Abstract

Phenolic compounds (PCs) could be applied to reduce reactive oxygen species (ROS) levels, and are used to prevent and treat diseases related to oxidative stress. QSAR study was applied to elucidate the relationship between the molecular descriptors and physicochemical properties of polyphenol analogues and their DPPH radical scavenging capability, to guide the design and discovery of highly-potent antioxidant substances more efficiently. PubMed database was used to collect 99 PCs with antioxidant activity, whereas, 105 negative PCs were found in ChEMBL database; their molecular descriptors were generated with Python's Rdkit package. While the molecular descriptors significantly related to the antioxidant activity of PCs were filtered by t-test. The prediction QSAR model was then established by discriminant analysis, and the obtained model was verified by the back-substitution and Leave-One-Out cross-validation methods along with heat map. It was revealed that the anti-DPPH radical activity of PCs was correlated with the drug-likeness and molecular fingerprints, physicochemical, topological, constitutional and electronic property. The established QSAR model could explicitly predict the antioxidant activity of polyphenols, thus were applicable to evaluate the potential of candidates as antioxidants.

Details

Title
QSAR study of phenolic compounds and their anti-DPPH radical activity by discriminant analysis
Author
Ang, Lu 1 ; Shi-meng, Yuan 2 ; Xiao Huai 3 ; Da-song, Yang 2 ; Zhi-qiong, Ai 1 ; Qi-Yan, Li 4 ; Zhao, Yu 3 ; Zhuang-zhi, Chen 5 ; Wu Xiu-mei 6 

 Dali University, School of Public Health, Dali, People’s Republic of China (GRID:grid.440682.c) (ISNI:0000 0001 1866 919X) 
 Dali University, Yunnan Provincial Key Laboratory of Entomological Biopharmaceutical R&D, Dali, People’s Republic of China (GRID:grid.440682.c) (ISNI:0000 0001 1866 919X) 
 Dali University, Yunnan Provincial Key Laboratory of Entomological Biopharmaceutical R&D, Dali, People’s Republic of China (GRID:grid.440682.c) (ISNI:0000 0001 1866 919X); Dali University, Yunnan Provincial 2011 Collaborative Innovation Center for Entomoceutics, Dali, People’s Republic of China (GRID:grid.440682.c) (ISNI:0000 0001 1866 919X) 
 Affiliated Hospital of Kunming University of Science and Technology, The First People’s Hospital of Yunnan Province, Kunming, People’s Republic of China (GRID:grid.218292.2) (ISNI:0000 0000 8571 108X); Dali University, Yunnan Provincial 2011 Collaborative Innovation Center for Entomoceutics, Dali, People’s Republic of China (GRID:grid.440682.c) (ISNI:0000 0001 1866 919X) 
 PharmaBlock Sciences (Nanjing), Inc., Nanjing, People’s Republic of China (GRID:grid.440682.c) 
 Dali University, School of Public Health, Dali, People’s Republic of China (GRID:grid.440682.c) (ISNI:0000 0001 1866 919X); Dali University, Yunnan Provincial Key Laboratory of Entomological Biopharmaceutical R&D, Dali, People’s Republic of China (GRID:grid.440682.c) (ISNI:0000 0001 1866 919X) 
Publication year
2022
Publication date
2022
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2663154774
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.