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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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Related Experiment Video

Updated: May 30, 2026

Quantitative Proteomics Workflow using Multiple Reaction Monitoring Based Detection of Proteins from Human Brain Tissue
11:49

Quantitative Proteomics Workflow using Multiple Reaction Monitoring Based Detection of Proteins from Human Brain Tissue

Published on: August 28, 2021

PChopper: high throughput peptide prediction for MRM/SRM transition design.

Vackar Afzal1, Jeffrey T-J Huang, Abdel Atrih

  • 1Translational Medicine Research Collaboration, Dundee, DD1 9SY, UK.

BMC Bioinformatics
|August 16, 2011
PubMed
Summary

PChopper software aids researchers in designing peptide analysis for mass spectrometry. It automates enzyme selection for enzymatic digests, streamlining the process for high-throughput experiments.

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Selected Reaction Monitoring Mass Spectrometry for Absolute Protein Quantification
09:04

Selected Reaction Monitoring Mass Spectrometry for Absolute Protein Quantification

Published on: August 17, 2015

Related Experiment Videos

Last Updated: May 30, 2026

Quantitative Proteomics Workflow using Multiple Reaction Monitoring Based Detection of Proteins from Human Brain Tissue
11:49

Quantitative Proteomics Workflow using Multiple Reaction Monitoring Based Detection of Proteins from Human Brain Tissue

Published on: August 28, 2021

Selected Reaction Monitoring Mass Spectrometry for Absolute Protein Quantification
09:04

Selected Reaction Monitoring Mass Spectrometry for Absolute Protein Quantification

Published on: August 17, 2015

Area of Science:

  • Biochemistry
  • Proteomics
  • Computational Biology

Background:

  • Selective reaction monitoring (SRM) based LC-MS/MS is increasingly used for quantifying phosphorylation stoichiometry.
  • The growing number of quantifiable sites per experiment necessitates computational tools for designing SRM candidates.
  • Manual processes for SRM experiments are time-consuming, highlighting the need for automation.

Purpose of the Study:

  • To develop a computational tool for assisting in the design of SRM candidates for LC-MS/MS experiments.
  • To automate the prediction of peptides from enzymatic protein digests.
  • To facilitate the identification of optimal enzymes for high-throughput peptide analysis.

Main Methods:

  • Developed PChopper, a software tool for predicting peptides from enzymatic digests, including single and combined enzymes.
  • Implemented batch mode simulation for digests and combined information to suggest optimal enzyme combinations.
  • Enabled users to define target peptide characteristics and automatically identify phosphorylation sites.
  • Provided two application endpoints: a web-based graphical tool and an HTTP REST API.

Main Results:

  • PChopper predicts peptides from single or combined enzymatic digests.
  • The software simulates digests in batch mode and suggests optimal enzymes.
  • Users can define target peptide characteristics and identify phosphorylation sites.
  • Offers both a graphical user interface and an API for system interaction.

Conclusions:

  • A service-oriented architecture enabled rapid development of a system for consuming and exposing services.
  • A graphical tool provides an intuitive workflow for scientists.
  • The system facilitates rapid identification of enzymes for parallel peptide production via enzymatic digests in a high-throughput manner.