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Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
Published on: November 15, 2017
Identification and accurate quantification of structurally related peptide impurities in synthetic human C-peptide by
Ming Li1,2, Ralf D Josephs3, Adeline Daireaux1
1Département de Chimie, Bureau International des Poids et Mesures (BIPM), Pavillon de Breteuil, 92312, Sèvres Cedex, France.
Abstract:
Peptides are an increasingly important group of biomarkers and pharmaceuticals. The accurate purity characterization of peptide calibrators is critical for the development of reference measurement systems for laboratory medicine and quality control of pharmaceuticals. The peptides used for these purposes are increasingly produced through peptide synthesis. Various approaches (for example mass balance, amino acid analysis, qNMR, and nitrogen determination) can be applied to accurately value assign the purity of peptide calibrators. However, all purity assessment approaches require a correction for structurally related peptide impurities in order to avoid biases. Liquid chromatography coupled to high resolution mass spectrometry (LC-hrMS) has become the key technique for the identification and accurate quantification of structurally related peptide impurities in intact peptide calibrator materials. In this study, LC-hrMS-based methods were developed and validated in-house for the identification and quantification of structurally related peptide impurities in a synthetic human C-peptide (hCP) material, which served as a study material for an international comparison looking at the competencies of laboratories to perform peptide purity mass fraction assignments. More than 65 impurities were identified, confirmed, and accurately quantified by using LC-hrMS. The total mass fraction of all structurally related peptide impurities in the hCP study material was estimated to be 83.3 mg/g with an associated expanded uncertainty of 3.0 mg/g (k = 2). The calibration hierarchy concept used for the quantification of individual impurities is described in detail. Graphical abstract ᅟ.
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