Neural Network‐Based Analysis of Thiol Proteomics Data in Identifying Potential Selenium Targets

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.

Keywords:

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

Acknowledgments

This work was supported by NIH CA109480, CA111846, CA09796, U.S. Army PC050127, Korea Health 21 R & D project 01-PJ3-PG6-01GN07, and Inha University.