Taiwanese Journal of Obstetrics and Gynecology
Volume 48, Issue 2 , Pages 130-132, June 2009

Mutation-Prone Positions Within the Estrogen Receptor

  • Viroj Wiwanitkit

      Affiliations

    • Corresponding Author InformationCorrespondence to: Dr Viroj Wiwanitkit, Wiwanitkit House, Bangkhae, Bangkok 10160, Thailand

Wiwanitkit House, Bangkhae, Bangkok, Thailand

Accepted 20 July 2008.

Article Outline

Summary 

Objective

Estrogen is an important female hormone. The estrogen receptor (ER) plays a critical role in the development of breast cancer. Mutations within the ER can have clinically significant consequences.

Materials and Methods

Identification of sites vulnerable to mutation is a new trend aimed at extending our knowledge of diseases at the genomic and proteomic levels. In this study, bioinformatics analysis was performed to determine the positions corresponding to specific peptide motifs in the amino acid sequence of the ER. A new computational tool called GlobPlot was used to identify the weak linkage positions within the ER.

Results

The results allowed the identification of mutation-resistant positions.

Conclusion

This study showed that the weak linkages within the ER could be identified, and these could provide the basis for further studies aimed at predicting possible new ER mutations.

Key Words:  estrogen , mutation , receptor , weak linkage

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References 

  1. Leclercq G , Lacroix M , Laios I , Laurent G . Estrogen receptor alpha: impact of ligands on intracellular shuttling and turnover rate in breast cancer cells . Curr Cancer Drug Targets . 2006;6:39–64
  2. Cordera F , Jordan VC . Steroid receptors and their role in the biology and control of breast cancer growth . Semin Oncol . 2006;33:631–641
  3. Ikeda K , Inoue S . Estrogen receptors and their downstream targets in cancer . Arch Histol Cytol . 2004;67:435–442
  4. Schneider HP , Bocker W . Hormones and progeny of breast tumor cells . Climacteric . 2006;9:88–107
  5. Herynk MH , Fuqua SA . Estrogen receptor mutations in human disease . Endocr Rev . 2004;25:869–898
  6. Lee C , Wang Q . Bioinformatics analysis of alternative splicing . Brief Bioinform . 2005;6:23–33
  7. Levin JM , Penland RC , Stamps AT , Cho CR . Using in silico biology to facilitate drug development . Novartis Found Symp . 2002;247:222–238
  8. Gasteiger E , Gattiker A , Hoogland C , Ivanyi I , Appel RD , Bairoch A . ExPASy: the proteomics server for in-depth protein knowledge and analysis . Nucleic Acids Res . 2003;31:3784–3788
  9. Linding R , Russell RB , Neduva V , Gibson TJ . GlobPlot: exploring protein sequences for globularity and disorder . Nucleic Acids Res . 2003;31:3701–3708
  10. Pearce ST , Jordan VC . The biological role of estrogen receptors alpha and beta in cancer . Crit Rev Oncol Hematol . 2004;50:3–22
  11. Murphy LC , Dotzlaw H , Leygue E , Douglas D , Coutts A , Watson PH . Estrogen receptor variants and mutations . J Steroid Biochem Mol Biol . 1997;62:363–372
  12. Gogarten JP , Olendzenski L . Orthologs, paralogs and genome comparisons . Curr Opin Genet Dev . 1999;9:630–636
  13. Golaz O , Wilkins MR , Sanchez JC , Appel RD , Hochstrasser DF , Williams KL . Identification of proteins by their amino acid composition: an evaluation of the method . Electrophoresis . 1996;17:573–579
  14. Wiwanitkit V . Where is the weak linkage in the globin chain? . Int J Nanomedicine . 2006;1:109–110
  15. Wiwanitkit V . Mutation-prone points in thrombin receptor . J Thromb Thrombolysis . 2008;25:190–192
  16. Wiwanitkit V . Weak linkage in androgen receptor: identification of mutation-prone points . Fertil Steril . 2009;91:e1–e3
  17. Wiwanitkit V . Identification of weak points prone for mutation in ferredoxin of Trichomonas vaginalis . Indian J Med Microbiol . 2008;26:158–159
  18. Wiwanitkit V . Identification of mutation-prone points in bile salt export pump . HPB (Oxford) . 2007;9:444–446
  19. Azuaje F , Al-Shahrour F , Dopazo J . Ontology-driven approaches to analyzing data in functional genomics . Methods Mol Biol . 2006;316:67–86
  20. Khan S , Situ G , Decker K , Schmidt CJ . GoFigure: automated Gene Ontology annotation . Bioinformatics . 2003;19:2484–2485

PII: S1028-4559(09)60272-2

doi:10.1016/S1028-4559(09)60272-2

Taiwanese Journal of Obstetrics and Gynecology
Volume 48, Issue 2 , Pages 130-132, June 2009

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