Literature DB >> 15283601

Coumarin tags for improved analysis of peptides by MALDI-TOF MS and MS/MS. 1. Enhancement in MALDI MS signal intensities.

Anna Pashkova1, Eugene Moskovets, Barry L Karger.   

Abstract

The goal of this study was the development of N-terminal tags to improve peptide identification using high-throughput MALDI-TOF MS and MS/MS. The proposed tags, commercially available fluorescent derivatives of coumarin, can be advantageous for peptide analysis in both MS and MS/MS modes. This paper, part 1, will focus on the influence of derivatization on the intensities of MALDI-TOF MS signals of peptides. Labeling peptides with tags containing the coumarin core was found to enhance the intensities of peptide peaks (in some cases over 40-fold) in MALDI-TOF MS using CHCA and 2,5-DHAP matrixes. The signal enhancement was found to be peptide- and matrix-dependent, being the most pronounced for hydrophilic peptides. No correlation was found between the UV absorptivity of the tags at the excitation wavelengths typical for UV-MALDI and the magnitude of the signal enhancement. Interestingly, peptides labeled with Alexa Fluor 350, a coumarin derivative containing a sulfo group (i.e., bearing strong negative charge), showed a 5-15-fold increase in intensity of MALDI MS signal in the positive ion mode, relative to the underivatized peptides, when 2,5-DHAP was used as the matrix. The Alexa Fluor 350 tag yielded a significantly higher signal relative to that for the CAF tag, likely due to the increased hydrophobicity of the coumarin structure. With 2,5-DHB, a decrease of MALDI MS signal was observed for all coumarin-labeled peptides, again relative to the unlabeled species. These findings support the hypothesis that derivatization with coumarin, a relatively hydrophobic structure, improves incorporation of hydrophilic peptides into hydrophobic MALDI matrixes, such as CHCA and 2,5-DHAP.

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Year:  2004        PMID: 15283601     DOI: 10.1021/ac049638+

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  10 in total

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