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Updated: May 28, 2026

Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools
07:01

Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools

Published on: August 19, 2025

Improving proteomics mass accuracy by dynamic offline lock mass.

Ying Zhang1, Zhihui Wen, Michael P Washburn

  • 1Stowers Institute for Medical Research, Kansas City, Missouri 64110, United States.

Analytical Chemistry
|November 3, 2011
PubMed
Summary

Dynamic offline lock mass (DOLM) improves mass accuracy in mass spectrometry by dynamically selecting background ions for recalibration. This method enhances data quality for proteomics research, achieving precise mass error below 1 ppm.

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Last Updated: May 28, 2026

Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools
07:01

Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools

Published on: August 19, 2025

Area of Science:

  • Mass spectrometry
  • Proteomics
  • Analytical chemistry

Background:

  • Low-ppm mass accuracy is crucial for mass spectrometry.
  • Existing lock mass methods struggle with weak and fluctuating background ion intensities.
  • Polydimethylcyclosiloxane ions are common but inconsistent calibrants.

Purpose of the Study:

  • To introduce and evaluate dynamic offline lock mass (DOLM) for improved mass accuracy.
  • To address the limitations of fluctuating background ion intensity in calibration.
  • To enhance data quality for tandem mass spectrometry (MS/MS) analyses.

Main Methods:

  • Implementation of dynamic offline lock mass (DOLM) using MS1 survey spectra.
  • Dynamic selection of strongest background ions for statistical treatment and m/z recalibration.
  • Optimization of mass profile abstraction and calibrant number selection.
  • Assessment using tandem mass spectroscopy (MS/MS) datasets from MudPIT analyses of protein samples.

Main Results:

  • DOLM outperformed external mass calibration and static offline lock mass, especially at low-ppm levels.
  • The dynamic feature adapted to wide variations in calibrant intensities.
  • Achieved an averaged mass error center of 0.03 ± 0.50 ppm for precursor ions.
  • Enabled precursor mass tolerance as low as 1.5 ppm for MS/MS data filtering.

Conclusions:

  • DOLM offers a robust solution for achieving high mass accuracy in mass spectrometry.
  • The method's adaptability to ion intensity fluctuations enhances its reliability.
  • DOLM significantly improves the precision of mass calibration for proteomics applications.