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Related Concept Videos

Peptide Identification Using Tandem Mass Spectrometry01:33

Peptide Identification Using Tandem Mass Spectrometry

Tandem mass spectrometry, also known as MS/MS or MS2, is an analytical technique that employs two mass analyzers. Essentially it is a series of mass spectrometers that helps isolate a particular biomolecule and then helps study its chemical properties.
This technique helps gather information regarding the protein from which the peptide was obtained and to study the peptides’ amino acid sequence. Identifying peptides from a complex mixture is an important component of the growing field of...

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Detection of Protein Ubiquitination Sites by Peptide Enrichment and Mass Spectrometry
11:54

Detection of Protein Ubiquitination Sites by Peptide Enrichment and Mass Spectrometry

Published on: March 23, 2020

Protein identification and Peptide expression resolver: harmonizing protein identification with protein expression

Paul Kearney1, Heather Butler, Kevin Eng

  • 1Caprion Proteomics. Montreal, QC, Canada, H4S 2C8. pkearney13@hotmail.com

Journal of Proteome Research
|December 8, 2007
PubMed
Summary

This study shows that analyzing peptide expression profiles enhances protein identification accuracy in proteomics. The new tool, PIPER (Protein Identification and Peptide Expression Resolver), significantly reduces false positive protein identifications.

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Detection of Protein Ubiquitination Sites by Peptide Enrichment and Mass Spectrometry
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Resolving Affinity Purified Protein Complexes by Blue Native PAGE and Protein Correlation Profiling
09:35

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Published on: April 1, 2017

Area of Science:

  • Proteomics
  • Biochemistry
  • Bioinformatics

Background:

  • Proteomic discovery platforms yield both peptide expression and protein identification data.
  • Peptide expression data typically guide protein identification by highlighting differentially expressed peptides.
  • The current study explores using peptide expression data to improve protein identification confidence.

Purpose of the Study:

  • To evaluate the hypothesis that tryptic peptides from the same protein exhibit similar expression profiles.
  • To develop and validate a computational tool leveraging this hypothesis for enhanced protein identification.
  • To reduce the rate of erroneous protein identifications in proteomic studies.

Main Methods:

  • Analysis of peptide expression profiles across multiple samples.
  • Development of the Protein Identification and Peptide Expression Resolver (PIPER) tool.
  • Application of PIPER to a large-scale (72-sample) biomarker discovery dataset.

Main Results:

  • Demonstrated that tryptic peptides from the same protein share similar expression patterns.
  • PIPER successfully reduced false positive protein identifications to below 5%.
  • Validated PIPER's effectiveness in a real-world biomarker discovery study.

Conclusions:

  • Peptide expression information is a valuable resource for increasing confidence in protein identifications.
  • The PIPER methodology offers a significant improvement in proteomic data analysis accuracy.
  • Incorporating PIPER into proteomic workflows is recommended for studies collecting both expression and identification data.