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Associating Drugs, Targets and Clinical Outcomes into an Integrated Network Affords a New Platform for Computer-Aided Drug Repurposing

  1. Tudor I. Oprea1,2,3,*,
  2. Sonny Kim Nielsen2,
  3. Oleg Ursu1,3,
  4. Jeremy J. Yang1,3,
  5. Olivier Taboureau2,
  6. Stephen L. Mathias1,3,
  7. Irene Kouskoumvekaki2,
  8. Larry A. Sklar3,
  9. Cristian G. Bologa1,3,*

Article first published online: 17 MAR 2011

DOI: 10.1002/minf.201100023

Issue

Molecular Informatics

Molecular Informatics

Special Issue: 18th European Symposium on Quantitative Structure-Activity Relationships (EuroQSAR 2010), September 19–24, 2010, Rhodes, Greece

Volume 30, Issue 2-3, pages 100–111, March 14, 2011

Additional Information

How to Cite

Oprea, T. I., Nielsen, S. K., Ursu, O., Yang, J. J., Taboureau, O., Mathias, S. L., Kouskoumvekaki, I., Sklar, L. A. and Bologa, C. G. (2011), Associating Drugs, Targets and Clinical Outcomes into an Integrated Network Affords a New Platform for Computer-Aided Drug Repurposing. Molecular Informatics, 30: 100–111. doi: 10.1002/minf.201100023

Author Information

  1. 1

    Division of Biocomputing, Department of Biochemistry and Molecular Biology, University of New Mexico School of Medicine, MSC11 6145, Albuquerque, NM 87131, USA phone: +1 505 272 3694/6509; fax: +1 505 272 0238;

  2. 2

    Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Kemitorvet 8, Kgs. Lyngby, 2800, Denmark

  3. 3

    UNM Center for Molecular Discovery, University of New Mexico School of Medicine, MSC11 6145, Albuquerque, NM 87131, USA

*Division of Biocomputing, Department of Biochemistry and Molecular Biology, University of New Mexico School of Medicine, MSC11 6145, Albuquerque, NM 87131, USA phone: +1 505 272 3694/6509; fax: +1 505 272 0238;

Publication History

  1. Issue published online: 23 MAR 2011
  2. Article first published online: 17 MAR 2011
  3. Manuscript Accepted: 4 MAR 2011
  4. Manuscript Received: 21 FEB 2011

Funded by

  • NIH. Grant Numbers: 1R21GM095952-01, 5U54MH084690-03
  • Lundbeck Foundation. Grant Number: R32-A3932
  • Villum Foundation

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Keywords:

  • Drug discovery;
  • Drug side effects;
  • Drug targets;
  • Principal component analysis;
  • Text mining

Graphical Abstract

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Abstract

Finding new uses for old drugs is a strategy embraced by the pharmaceutical industry, with increasing participation from the academic sector. Drug repurposing efforts focus on identifying novel modes of action, but not in a systematic manner. With intensive data mining and curation, we aim to apply bio- and cheminformatics tools using the DRUGS database, containing 3837 unique small molecules annotated on 1750 proteins. These are likely to serve as drug targets and antitargets (i.e., associated with side effects, SE). The academic community, the pharmaceutical sector and clinicians alike could benefit from an integrated, semantic-web compliant computer-aided drug repurposing (CADR) effort, one that would enable deep data mining of associations between approved drugs (D), targets (T), clinical outcomes (CO) and SE. We report preliminary results from text mining and multivariate statistics, based on 7684 approved drug labels, ADL (Dailymed) via text mining. From the ADL corresponding to 988 unique drugs, the “adverse reactions” section was mapped onto 174 SE, then clustered via principal component analysis into a 5×5 self-organizing map that was integrated into a Cytoscape network of SE-D-T-CO. This type of data can be used to streamline drug repurposing and may result in novel insights that can lead to the identification of novel drug actions.

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