Skip to main content

Drug-Induced Expression-Based Computational Repurposing of Small Molecules Affecting Transcription Factor Activity

  • Protocol
  • First Online:
Computational Methods for Drug Repurposing

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1903))

Abstract

Inhibition of oncogenes and reactivation of tumor suppressors are well-established goals in anticancer drug development. Unfortunately many oncogenes and tumor suppressors are not classically druggable, in that they lack a targetable enzymatic activity and associated binding pockets that small molecule drugs can be directed to. This is especially relevant for transcription factors, which have long been thought to be undruggable. To address this gap, we have developed and described CRAFTT, a broadly applicable computational drug-repositioning approach for targeting transcription factors. CRAFTT combines transcription factor target gene sets with drug-induced expression profiling to identify small molecules that can perturb transcription factor activity. Network analysis is then used to derive a modulation index (MI) and prioritize predictions.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Libermann TA, Zerbini LF (2006) Targeting transcription factors for cancer gene therapy. Curr Gene Ther 6:17–33

    Article  CAS  Google Scholar 

  2. Ablain J, Nasr R, Bazarbachi A, de The H (2011) The drug-induced degradation of oncoproteins: an unexpected Achilles' heel of cancer cells? Cancer Discov 1:117–127

    Article  CAS  Google Scholar 

  3. Delmore JE et al (2011) BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell 146:904–917

    Article  CAS  Google Scholar 

  4. Puissant A et al (2013) Targeting MYCN in neuroblastoma by BET bromodomain inhibition. Cancer Discov 3:308–323

    Article  CAS  Google Scholar 

  5. Gayvert KM et al (2016) A computational drug repositioning approach for targeting oncogenic transcription factors. Cell Rep 15:2348–2356

    Article  CAS  Google Scholar 

  6. Lamb J et al (2006) The Connectivity Map: using gene-expression signatures to connect small molecules, genes, and disease. Science 313:1929–1935

    Article  CAS  Google Scholar 

  7. Barrett T, Edgar R (2006) Gene expression omnibus: microarray data storage, submission, retrieval, and analysis. Methods Enzymol 411:352–369

    Article  CAS  Google Scholar 

  8. Giannopoulou EG, Elemento O (2011) An integrated ChIP-seq analysis platform with customizable workflows. BMC Bioinformatics 12:277

    Article  Google Scholar 

  9. Zhang Y et al (2008) Model-based analysis of ChIP-Seq (MACS). Genome Biol 9:R137

    Article  Google Scholar 

  10. Heinz S et al (2010) Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol Cell 38:576–589

    Article  CAS  Google Scholar 

  11. Szklarczyk D et al (2011) The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored. Nucleic Acids Res 39:D561–D568

    Article  CAS  Google Scholar 

  12. Khurana E, Fu Y, Chen J, Gerstein M (2013) Interpretation of genomic variants using a unified biological network approach. PLoS Comput Biol 9:e1002886

    Article  CAS  Google Scholar 

  13. Knox C et al (2011) DrugBank 3.0: a comprehensive resource for 'omics' research on drugs. Nucleic Acids Res 39:D1035–D1041

    Article  CAS  Google Scholar 

  14. Li H, Durbin R (2009) Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25:1754–1760

    Article  CAS  Google Scholar 

  15. Subramanian A et al (2005) Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A 102:15545–15550

    Article  CAS  Google Scholar 

  16. Hatzi K et al (2013) A hybrid mechanism of action for BCL6 in B cells defined by formation of functionally distinct complexes at enhancers and promoters. Cell Rep 4:578–588

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Olivier Elemento .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Science+Business Media, LLC, part of Springer Nature

About this protocol

Check for updates. Verify currency and authenticity via CrossMark

Cite this protocol

Gayvert, K., Elemento, O. (2019). Drug-Induced Expression-Based Computational Repurposing of Small Molecules Affecting Transcription Factor Activity. In: Vanhaelen, Q. (eds) Computational Methods for Drug Repurposing. Methods in Molecular Biology, vol 1903. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-8955-3_10

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-8955-3_10

  • Published:

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-8954-6

  • Online ISBN: 978-1-4939-8955-3

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics