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MALINTO: A New MALDI Interpretation Tool for Enhanced Peak Assignment and Semiquantitative Studies of Complex Synthetic Polymers
[Image: see text] 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 li...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9896554/ https://www.ncbi.nlm.nih.gov/pubmed/36599090 http://dx.doi.org/10.1021/jasms.2c00311 |
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author | Saller, Klara M. Pernusch, Daniel C. Schwarzinger, Clemens |
author_facet | Saller, Klara M. Pernusch, Daniel C. Schwarzinger, Clemens |
author_sort | Saller, Klara M. |
collection | PubMed |
description | [Image: see text] 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 A(2) + B(2) 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. |
format | Online Article Text |
id | pubmed-9896554 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-98965542023-02-04 MALINTO: A New MALDI Interpretation Tool for Enhanced Peak Assignment and Semiquantitative Studies of Complex Synthetic Polymers Saller, Klara M. Pernusch, Daniel C. Schwarzinger, Clemens J Am Soc Mass Spectrom [Image: see text] 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 A(2) + B(2) 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. American Chemical Society 2023-01-04 /pmc/articles/PMC9896554/ /pubmed/36599090 http://dx.doi.org/10.1021/jasms.2c00311 Text en © 2023 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by/4.0/Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Saller, Klara M. Pernusch, Daniel C. Schwarzinger, Clemens MALINTO: A New MALDI Interpretation Tool for Enhanced Peak Assignment and Semiquantitative Studies of Complex Synthetic Polymers |
title | MALINTO: A New MALDI Interpretation
Tool for Enhanced Peak Assignment and Semiquantitative Studies of
Complex Synthetic Polymers |
title_full | MALINTO: A New MALDI Interpretation
Tool for Enhanced Peak Assignment and Semiquantitative Studies of
Complex Synthetic Polymers |
title_fullStr | MALINTO: A New MALDI Interpretation
Tool for Enhanced Peak Assignment and Semiquantitative Studies of
Complex Synthetic Polymers |
title_full_unstemmed | MALINTO: A New MALDI Interpretation
Tool for Enhanced Peak Assignment and Semiquantitative Studies of
Complex Synthetic Polymers |
title_short | MALINTO: A New MALDI Interpretation
Tool for Enhanced Peak Assignment and Semiquantitative Studies of
Complex Synthetic Polymers |
title_sort | malinto: a new maldi interpretation
tool for enhanced peak assignment and semiquantitative studies of
complex synthetic polymers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9896554/ https://www.ncbi.nlm.nih.gov/pubmed/36599090 http://dx.doi.org/10.1021/jasms.2c00311 |
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