学術雑誌論文

学術雑誌論文

Chemistry Letters. 2024, 53(6), p. upae087

Developing a design guideline of boronic acid derivatives to scavenge targeted sugars in the formose reaction products using DFT-based machine learning

Chemical Society of Japan

英語

2024-06-01

https://doi.org/10.1093/chemle/upae087

This is a pre-copyedited, author-produced version of an article accepted for publication in Chemistry Letters following peer review. The version of record Ishihara N., Chikatani G., Nishijima H., et al. Developing a design guideline of boronic acid derivatives to scavenge targeted sugars in the formose reaction products using DFT-based machine learning. Chemistry Letters 53, upae087 (2024) is available online at: https://doi.org/10.1093/chemle/upae087.

Formose reaction facilitates the synthesis of sugars from formaldehyde, 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 nontarget ones via machine learning informed by density functional theory calculations.

97753

Developing a design guideline of boronic acid derivatives to scavenge targeted sugars in the formose reaction products using DFT-based machine learning

Chemical Society of Japan

英語

2024-06-01

Chemistry Letters

53

6

upae087

https://doi.org/10.1093/chemle/upae087

https://hdl.handle.net/11094/97753