Statistical characterization of therapeutic protein modifications

Tsung Heng Tsai, Zhiqi Hao, Qiuting Hong, Benjamin Moore, Cinzia Stella, Jeffrey H. Zhang, Yan Chen, Michael Kim, Theo Koulis, Gregory A. Ryslik, Erik Verschueren, Fred Jacobson, William E. Haskins, Olga Vitek

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Peptide mapping with liquid chromatography–tandem mass spectrometry (LC-MS/MS) is an important analytical method for characterization of post-translational and chemical modifications in therapeutic proteins. Despite its importance, there is currently no consensus on the statistical analysis of the resulting data. In this manuscript, we distinguish three statistical goals for therapeutic protein characterization: (1) estimation of site occupancy of modifications in one condition, (2) detection of differential site occupancy between conditions, and (3) estimation of combined site occupancy across multiple modification sites. We propose an approach, which addresses these goals in terms of summarizing the quantitative information from the mass spectra, statistical modeling, and model-based analysis of LC-MS/MS data. We illustrate the approach using an LC-MS/MS experiment from an antibody-drug conjugate and its monoclonal antibody intermediate. The performance was compared to a ‘naïve’ data analysis approach, by using computer simulation, evaluation of differential site occupancy in positive and negative controls, and comparisons of estimated site occupancy with orthogonal experimental measurements of N-linked glycoforms and total oxidation. The results demonstrated the importance of replicated studies of protein characterization, and of appropriate statistical modeling, for reproducible, accurate and efficient site occupancy estimation and differential analysis.

Original languageEnglish (US)
Article number7896
JournalScientific reports
Volume7
Issue number1
DOIs
StatePublished - Dec 1 2017

ASJC Scopus subject areas

  • General

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