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  3. Automating Middle-down Mass Spectrometry Analysis For Extensive Antibody Characterization.
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  3. Automating Middle-down Mass Spectrometry Analysis For Extensive Antibody Characterization.

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Automating Middle-Down Mass Spectrometry Analysis for Extensive Antibody Characterization.

Amy K Carfagno1, Linda B Lieu2, Jake T Kline1

  • 1School of Biological Sciences, University of Oklahoma, Norman, Oklahoma 73019, United States.

Analytical Chemistry
|April 13, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

Proteoform Studio simplifies intact protein analysis by automating data processing for top-down and middle-down workflows. This new software enables routine proteoform characterization, reducing manual effort and improving antibody subunit analysis.

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Area of Science:

  • Proteomics
  • Biopharmaceutical Analysis
  • Mass Spectrometry

Background:

  • Peptide mapping is widely used but lacks proteoform information.
  • Top-down and middle-down workflows offer deeper proteoform insights but are complex.
  • Existing software often requires multiple tools for targeted protein characterization.

Purpose of the Study:

  • To introduce Proteoform Studio, an automated platform for routine intact protein characterization.
  • To streamline top-down and middle-down mass spectrometry workflows.
  • To reduce user expertise and data analysis bottlenecks in proteoform analysis.

Main Methods:

  • Development of Proteoform Studio, an integrated software platform.
  • Automated data processing including instrument run setup, method modification, data deconvolution, and proteoform searching.
  • Automated aggregation of fragmentation results for enhanced characterization.
  • Optimization of fragment ion matching parameters (signal-to-noise ratio, isotope fit score).

    • Main Results:

    • >80% sequence coverage of antibody light chain (Lc) and N-terminal heavy chain (Fd) subunits achieved via automated middle-down analysis.
    • Automated matching results aligned well with manual validation, reducing manual verification needs.
    • Aggregation of spectral results from complementary fragmentation methods improved sequence coverage.

    Conclusions:

    • Proteoform Studio enables routine, automated intact protein characterization with a single software tool.
    • The software lowers barriers to entry and eliminates data analysis bottlenecks for biopharmaceutical assays.
    • Automated analysis drives adoption and enables more precise characterization of therapeutic proteoform landscapes.