Prediction and design of cyclodextrin inclusion complexes formation via machine learning-based strategies-Reference-Cited by-同舟云学术

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Prediction and design of cyclodextrin inclusion complexes formation via machine learning-based strategies

Published:2022-11 Issue: Volume:261 Page:117946
ISSN:0009-2509
Container-title:Chemical Engineering Science
language:en
Short-container-title:Chemical Engineering Science

Author:

Ma Yiming,Niu Yue,Yang Huaiyu^ORCID,Dai Jiayu,Lin Jiawei,Wang Huiqi,Wu Songgu,Yin Qiuxiang,Zhou Ling,Gong Junbo

Funder

National Natural Science Foundation of China

China Scholarship Council

Natural Science Foundation of Tianjin Municipal Science and Technology Commission

Publisher

Elsevier BV

Subject

Applied Mathematics,Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry

Reference50 articles.

1. Effect of beta-cyclodextrin and hydroxypropyl beta-cyclodextrin complexation on physicochemical properties and antimicrobial activity of cefdinir;Aleem;J. Pharm. Biomed. Anal.,2008

2. A systematic review on nanoencapsulation of food bioactive ingredients and nutraceuticals by various nanocarriers;Assadpour;Crit. Rev. Food Sci. Nutr.,2019

3. Prediction of Orthosteric and Allosteric Regulations on Cannabinoid Receptors Using Supervised Machine Learning Classifiers;Bian;Mol Pharm,2019

4. Experimental Binding Energies in Supramolecular Complexes;Biedermann;Chem Rev,2016

5. Cyclodextrins as pharmaceutical solubilizers;Brewster;Adv Drug Deliv Rev,2007

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4. QSPR models for complexation performance of α-cyclodextrin and β-cyclodextrin complexes by norm indices;Chemical Engineering Science;2024-02

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