Prediction of multi-target of Aconiti Lateralis Radix Praeparata and its network pharmacology
Wu, L.; Gao, X.; Wang, L.; Liu, Q.; Fan, X.; Wang, Y.; Cheng, Y.
Zhongguo Zhong Yao Za Zhi 36(21): 2907-2910
2011
ISSN/ISBN: 1001-5302 PMID: 22308671 Document Number: 653261
To predict multi-targets by multi-compounds found in Aconiti Lateralis Radix Praeparata and construct the corresponding multi-compound-multi-target network. Based on drug-target relationships of FDA approved drugs, a model for predicting targets was established by random forest algorithm. This model was then applied to predict the targets of Aconiti Lateralis Radix Praeparata and construct the multi-compound-multi-target network. The predicted targets of 22 compounds of Aconiti Lateralis Radix Praeparata are validated by literature. Each compound in the established network was correlated with 16. 3 targets on average, while each target was correlated with 4. 77 compounds on average, which reflects the "multi-compound and multi-target" characteristic of Chinese medicine. The proposed approach can be used to find potential targets of Chinese medicine.