Predicting Ion Mobility-Mass Spectrometry trends of polymers using the concept of apparent densities.

Abstract

Ion Mobility (IM) coupled to Mass Spectrometry (MS) has been used for several decades, bringing a fast separation dimension to the MS detection. IM-MS is a convenient tool for structural elucidation. The folding of macromolecules is often assessed with the support of computational chemistry. However, this strategy is strongly dependent on computational initial guesses. Here, we propose the analysis of the Collision Cross-Section (CCS) trends of synthetic homopolymers based on a fitting method which does not rely on computational chemistry a prioris of the three-dimensional structures. The CCS trends were evaluated as a function of the polymer chain length and the charge state. This method is also applicable to mobility trends. It leads to two parameters containing all information available through IM(-MS) measurements. One parameter can be interpreted as an apparent density. The second parameter is related to the shape of the ions and leads us to introduce the concept of trends with constant apparent density. Based on the two fitting parameters, a method for IM trend predictions is elaborated. Experimental deviations from the predictions facilitate detecting structural rearrangements and three-dimensional structure differences of the cationized polymer ions. This leads for instance to an easy identification and prediction of the presence of different polymer topologies in complex polymer mixtures. The classification of predicted trends could as well allow for software-assisted data processing. Finally, we suggest the link between the CCS trends of homopolymers and those obtained from (monodisperse) biomolecules to interpret potential folding differences during IM-MS studies.