Skip to main content

High-Throughput Analysis of the Drug Mode of Action of PB28, MC18 and MC70, Three Cyclohexylpiperazine Derivative New Molecules

  • Conference paper
Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence (ICIC 2008)

Abstract

Objective: This work explores the mode of action of PB28, MC70 and MC18 three molecules that showed anti-tumoral properties by arresting cellular growth and inhibiting glycoprotein P. Methods: Here we conduct a microarray-based study and analyze the expression patterns associated with the action of drugs. An ontology based analysis has been conducted, and the individuated cellular processes have been analyzed with gene networks, examining the interactions among genes. A clustering analysis revealed mechanisms shared with other drugs. Results: The results indicate that this compounds have side effects that include inflammatory response and fever, induced by the interleukin signaling pathway. Other evidences related with known effects of the compounds were highlighted. Conclusions: The results indicate that the direct effects could be reached at a post-transcriptional level of P-gp or through other targets, further studies will address these hypothesis. The prediction of side effects will be useful in subsequent in vivo experiments.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 189.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Amalia, A., Nicola, A., Colabufo, F.B., Letizia, P., Niso, M., Simone, G.M., Roberto, P., Angelo, P.: Cyclohexylpiperazine Derivative PB28, a s2 Agonist and s1 Antagonist Receptor, Inhibits Cell Growth, Modulates P-glycoprotein, and Synergizes with Anthracyclines in Breast Cancer. Mol. Cancer Ther. 5(7), 1807–1816 (2006)

    Article  Google Scholar 

  2. Li, J., Pankratz, M., Johnson, J.A.: Differential Gene Expression Patterns Revealed by Oligonucleotide Versus Long cDNA Arrays. Toxicol. Sci. 69(2), 383–390 (2002)

    Article  Google Scholar 

  3. Marton, et al.: Drug Target Validation and Identification of Secondary Drug Target Effects Using DNA Microarrays. Nature Medicine 4(11), 1293–1301 (1998)

    Article  Google Scholar 

  4. Pan, W.: A Comparative Review of Statistical Methods for Discovering Differentially Expressed Genes in Replicated Microarray Experiments. Bioinformatics 18(4), 546–554 (2002)

    Article  Google Scholar 

  5. Jeffery, I.B., Higgins, D.G., Culhane, A.C.: Comparison and Evaluation of Methods for Generating Differentially Expressed Gene Lists from Microarray Data. BMC Bioinformatics 7, 359 (2006)

    Article  Google Scholar 

  6. Ye, C., Eskin, E.: Discovering Tightly Regulated and Differentially Expressed Gene Sets in Whole Genome Expression Data. In: ECCB 2006, vol. 23, pp. 84–90 (2006)

    Google Scholar 

  7. Bernardo, D.D., et al.: Chemogenomic Profiling on a Genome-wide Scale Using Reverse-engineered Gene Networks. Nature Biotechnology 23(3), 377–383 (2005)

    Article  Google Scholar 

  8. Timothy, S., Gardner, Faith, J.J.: Reverse-engineering Transcription Control Networks. Physiscs of Life Reviews 2, 65–88 (2005)

    Article  Google Scholar 

  9. Markowetz, F., Spang, R.: Inferring Cellular Networks: a Review. BMC Bioinformatics 8, S5 (2007)

    Article  Google Scholar 

  10. Dahlquist, K.D., Salomonis, N., Vranizan, K., Lawlor, S.C., Conklin, B.R.: GenMAPP, a New Tool for Viewing and Analyzing Microarray Data on Biological Pathways. Nat. Genet. 31, 19–20 (2002)

    Article  Google Scholar 

  11. Doniger, S.W., Salomonis, N., Dahlquist, K.D., Vranizan, K., Lawlor, S.C., Conklin, B.R.: MAPPFinder: Using Gene Ontology and GenMAPP to create a Global Gene-Expression Profile from Microarray Data. Genome. Biol. 4, R7 (2003)

    Article  Google Scholar 

  12. Zeeberg, et al.: GoMiner: A Resource for Biological Interpretation of Genomic and Proteomic Data. Genome Biology 4(4), R28 (2003)

    Article  Google Scholar 

  13. Sallenave, J.M., Res, R.: The Role of Secretory Leukocyte Proteinase Inhibitor and Elafin (Elastase-specific Inhibitor/skin-derived Antileukoprotease) as Alarm Antiproteinases. Inflammatory Lung Disease 1(2), 87–92 (2000)

    Google Scholar 

  14. Sontheimer, E.J., Steitz, J.A.: Three Novel Functional Variants of Human U5 Small Nuclear RNA. Mol. Cell. Biol. 12(2), 734–746 (1992)

    Google Scholar 

  15. Lamb, J., et al.: The Connectivity Map: Using Gene-expression Signatures to Connect Small Molecules, Genes and Diseases. Science 313, 1929–1935 (2006)

    Article  Google Scholar 

  16. Bertoni, et al.: Random Projections for Assessing Gene Expression Cluster Stability. In: IJCNN 2005. LNCS, vol. 3931, pp. 31–37 (2005)

    Google Scholar 

  17. Tusher, et al.: Significance Analysis of Microarrays Applied to the Ionizing Radiation Response. PNAS 98(9), 5116–5121 (2001)

    Article  MATH  Google Scholar 

  18. Ciaramella, et al.: Interactive Data Analysis and Clustering of Genomic Data. Neural Networks 21(2-3), 368–378 (2007)

    Article  Google Scholar 

  19. Ciaramella, et al.: Clustering, Assessment and Validation: an Application to gene Expression Data. In: Proceedings of the International Joint Conference on Neural Networks. IJCNN 2007, p. 1419 (2007)

    Google Scholar 

  20. Iorio, F., Miele, G., Napolitano, F., Raiconi, G., Tagliaferri, R.: An Interactive Tool for Data Visualization and Clustering. In: Apolloni, B., Howlett, R.J., Jain, L. (eds.) KES 2007, Part III. LNCS (LNAI), vol. 4694, pp. 870–877. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

De-Shuang Huang Donald C. Wunsch II Daniel S. Levine Kang-Hyun Jo

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Bevilacqua, V. et al. (2008). High-Throughput Analysis of the Drug Mode of Action of PB28, MC18 and MC70, Three Cyclohexylpiperazine Derivative New Molecules. In: Huang, DS., Wunsch, D.C., Levine, D.S., Jo, KH. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2008. Lecture Notes in Computer Science(), vol 5227. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85984-0_130

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-85984-0_130

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-85983-3

  • Online ISBN: 978-3-540-85984-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics