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Anal Chem. 2018 Jun 5;90(11):6594-6600. doi: 10.1021/acs.analchem.8b00365. Epub 2018 May 15.

Identification of Poly(ethylene glycol) and Poly(ethylene glycol)-Based Detergents Using Peptide Search Engines.

Author information

1
Institute for Biochemistry and Molecular Biology , University of Bonn , 53115 Bonn , Germany.

Abstract

Poly(ethylene glycol) (PEG) is one of the most common polymer contaminations in mass spectrometry (MS) samples. At present, the detection of PEG and other polymers relies largely on manual inspection of raw data, which is laborious and frequently difficult due to sample complexity and retention characteristics of polymer species in reversed-phase chromatography. We developed a new strategy for the automated identification of PEG molecules from tandem mass spectrometry (MS/MS) data using protein identification algorithms in combination with a database containing "PEG-proteins". Through definition of variable modifications, we extend the approach for the identification of commonly used PEG-based detergents. We exemplify the identification of different types of polymers by static nanoelectrospray tandem mass spectrometry (nanoESI-MS/MS) analysis of pure detergent solutions and data analysis using Mascot. Analysis of liquid chromatography-tandem mass spectrometry (LC-MS/MS) runs of a PEG-contaminated sample by Mascot identified 806 PEG spectra originating from four PEG species using a defined set of modifications covering PEG and common PEG-based detergents. Further characterization of the sample for unidentified PEG species using error-tolerant and mass-tolerant searches resulted in identification of 3409 and 3187 PEG-related MS/MS spectra, respectively. We further demonstrate the applicability of the strategy for Protein Pilot and MaxQuant.

PMID:
29726681
DOI:
10.1021/acs.analchem.8b00365
[Indexed for MEDLINE]

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