Discovery of cytochrome P450 enzymes-inhibiting components in traditional Chinese medicine.
10.19540/j.cnki.cjcmm.20191022.401
- Author:
Ya-Nan ZHAO
1
;
Yan-Kun CHEN
1
;
Xi CHEN
1
;
Lian-Sheng QIAO
1
;
Jing-Fang ZHANG
1
;
Lian-Yi CAI
1
;
Yan-Ling PEI
2
;
Yan-Ling ZHANG
1
Author Information
1. State Laboratory of Traditional Chinese Medicine-Information Engineering, State Administration of Traditional Chinese Medicine, School of Chinese Material Medica, Beijing University of Chinese Medicine Beijing 102488, China.
2. Hebei Xinminhe Quality Inspection Technology Service Co.Ltd. Baoding 071200, China.
- Publication Type:Journal Article
- Keywords:
CYP450;
drug-drug interaction(DDI);
molecular docking;
support vector machine;
traditional Chinese medicine
- MeSH:
Cytochrome P-450 Enzyme Inhibitors/analysis*;
Cytochrome P-450 Enzyme System;
Drugs, Chinese Herbal/chemistry*;
Medicine, Chinese Traditional;
Molecular Docking Simulation;
Plants, Medicinal/chemistry*
- From:
China Journal of Chinese Materia Medica
2020;45(4):923-931
- CountryChina
- Language:Chinese
-
Abstract:
With the widespread use of traditional Chinese medicine(TCM) and the integration of TCM and western medicine, drug-drug interaction(DDI) is considered as a major cause of therapeutic failures and side effects. Cytochrome P450 enzymes(CYPs) are responsible for large number of drug metabolism. CYP3 A4 and CYP2 D6, two important CYP isoforms, are responsible for about 80% drug metabolism of CYPs super family. The inhibition of CYPs is likely to be the most common factor leading to adverse DDI. Therefore, it is of great significance to predict potential CYP3 A4 and CYP2 D6 inhibitors to prevent the DDI. A fast and low-cost me-thod for calculating and predicting CYP inhibiting components was established in this paper, namely support vector machine(SVM) and molecular docking technology which are used to predict and screen drugs. Firstly, 12 qualitative models of two targets were established by using SVM, and the optimal model was selected to predict the compounds in traditional Chinese medicine database(TCMD). Then, molecular docking technology was used to establish docking model. By analyzing the key amino acids involved in drug-target interactions and combining with SVM model, potential inhibitors of CYP3 A4 and CYP2 D6 were found. From the computational results, astin D and epiberberine exhibited inhibition effect on CYP3 A4 and CYP2 D6, respectively. Astin D was only found in astins family from Aster tataricus, while epiberberine was considered to be the active constituent of Coptidis Rhizoma. Therefore, for the risk of DDI, extra attention should be paid to the source of these potential inhibitors, Asteris Radix et Rhizoma and Coptidis Rhizoma. This computational method provides technical support for discovering potential natural inhibitors of CYPs from Chinese herbs by using SVM and molecular docking model, and it is also helpful to recognize the CYPs-mediated DDI existing in TCM, providing research ideas for further pharmacovigilance of integrated therapy.
