Inequality relations for NMR-based polymer homoblock analysis and extended application: Reanalysis of historical data on alginates, chitosans, homogalacturonans, and galactomannans.

Autor: Xing X; Lethbridge Research and Development Centre, Agriculture and Agri-Food Canada, 5403 1st Avenue South, Lethbridge, Alberta T1J 4B1, Canada. Electronic address: xiaohui.xing@agr.gc.ca., Xing K; Department of Mechanical Engineering, École de technologie Supérieure, 1100 Notre-Dame Street West, Montreal, Quebec H3C 1K3, Canada. Electronic address: kanglin.xing.1@ens.etsmtl.ca., Hsieh YSY; Division of Glycoscience, Department of Chemistry, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, AlbaNova University Centre, Stockholm SE10691, Sweden; School of Pharmacy, College of Pharmacy, Taipei Medical University, 250 Wuxing Street, Taipei 11031, Taiwan. Electronic address: yvhsieh@kth.se., Abbott DW; Lethbridge Research and Development Centre, Agriculture and Agri-Food Canada, 5403 1st Avenue South, Lethbridge, Alberta T1J 4B1, Canada. Electronic address: wade.abbott@agr.gc.ca.
Jazyk: angličtina
Zdroj: Carbohydrate research [Carbohydr Res] 2024 Aug; Vol. 542, pp. 109189. Date of Electronic Publication: 2024 Jun 11.
DOI: 10.1016/j.carres.2024.109189
Abstrakt: There has been a long-standing bottleneck in the quantitative analysis of the frequencies of homoblock polyads beyond triads using 1 H and 13 C NMR for linear polysaccharides, primarily because monosaccharides within a long homoblock share similar chemical environments due to identical neighboring units, resulting in indistinct NMR peaks. In this study, through rigorous mathematical induction, inequality relations were established that enabled the calculation of frequency ranges of homoblock polyads from historically reported NMR-derived frequency values of diads and/or triads of alginates, chitosans, homogalacturonans, and galactomannans. The calculated homoblock frequency ranges were then applied to evaluate three chain growth statistical models, including the Bernoulli chain, first-order Markov chain, and second-order Markov chain, for predicting homoblock frequencies in these polysaccharides. Furthermore, based on the mathematically derived inequality relations, a novel 2D array was constructed, enabling the graphical visualization of homoblock features in polysaccharides. It was demonstrated, as a proof of concept, that the novel 2D array, along with a 1D code generated from it, could serve as an effective feature engineering tool for polymer classification using machine learning algorithms.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Crown Copyright © 2024. Published by Elsevier Ltd. All rights reserved.)
Databáze: MEDLINE
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