Submitted to: Magnetic Resonance in Chemistry
Publication Type: Peer reviewed journal
Publication Acceptance Date: 10/29/1995
Publication Date: N/A
Citation: Interpretive Summary: Lignin is a rather complex polymer in plant cell walls that is composed of known units linked together in a huge variety of ways. It is responsible for, among other things, the inability of cows to digest a significant portion of plants. One way we can get considerable information about the chemical structure of lignin is to run NMR spectra. But one-dimensional spectra are extremely broad and difficult to interpret. By acquiring two-dimensional spectra, an amazing amount of detail is revealed. In proton NMR, where you obtain information about all the hydrogen atoms in a molecule, this paper shows that good model compounds [smaller compounds that we are able to make that 'look like' structures in the large and complex lignin polymer] provide data that can be used to assign those structures in lignin. So, by taking a two-dimensional lignin spectrum and overlaying (on a computer) the spectrum from good model compounds, we can identify structures in the lignin polymer. Although we are essentially demonstrating a method here, we found structures that had not previously been identified in lignin NMR spectra. This structural information helps us in understanding the limits to plant digestibility.
Technical Abstract: The validity of using model compound data to facilitate the interpretation of solution-state two-dimensional TOCSY spectra of soluble wood lignins is demonstrated. The correspondence between model data and lignin correlations was such that it was possible to match the structure and stereochemistry of model compounds to structures present in the lignins by mapping model compound proton chemical shift data to the cross-peaks observed in the TOCSY spectra. For systematic comparisons of model data and lignin correlations, an XY scatter plot of model compound side-chain data was generated and then overlaid on the lignin TOCSY spectra. As well as providing an accurate way of comparing model compound data with lignin correlations, this technique enabled the elucidation of some previously unassigned correlations. In situations where not all possible combinations of model compound side-chain stereochemistry and aromatic ring substitution nwere available, it was possible to generate internally consistent side-chain data from substituent effects. This enabled the prediction of the mode of attachment of certain interunit structures in the lignins.