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Covalent Labeling Denaturation Mass Spectrometry for Sensitive Localized Higher Order Structure Comparisons.

James A Madsen1, Yan Yin1, Jing Qiao1

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|January 12, 2016
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Summary
This summary is machine-generated.

This study introduces a novel mass spectrometry method using high levels of isobaric labels to detect subtle protein higher order structure (HOS) differences. This technique enhances sensitivity for identifying localized structural variations in biopharmaceuticals.

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Area of Science:

  • Biochemistry
  • Analytical Chemistry
  • Protein Science

Background:

  • Protein higher order structure (HOS) is crucial for protein function and a key attribute in biopharmaceutical development.
  • Covalent labeling coupled with mass spectrometry is used to assess localized protein HOS.
  • Conventional methods often use minimal labeling to preserve protein structure.

Purpose of the Study:

  • To present a new method using high concentrations of isobaric labels to detect localized protein HOS differences.
  • To enhance sensitivity and resolution for identifying structural variations in biological products.
  • To demonstrate the method's ability to quantify other product attributes.

Main Methods:

  • Utilizing high amounts of isobaric labels, sufficient to induce denaturation, for enhanced HOS analysis.
  • Employing liquid chromatography-tandem mass spectrometry (LC-MS/MS) for data acquisition.
  • Implementing automated data analysis for efficient processing.

Main Results:

  • The method detected localized HOS differences at levels as low as 2.5-5% of the molecular population.
  • Demonstrated higher sensitivity compared to circular dichroism and nuclear magnetic resonance spectroscopy fingerprinting for specific HOS variations.
  • Showed comparable sensitivity to differential scanning calorimetry for detecting HOS differences.
  • Successfully quantified post-translational modifications and site-specific glycosylation in a single LC-MS/MS run.

Conclusions:

  • High-labeling mass spectrometry is a highly discriminative technique for detecting subtle protein HOS variations.
  • This workflow offers a sensitive and comprehensive approach for biopharmaceutical characterization.
  • The method is applicable to large, multiply glycosylated therapeutic proteins under various stress conditions.