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Automated Quantification of Hydroxyl Reactivities: Prediction of Glycosylation Reactions
Author(s) -
Chang ChunWei,
Lin MeiHuei,
Chan ChiehKai,
Su KuanYu,
Wu ChiaHui,
Lo WeiChih,
Lam Sarah,
Cheng YuTing,
Liao PinHsuan,
Wong ChiHuey,
Wang ChengChung
Publication year - 2021
Publication title -
angewandte chemie international edition
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.831
H-Index - 550
eISSN - 1521-3773
pISSN - 1433-7851
DOI - 10.1002/anie.202013909
Subject(s) - glycosylation , chemistry , aka , nucleophile , reactivity (psychology) , steric effects , combinatorial chemistry , stereoselectivity , yield (engineering) , computer science , organic chemistry , catalysis , biochemistry , materials science , alternative medicine , pathology , library science , metallurgy , medicine
The stereoselectivity and yield in glycosylation reactions are paramount but unpredictable. We have developed a database of acceptor nucleophilic constants (Aka) to quantify the nucleophilicity of hydroxyl groups in glycosylation influenced by the steric, electronic and structural effects, providing a connection between experiments and computer algorithms. The subtle reactivity differences among the hydroxyl groups on various carbohydrate molecules can be defined by Aka, which is easily accessible by a simple and convenient automation system to assure high reproducibility and accuracy. A diverse range of glycosylation donors and acceptors with well‐defined reactivity and promoters were organized and processed by the designed software program “GlycoComputer” for prediction of glycosylation reactions without involving sophisticated computational processing. The importance of Aka was further verified by random forest algorithm, and the applicability was tested by the synthesis of a Lewis A skeleton to show that the stereoselectivity and yield can be accurately estimated.