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Quantitative Proteomics Using Reductive Dimethylation for Stable Isotope Labeling
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Optimization of reversed-phase chromatography methods for peptide analytics.

Rushd Khalaf1, Daniel Baur1, David Pfister1

  • 1Institute for Chemical and Bioengineering, ETH Zurich, Zurich 8093, ZH, Switzerland.

Journal of Chromatography. A
|December 2, 2015
PubMed
Summary

This study introduces a model-based tool for optimizing analytical reversed-phase liquid chromatography conditions. It enhances peptide separation and quality control in peptide production and mapping.

Keywords:
Mathematical modelModel-based designPeptide analyticsPeptide mappingReversed phaseVan’t Hoff equation

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Area of Science:

  • Analytical Chemistry
  • Chromatography Science

Background:

  • Peptide solution analysis is crucial for quality control and peptide mapping.
  • Analytical reversed-phase liquid chromatography (RPLC) is a traditional method for peptide analysis.

Purpose of the Study:

  • To develop a model-based tool for optimizing RPLC conditions.
  • To achieve clear, efficient, and robust analytical method design for peptide mixtures.

Main Methods:

  • A model integrating Van't Hoff equation, linear solvent strength correlation, and mass balance equation for peptide retention in gradient RPLC.
  • Application of the model to optimize separation of components in peptide mixtures.

Main Results:

  • Successful development of a model-based tool for optimizing RPLC methods.
  • Demonstrated application in designing analytical RPLC methods for five distinct peptide mixtures.

Conclusions:

  • The model-based tool provides an efficient and robust approach for optimizing peptide separation in RPLC.
  • This method aids in the design of analytical RPLC for quality control and peptide mapping.