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完成单糖至四糖的 1H 和 13C NMR 化学位移赋值,为使用计算机程序 CASPER 预测寡糖和多糖的 NMR 化学位移提供基础。

Complete H and C NMR chemical shift assignments of mono-to tetrasaccharides as basis for NMR chemical shift predictions of oligo- and polysaccharides using the computer program CASPER.

机构信息

Department of Organic Chemistry, Arrhenius Laboratory, Stockholm University, S-106 91 Stockholm, Sweden.

Department of Organic Chemistry, Arrhenius Laboratory, Stockholm University, S-106 91 Stockholm, Sweden.

出版信息

Carbohydr Res. 2022 Mar;513:108528. doi: 10.1016/j.carres.2022.108528. Epub 2022 Feb 25.

Abstract

Carbohydrate structure can be elucidated or confirmed by using NMR spectroscopy as the prime technique. Prediction of H and C NMR chemical shifts by computational approaches makes this assignment process more efficient and the program CASPER can perform this task rapidly. It does so by relying on chemical shift data of mono-, di-, and trisaccharides. In order to improve accuracy and quality of these predictions we have assigned H and C NMR chemical shifts of 30 monosaccharides, 17 disaccharides, 10 trisaccharides and one tetrasaccharide; in total 58 compounds. Due to different rotamers, ring forms, α- and β-anomeric forms and pD conditions this resulted in 74 H and C NMR chemical shift data sets, all of which were refined using total line-shape analysis for the H resonances in order to obtain accurate chemical shifts. Subsequent NMR chemical shift predictions for three sialic acid-containing oligosaccharides, viz., GD1a, a disialyl-LNnT hexasaccharide and a polysialic acid-lactose decasaccharide, and NMR-based structural elucidations of two O-antigen polysaccharides from E. coli O174 were performed by the CASPER program (http://www.casper.organ.su.se/casper/) resulting in very good to excellent agreement between experimental and predicted data thereby demonstrating its utility for carbohydrate compounds that have been chemically or enzymatically synthesized, structurally modified or isolated from nature.

摘要

碳水化合物结构可以通过 NMR 光谱学作为主要技术来阐明或确认。通过计算方法预测 H 和 C NMR 化学位移,使这个分配过程更加高效,程序 CASPER 可以快速完成这项任务。它通过依赖于单糖、二糖和三糖的化学位移数据来实现。为了提高这些预测的准确性和质量,我们已经分配了 30 个单糖、17 个二糖、10 个三糖和 1 个四糖的 H 和 C NMR 化学位移;总共 58 种化合物。由于不同的构象、环形式、α-和β-端基形式和 pD 条件,这导致了 74 个 H 和 C NMR 化学位移数据集,所有这些数据集都使用总线形状分析进行了 H 共振的精细处理,以获得准确的化学位移。随后,通过 CASPER 程序(http://www.casper.organ.su.se/casper/)对三种含有唾液酸的寡糖,即 GD1a、二唾液酰-LNnT 六糖和多唾液酸-乳糖十糖,以及两种来自大肠杆菌 O174 的 O-抗原多糖的基于 NMR 的结构阐明进行了 NMR 化学位移预测,实验和预测数据之间的一致性非常好,甚至是极好的,从而证明了它在化学或酶合成、结构修饰或从自然界中分离的碳水化合物化合物中的实用性。

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