Contributions to Lignomics: Stochastic Generation of Oligomeric Lignin Structures for Interpretation of MALDI–FT‐ICR‐MS Results

The lack of standards to identify oligomeric molecules is a challenge for the analysis of complex organic mixtures. High‐resolution mass spectrometry—specifically, Fourier‐transform ion cyclotron resonance mass spectrometry (FT‐ICR MS)—offers new opportunities for analysis of oligomers with the assignment of formulae (CxHyOz) to detected peaks. However, matching a specific structure to a given formula remains a challenge due to the inability of FT‐ICR MS to distinguish between isomers. Additional separation techniques and other analyses (e.g., NMR spectroscopy) coupled with comparison of results to those from pure compounds is one route for assignment of MS peaks. Unfortunately, this strategy may be impractical for complete analysis of complex, heterogeneous samples. In this study we use computational stochastic generation of lignin oligomers to generate a molecular library for supporting the assignment of potential candidate structures to compounds detected during FT‐ICR MS analysis. This approach may also be feasible for other macromolecules beyond lignin. Fragmentation brought to light: High resolution mass spectrometry (Fourier‐transform ion cyclotron resonance mass spectrometry, FT‐ICR MS) is used to characterize milled wood lignins along with other experimental techniques. The structure is also simulated following a stochastic approach, which shows excellent agreement with quantitative experimental results. Coupling this type of structure simulation with FT‐ICR MS shows promise for application to other types of macromolecules.