Faleva Anna V, Grishanovich Ilya A, Ul'yanovskii Nikolay V, Kosyakov Dmitry S
Laboratory of Natural Compounds Chemistry and Bioanalytics, Core Facility Center "Arktika", M.V. Lomonosov Northern (Arctic) Federal University, Northern Dvina Emb. 17, 163002 Arkhangelsk, Russia.
Int J Mol Sci. 2023 Aug 3;24(15):12403. doi: 10.3390/ijms241512403.
Lignin is considered a promising renewable source of valuable chemical compounds and a feedstock for the production of various materials. Its suitability for certain directions of processing is determined by the chemical structure of its macromolecules. Its formation depends on botanical origin, isolation procedure and other factors. Due to the complexity of the chemical composition, revealing the structural differences between lignins of various origins is a challenging task and requires the use of the most informative methods for obtaining and processing data. In the present study, a combination of two-dimensional nuclear magnetic resonance (2D NMR) spectroscopy and multivariate analysis of heteronuclear single quantum coherence (HSQC) spectra is proposed. Principal component analysis and hierarchical cluster analysis techniques demonstrated the possibility to effectively classify lignins at the level of belonging to classes and families of plants, and in some cases individual species, with an error rate for data classification of 2.3%. The reverse transformation of loading plots into the corresponding HSQC loading spectra allowed for structural information to be obtained about the latent components of lignins and their structural fragments (biomarkers) responsible for certain differences. As a result of the analysis of 34 coniferous, deciduous, and herbaceous lignins, 10 groups of key substructures were established. In addition to syringyl, guaiacyl, and -hydroxyphenyl monomeric units, they include various terminal substructures: dihydroconiferyl alcohol, balanopholin, cinnamic acids, and tricin. It was shown that, in some cases, the substructures formed during the partial destruction of biopolymer macromolecules also have a significant effect on the classification of lignins of various origins.
木质素被认为是一种有前景的可再生的有价值化合物来源以及用于生产各种材料的原料。其对于特定加工方向的适用性由其大分子的化学结构决定。其形成取决于植物来源、分离程序和其他因素。由于化学成分的复杂性，揭示不同来源木质素之间的结构差异是一项具有挑战性的任务，需要使用最具信息性的方法来获取和处理数据。在本研究中，提出了二维核磁共振（2D NMR）光谱法与异核单量子相干（HSQC）光谱的多变量分析相结合的方法。主成分分析和层次聚类分析技术表明，有可能在属于植物类别和科的层面上，在某些情况下甚至在个别物种层面上有效地对木质素进行分类，数据分类的错误率为2.3%。将载荷图反向转换为相应的HSQC载荷光谱，可以获得有关木质素潜在成分及其负责某些差异的结构片段（生物标志物）的结构信息。通过对34种针叶、阔叶和草本木质素的分析，建立了10组关键子结构。除了紫丁香基、愈创木基和对羟基苯基单体单元外，它们还包括各种末端子结构：二氢松柏醇、巴兰诺酚、肉桂酸和小麦黄素。结果表明，在某些情况下，生物聚合物大分子部分破坏过程中形成的子结构对不同来源木质素的分类也有显著影响。
