Automating Middle-Down Mass Spectrometry Analysis for Extensive Antibody Characterization

Workflows and software tools for peptide mapping have been extensively optimized and simplified for widespread use. However, top-down and middle-down workflows, despite offering valuable proteoform information not obtainable by peptide mapping, remain demanding in terms of user expertise as well as instrument setup, data analysis, and result validation. Current software offerings have also not been tailored to address targeted protein characterization workflows, often necessitating multiple software tools to accomplish data analysis. To move toward routine intact protein characterization workflows with a single software tool, an automated platform named Proteoform Studio is introduced here. Proteoform Studio features a complete analysis pipeline, allowing a user to set up instrument runs, modify acquisition methods, rapidly deconvolute data to define intact mass features, search results to identify proteoforms, and obtain the highest quality proteoform characterization through automated aggregation of fragmentation results. Additionally, fragment ion matching settings for signal-to-noise ratio and isotope fit score were identified that produced automated matching results well-aligned with manual validation results, thereby reducing the need for time-consuming manual verification. With Proteoform Studio analysis, >80% sequence coverage of light chain (Lc) and the N-terminal portion of heavy chain (Fd) antibody subunits was achieved in an automated fashion using a middle-down approach. These sequence coverage results utilized aggregation of spectral results from different fragmentation methods to take advantage of complementary fragment ion formation. Overall, introducing software to automate antibody subunit analysis will lower barriers to entry and eliminate data analysis bottlenecks, driving adoption in biopharmaceutical assays and ultimately leading to more precise characterization of therapeutic proteoform landscapes.

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Publication Details

Journal
Analytical Chemistry
Published
2026-04-13
DOI
https://doi.org/10.1021/acs.analchem.5c06408
Primary Topic
Advanced Proteomics Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Automating Middle-Down Mass Spectrometry Analysis for Extensive Antibody Characterization

Jake Kline, Kenneth R. Durbin, Luca Fornelli, Amy Carfagno et al.
Analytical Chemistry
Advanced Proteomics Techniques and Applications
article

Automating Middle-Down Mass Spectrometry Analysis for Extensive Antibody Characterization

Jake Kline, Kenneth R. Durbin, Luca Fornelli, Amy Carfagno, Linda Lieu
article en

Abstract

Workflows and software tools for peptide mapping have been extensively optimized and simplified for widespread use. However, top-down and middle-down workflows, despite offering valuable proteoform information not obtainable by peptide mapping, remain demanding in terms of user expertise as well as instrument setup, data analysis, and result validation. Current software offerings have also not been tailored to address targeted protein characterization workflows, often necessitating multiple software tools to accomplish data analysis. To move toward routine intact protein characterization workflows with a single software tool, an automated platform named Proteoform Studio is introduced here. Proteoform Studio features a complete analysis pipeline, allowing a user to set up instrument runs, modify acquisition methods, rapidly deconvolute data to define intact mass features, search results to identify proteoforms, and obtain the highest quality proteoform characterization through automated aggregation of fragmentation results. Additionally, fragment ion matching settings for signal-to-noise ratio and isotope fit score were identified that produced automated matching results well-aligned with manual validation results, thereby reducing the need for time-consuming manual verification. With Proteoform Studio analysis, >80% sequence coverage of light chain (Lc) and the N-terminal portion of heavy chain (Fd) antibody subunits was achieved in an automated fashion using a middle-down approach. These sequence coverage results utilized aggregation of spectral results from different fragmentation methods to take advantage of complementary fragment ion formation. Overall, introducing software to automate antibody subunit analysis will lower barriers to entry and eliminate data analysis bottlenecks, driving adoption in biopharmaceutical assays and ultimately leading to more precise characterization of therapeutic proteoform landscapes.

Analytical ChemistryVol. 98(16)
University of Oklahoma (US)
National Institute of General Medical Sciences
Openalex Percentile: Top 22%
Advanced Proteomics Techniques and Applications
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