High Performance Quantification of Complex High Resolution Polymer Mass Spectra.

Abstract

Modern soft ionization mass spectrometry provides chemical information on various polymers with unparalleled resolution and sensitivity. However, the interpretation of the resulting highly complex mass spectra is hampered by the sheer amount of contributing macromolecular species. For example, state-of-the-art reversible deactivation radical polymerization techniques, which are generally considered to be highly controlled, can still generate tens or even hundreds of species in a narrow mass window. Moreover, the multitude of species typically leads to partially overlapping isotopic patterns, further complicating the data evaluation. Herein, a rapid and powerful three-step methodical approach is introduced that enables the successful identification and quantification of the contributing species. The approach is subsequently implemented in "pyMacroMS", a high performance algorithm that allows for ultrafast processing of high resolution polymer mass spectra with varying complexities. The power of our algorithm is demonstrated on the example of a photochemical atom transfer radical polymerization (photoATRP) of three monomers, ultimately leading to 908 identified species. pyMacroMS is available free of charge under a GNU General Public License v3.0.