Analysis of different synthetic homopolymers by the use of a new calculation software for tandem mass spectra

Mass spectrometry of polymers: A tutorial review

Ever since the inception of synthetic polymeric materials in the late 19th century, the number of studies on polymers as well as the complexity of their structures have only increased. The development and commercialization of new polymers with properties fine-tuned for specific technological, environmental, consumer, or biomedical applications requires powerful analytical techniques that permit the in-depth characterization of these materials. One such method with the ability to provide chemical composition and structure information with high sensitivity, selectivity, specificity, and speed is mass spectrometry (MS). This tutorial review presents and exemplifies the various MS techniques available for the elucidation of specific structural features in a synthetic polymer, including compositional complexity, primary structure, architecture, topology, and surface properties. Key to every MS analysis is sample conversion to gas-phase ions. This review describes the fundamentals of the most suitable ionization methods for synthetic materials and provides relevant sample preparation protocols. Most importantly, structural characterizations via one-step as well as hyphenated or multidimensional approaches are introduced and demonstrated with specific applications, including surface sensitive and imaging techniques. The aim of this tutorial review is to illustrate the capabilities of MS for the characterization of large, complex polymers and emphasize its potential as a powerful compositional and structural elucidation tool in polymer chemistry.

MALINTO: A New MALDI Interpretation Tool for Enhanced Peak Assignment and Semiquantitative Studies of Complex Synthetic Polymers

The newly developed MALDI interpretation tool ("MALINTO") allows for the accelerated characterization of complex synthetic polymers via MALDI mass spectrometry. While existing software provides solutions for simple polymers like poly(ethylene glycol), polystyrene, etc., they are limited in their application on polycondensates synthesized from two different kinds of monomers (e.g., diacid and diol in polyesters). In addition to such A₂ + B₂ polycondensates, MALINTO covers branched and even multicyclic polymer systems. Since the MALINTO software works based on input data of monomers/repeating units, end groups, and adducts, it can be applied on polymers whose components are previously known or elucidated. Using these input data, a list with theoretically possible polymer compositions and resulting m/z values is calculated, which is further compared to experimental mass spectrometry data. For optional semiquantitative studies, peak areas are allocated according to their assigned polymer composition to evaluate both comonomer and terminating group ratios. Several tools are implemented to avoid mistakes, for example, during peak assignment. In the present publication, the functions of MALINTO are described in detail and its broad applicability on different linear polymers as well as branched and multicyclic polycondensates is demonstrated. Fellow researchers will benefit from the accelerated peak assignment using the freely available MALINTO software and might be encouraged to explore the potential of MALDI mass spectrometry for (semi)quantitative applications.

Stochasticity of poly(2-oxazoline) oligomer hydrolysis determined by tandem mass spectrometry

Understanding modification of synthetic polymer structures is necessary for their accurate synthesis and potential applications. In this contribution, a series of partially hydrolyzed poly(2-oxazoline) species were produced forming poly[(2-polyoxazoline)-co-(ethylenimine)] (P(EtOx-co-EI)) copolymers; EI being the hydrolyzed product of Ox. Bulk mass spectrometry (MS) measurements accurately measured the EI content. Tandem mass spectrometry analysis of the EI content in the copolymer samples determined the distribution of each monomer within the copolymer and corresponded to a theoretically modelled random distribution. The EI distribution across the polymers was shown to be effected by the choice of terminus, with a permanent hydrolysis event observed at an OH terminus. A neighbouring group effect wasn't observed at the polymer length analysed (approximately 25-mer species), suggesting that previously observed neighbouring group effects require a larger polymer chain. Although clearly useful for random polymer distribution this approach may be applied to many systems containing non-specific modifications to determine if they are directed or random locations across peptides, proteins, polymers, and nucleic acids.

Tandem mass spectrometry can be used to better understand modification sites of synthetic polymer structures providing more complete chemical knowledge which is necessary for their accurate synthesis and potential applications.

Characterization Across a Dispersity: Polymer Mass Spectrometry in the Second Dimension

Due to the natural dispersity that is present in synthetic polymers, an added complexity is always present in the analysis of polymeric species. Tandem mass spectrometry analysis requires the isolation of individual precursors before a fragmentation event to allow the unambiguous characterization of these species and is not viable at certain levels of complexity due to achievable isolation widths. Two-dimensional mass spectrometry (2DMS) fragments ions and correlates fragments with their corresponding precursors without the need for isolation. In this study, 2DMS electron capture dissociation (ECD) fragmentation of a polyoxazoline and polyacrylamide species was carried out, resulting in the analysis of byproducts and individual polymer species without the use of chromatographic techniques. This study shows that 2DMS ECD is a powerful tool for the analysis of polyacrylamide and polyoxazoline species and offers a new dimension in the characterization of polymers.

MSPolyCalc: A web-based App for polymer mass spectrometry data interpretation. The case study of a pharmaceutical excipient

RATIONALE

In contrast to biological polymers, synthetic macromolecules consist of distributions of sizes, chemical compositions, functionalities and eventually architectures. The mass spectrum of a synthetic polymer may exhibit a tremendous number of signals. The availability of suitable IT tools to support interpretation is key.

METHODS

A web-based tool is presented: MSPolyCalc. It offers a set of functionalities, including the calculation of polymer distributions, molecular formulae and a match evaluation for peak assignment based on both mass and spectral accuracy (similarity score). The software was successfully tested with mass spectra exhibiting resolutions ranging from 10,000 to 240,000.

RESULTS

The molecular characterization of a synthetic poly(ethylene glycol)-based excipient was achieved. MSPolyCalc allowed the discrimination of six polymer compositions of variable relative abundance. Secondary ionization adducts with very low intensity consisting of matrix-analyte clusters were also successfully identified.

CONCLUSIONS

MSPolyCalc offers assisted data interpretation to target the needs of polymer chemists. It facilitates structure characterization, ionization adduct identification, and end-group determination together with visual result reporting.

Computational mass spectrometry for small molecules

: The identification of small molecules from mass spectrometry (MS) data remains a major challenge in the interpretation of MS data. This review covers the computational aspects of identifying small molecules, from the identification of a compound searching a reference spectral library, to the structural elucidation of unknowns. In detail, we describe the basic principles and pitfalls of searching mass spectral reference libraries. Determining the molecular formula of the compound can serve as a basis for subsequent structural elucidation; consequently, we cover different methods for molecular formula identification, focussing on isotope pattern analysis. We then discuss automated methods to deal with mass spectra of compounds that are not present in spectral libraries, and provide an insight into de novo analysis of fragmentation spectra using fragmentation trees. In addition, this review shortly covers the reconstruction of metabolic networks using MS data. Finally, we list available software for different steps of the analysis pipeline.