictive power of our proposed PDTD method.

Graphical abstract: Predicting drug targets based on protein domains

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Supplementary files

Publication details

The article was received on 01 Nov 2011, accepted on 14 Feb 2012 and first published on 08 Mar 2012


Article type: Paper
DOI: 10.1039/C2MB05450G
Citation: Mol. BioSyst., 2012,8, 1528-1534
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    Predicting drug targets based on protein domains

    Y. Wang, J. C. Nacher and X. Zhao, Mol. BioSyst., 2012, 8, 1528
    DOI: 10.1039/C2MB05450G

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