基于数据驱动模型筛选高结合性能双酚类环糊精配合物

IF 2.9 2区 化学 Q3 CHEMISTRY, PHYSICAL
Haoren Niu, Qiaoyan Shang, Qingzhu Jia, Qiang Wang, Jin Zhao* and Fangyou Yan*, 
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引用次数: 0

摘要

环糊精独特的空腔结构使其具有良好的结合性能,在化工、制药、材料等领域有着广阔的应用前景。结合能力可以通过取代环糊精上的羟基来调节。通过设计环糊精上的修饰基团,可以获得预期的结合性能。本文提出了一种新的环糊精/客体结构表示方法来辅助环糊精设计的数据驱动模型。通过多次验证验证了模型的性能,交叉验证(Q2)和测试集(R2test)的平方相关系数分别为0.801和0.841。通过所建立的环糊精/双酚配合物的模型和荧光实验,筛选、合成并表征了几种对双酚类具有较强结合能力的环糊精宿主。结果表明,控制平均绝对误差为0.605 M-1,表明数据补充和分子设计是可行的。数据驱动模型可以作为环糊精配合物设计的理论辅助和驱动工具,有可能推动环糊精的工业应用和科学研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Screening Cyclodextrin Complexes for Bisphenols with High Binding Performance Based on the Data-Driven Model

Screening Cyclodextrin Complexes for Bisphenols with High Binding Performance Based on the Data-Driven Model

The distinctive cavity structure of cyclodextrin, which results in binding properties, is credited with its application prospects in chemical, pharmacy, and material fields. The binding capacity can be regulated by substituting the hydroxyl groups on the cyclodextrins. It is possible to acquire anticipated binding properties by designing the modified groups on cyclodextrins. In this article, a data-driven model is proposed with a novel cyclodextrin/guest structure representation method to assist the cyclodextrin design. The model’s performance is verified via several validations, as the squared correlation coefficients for cross-validation (Q2) and test set (R2test) are 0.801 and 0.841, respectively. With the proposed model and fluorescence experiments for cyclodextrin/bisphenol complexes, several cyclodextrin hosts, which have a strong binding capacity for bisphenols, are screened, synthesized, and characterized. The results show a controlled average absolute error of 0.605 M–1, suggesting the feasibility of data supplementation and molecular design. It is believed that the data-driven model can serve as theoretical assistance and a driving tool for the cyclodextrin complexes design, potentially leading to advancements in cyclodextrin’s industrial applications and scientific research.

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来源期刊
CiteScore
5.80
自引率
9.10%
发文量
965
审稿时长
1.6 months
期刊介绍: An essential criterion for acceptance of research articles in the journal is that they provide new physical insight. Please refer to the New Physical Insights virtual issue on what constitutes new physical insight. Manuscripts that are essentially reporting data or applications of data are, in general, not suitable for publication in JPC B.
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