Novel chemical tools to elucidate carbohydrate chemistry

复合碳水化合物是最通用的生物分子之一，在几乎每一个生命系统中都扮演着多样化和重要的角色。此外，作为生物过程中的关键介质，它们是开发拟糖药物和疫苗的基础。由于缺乏扩增技术和表达系统，化学合成提供了获得纯聚糖的最有效方法。由于WG Seeberger开发的自动聚糖组装技术，复杂而耗时的合成大大加快了速度，提供了直接获取各种聚糖的途径。然而，糖苷键形成的详细机制-糖合成中的基本反应-仍然知之甚少。对这些机理丰富、结构复杂的连锁反应的研究存在两个限制：对每一个新的耦合进行可控的、可重复的优化，以及快速的、数据丰富的分析。WG Seeberger和WG Pagel的联合项目旨在更好地了解糖苷键形成的潜在机制。WG Seeberger将利用可控微反应器合成平台来优化实验参数和条件。由此产生的中间体、产物和副产物的身份和比例的变化将随后用离子迁移-质谱法在WG Pagel中进行探测。对由此产生的综合数据集的系统分析将扩展有关聚糖中间体的知识，并为糖基化反应的预测模型的发展奠定基础。

Complex carbohydrates are among the most versatile biomolecules, playing diverse and essential roles in virtually every living system. Additionally, as key mediators in biological processes, they form the basis for the development of glycomimetic drugs and vaccines.Due to the absence of amplification techniques and expression systems, chemical synthesis offers the most efficient way to access glycans in pure form. The complex and time consuming syntheses have been significantly accelerated by the development of automated glycan assembly by WG Seeberger, providing straightforward access to a wide variety of glycans. However, the detailed mechanism of the glycosidic bond formation – the elementary reaction in glycan synthesis – remains poorly understood. Two limitations exist in the study of these mechanistically rich and structurally complex linkage reactions: the controlled, reproducible optimization of each new coupling, and rapid, data-rich analytics.The joint project of WG Seeberger and WG Pagel aims at the better understanding of the underlying mechanisms of glycosidic bond formation. WG Seeberger will utilize the controlled microreactor synthesis platform to optimize experimental parameters and conditions. The resulting changes in identity and proportion of intermediates, products and byproducts will afterwards be probed by ion mobility-mass spectrometry in WG Pagel. The systematic analysis of the resulting comprehensive dataset will expand the knowledge about glycan intermediates and form the basis for their development of predictive models for glycosylation reactions.