Developing a Design Guideline of Boronic Acid Derivatives to Scavenge Targeted Sugars in the Formose Reaction Products using DFT-based Machine Learning
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Abstract
Formose reaction facilitates the synthesis of sugars from HCHO, yet the valuable sugars constitute only a small portion of the total products. This necessitates the need for a chemical scavenger capable of selectively capturing only valuable sugars. With over 600,000 potential combinations of boronic acid-based scavengers available, pursuing a deductive search approach is unfeasible. This study aims to derive guidelines for designing scavengers that readily bind with target sugars while avoiding non-target ones, via machine learning informed by DFT calculations.
期刊介绍：
Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance.
Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
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