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Related Concept Videos

Proteomics01:33

Proteomics

A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term proteomics...

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Standards for Quantitative Metalloproteomic Analysis Using Size Exclusion ICP-MS
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Metalloproteomes: a bioinformatic approach.

Claudia Andreini1, Ivano Bertini, Antonio Rosato

  • 1Magnetic Resonance Center (CERM) and Department of Chemistry, University of Florence, Via L. Sacconi 6, 50019 Sesto Fiorentino, Italy. andreini@cerm.unifi.it

Accounts of Chemical Research
|August 25, 2009
PubMed
Summary

Researchers are developing bioinformatics tools to identify all metalloproteins within an organism, crucial for understanding life at a systems level. These predictions aid in studying metalloprotein function and evolution across different life forms.

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JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

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Area of Science:

  • Bioinformatics
  • Systems Biology
  • Proteomics

Background:

  • Metal ions are essential for life, with metalloproteins playing vital physiological roles across all organisms.
  • A comprehensive understanding of metalloproteomes (the complete set of metalloproteins) is lacking due to the absence of established experimental analysis methods.
  • Systems biology requires complete metalloproteome information for accurate insights into the role of metal ions.

Purpose of the Study:

  • To discuss progress in developing bioinformatics methods for predicting metalloproteins solely from protein sequences.
  • To enable the scanning of entire proteomes for metalloproteins, aiding in the analysis of their function and evolution.
  • To present case studies predicting zinc, nonheme iron, and copper proteins across the three domains of life.

Main Methods:

  • Development of bioinformatics tools for predicting metalloproteins based on protein sequences.
  • Identification of specific metal-binding sites or domains within protein sequences.
  • Comparative analysis of predicted metalloproteomes across diverse organisms.

Main Results:

  • Zinc proteins constitute approximately 9% of eukaryotic proteomes, compared to 5-6% in prokaryotes, indicating an increase in higher organisms.
  • Nonheme iron proteins show a relatively constant number across eukaryotes and prokaryotes, with their relative share decreasing from archaea (7%) to bacteria (4%) to eukaryotes (1%).
  • Copper proteins represent less than 1% of proteomes in all studied organisms.

Conclusions:

  • Bioinformatics-based prediction of metalloproteomes is essential for systems biology and understanding the role of metals in life.
  • Comparative analysis of metalloproteomes provides insights into their evolution.
  • Ongoing development of prediction methods is crucial for improving accuracy and expanding our knowledge of metalloproteins.