Neural network-based analysis of thiol proteomics data in identifying potential selenium targets

Jong Sik Lee, Yong Beom Ma, Kyoung Soo Choi, Soo Yeon Park, Sun Hee Baek, Young Mee Park, Ke Zu, Haitao Zhang, Clement Ip, Hong Kim Yeul, Eun Mi Park

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

Generation of a monomethylated selenium metabolite is critical for the anticancer activity of selenium. Because of its strong nucleophilicity, the metabolite can react directly with protein thiols to cause redox modification. Here, we report a neural network-based analysis to identify potential selenium targets. A reactive thiol specific reagent, BIAM, was used to monitor thiol proteome changes on 2D gel. We constructed a dynamic model and evaluated the relative importance of proteins mediating the cellular responses to selenium. Information from this study will provide new clues to unravel mechanisms of anticancer action of selenium. High impact selenium targets could also serve as biomarkers to gauge the efficacy of selenium chemoprevention.

Original languageEnglish
Pages (from-to)37-64
Number of pages28
JournalPreparative Biochemistry and Biotechnology
Volume36
Issue number1
DOIs
Publication statusPublished - 2006 Feb 1

Keywords

  • Anticancer action
  • Display thiol proteomics
  • Dynamic modeling
  • Neural-network
  • Redox modification
  • Selenium

ASJC Scopus subject areas

  • Biotechnology
  • Biochemistry

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  • Cite this

    Lee, J. S., Ma, Y. B., Choi, K. S., Park, S. Y., Baek, S. H., Park, Y. M., Zu, K., Zhang, H., Ip, C., Yeul, H. K., & Park, E. M. (2006). Neural network-based analysis of thiol proteomics data in identifying potential selenium targets. Preparative Biochemistry and Biotechnology, 36(1), 37-64. https://doi.org/10.1080/10826060500388512