Issue 6, 2018

Improved mass spectrometric detection of acidic peptides by variations in the functional group pKa values of reverse micelle extraction agents

Abstract

Polymeric reverse micelles can be used to selectively extract peptides from complex mixtures via a two-phase extraction approach. In previous work, we have shown that the charge polarity of the hydrophilic functional group that is in the interior of the reverse micelle dictates the extraction selectivity. To investigate how the extraction is influenced by the inherent pKa of the functional group, we designed and tested a series of polymeric reverse micelles with variations in the hydrophilic functional group. From this series of polymers, we find that the extraction capability of the reverse micelles in an apolar phase is directly related to the aqueous phase pKa of the interior functional group, suggesting that the functional groups maintain their inherent chemistry even in the confined environment of the reverse micelle interior. Because these functional groups maintain their inherent pKa in the reverse micelle interior, they provide predictable extraction selectivity upon changes in aqueous phase pH. We exploit this finding to demonstrate that sulfonate-containing polymers can be used to remove basic peptides from complex mixtures, thereby allowing the improved detection of acidic peptides. Using these new materials, we also demonstrate a new means of isoelectric point (pI) bracketing that allows the mass spectrometric detection of peptides with a defined and narrow range of pI values.

Graphical abstract: Improved mass spectrometric detection of acidic peptides by variations in the functional group pKa values of reverse micelle extraction agents

Supplementary files

Article information

Article type
Paper
Submitted
27 Dec 2017
Accepted
14 Feb 2018
First published
15 Feb 2018

Analyst, 2018,143, 1434-1443

Improved mass spectrometric detection of acidic peptides by variations in the functional group pKa values of reverse micelle extraction agents

B. Zhao, M. A. C. Serrano, M. Wang, T. Liu, M. R. Gordon, S. Thayumanavan and R. W. Vachet, Analyst, 2018, 143, 1434 DOI: 10.1039/C7AN02094E

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