A simple and robust method for connecting small-molecule drugs using gene-expression signatures.

Abstract:

BACKGROUND:Interaction of a drug or chemical with a biological system can result in a gene-expression profile or signature characteristic of the event. Using a suitably robust algorithm these signatures can potentially be used to connect molecules with similar pharmacological or toxicological properties by gene expression profile. Lamb et al first proposed the Connectivity Map [Lamb et al (2006), Science 313, 1929-1935] to make successful connections among small molecules, genes, and diseases using genomic signatures. RESULTS:Here we have built on the principles of the Connectivity Map to present a simpler and more robust method for the construction of reference gene-expression profiles and for the connection scoring scheme, which importantly allows the valuation of statistical significance of all the connections observed. We tested the new method with two randomly generated gene signatures and three experimentally derived gene signatures (for HDAC inhibitors, estrogens, and immunosuppressive drugs, respectively). Our testing with this method indicates that it achieves a higher level of specificity and sensitivity and so advances the original method. CONCLUSION:The method presented here not only offers more principled statistical procedures for testing connections, but more importantly it provides effective safeguard against false connections at the same time achieving increased sensitivity. With its robust performance, the method has potential use in the drug development pipeline for the early recognition of pharmacological and toxicological properties in chemicals and new drug candidates, and also more broadly in other 'omics sciences.

journal_name

BMC Bioinformatics

journal_title

BMC bioinformatics

authors

Zhang SD,Gant TW

doi

10.1186/1471-2105-9-258

subject

Has Abstract

pub_date

2008-06-02 00:00:00

pages

258

issn

1471-2105

pii

1471-2105-9-258

journal_volume

9

pub_type

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