Mechanism of hepatotoxicity induced by ethanol extract of Dysosma versipellis based on "quantity-weight-evidence" network toxicology.
10.19540/j.cnki.cjcmm.20210914.701
- Author:
Jiao KONG
1
;
Yue TIAN
1
;
Chuan-Xin LIU
2
;
Jian-Mei HUANG
1
Author Information
1. School of Chinese Materia Medica, Beijing University of Chinese Medicine Beijing 102488, China.
2. School of Chinese Materia Medica, Beijing University of Chinese Medicine Beijing 102488, China Medical Key Laboratory of Hereditary Rare Diseases of Henan, Luoyang City Clinical Research for Endocrinology and Metabolism,Department of Endocrinology and Metabolism, the First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technology Luoyang 471003, China.
- Publication Type:Journal Article
- Keywords:
"quantity-weight-evidence" network toxicology;
ethanol extract of Dysosma versipellis;
hepatotoxicity in rats;
molecular mechanism;
potential toxic material;
quantitative network
- MeSH:
Animals;
Chemical and Drug Induced Liver Injury/etiology*;
Drugs, Chinese Herbal/toxicity*;
Ethanol;
Medicine, Chinese Traditional;
Molecular Docking Simulation;
Rats;
Reproducibility of Results
- From:
China Journal of Chinese Materia Medica
2022;47(2):511-527
- CountryChina
- Language:Chinese
-
Abstract:
In this study, the toxicological/pharmacological research method of "quantity-weight-evidence" network was first proposed and practiced to supplement the existing methodology of network toxicology. We transformed the traditional qualitative network into a quantitative network in this study by attributing weights to toxic component content and target frequency, which improved the reliability of data and provided a research idea for the systematic safety evaluation and toxicological research of Chinese medicinal herbs. Firstly, 50% ethanol extract of Dysosma versipellis(DV) was administrated to rats via gavage and the potential hepatotoxic components were identified by serum pharmacochemistry. Then, the component targets were obtained from SwissTargetPrediction, PharmMapper and other online databases, and the target weights were given according to the relative content of components and target fishing frequency. Meanwhile, the targets of hepatotoxicity were predicted from online databases such as Comparative Toxicology Database(CTD) and GeneCards. Subsequently, protein-protein interaction analysis and KEGG pathway enrichment were performed with the STRING database. Finally, the quantitative network of "toxic components-weighted targets-pathways" was constructed. Eleven potential toxic compounds were predicted, including podophyllotoxin, podophyllotoxone, deoxypodophyllotoxin, and 6-methoxypodophyllotoxin. A total of 106 hepatotoxic targets and 65 weighted targets(e.g., Cdk2, Egfr, and Cyp2 c9) were identified. The results of Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment showed that these targets could act on PI3 K-AKT, MAPK, and Ras signaling pathways to play a role in inflammatory response and oxidative stress. However, traditional network toxicology showed that 51 targets such as AKT1, Alb, and Stat3 may lead to hepatotoxicity by mediating inflammation and cell proliferation. In conclusion, we proposed "quantity-weight-evidence" network toxicology in this study and used it to study the mechanism of DV-induced hepatotoxicity in rats. This study confirms the feasibility of this new methodology in toxicological evaluation and further improves the systematic evaluation of the safety of Chinese medicinal herbs.
