摘要
目的:以常用中药附子为例,探索以中药化学成分预测其作用靶点,并构建中药多成分-多靶点网络。方法:根据1 401个美国FDA批准上市药物的分子结构及其相应靶点数据,采用随机森林法建立靶点预测模型;进而依据附子所含化学成分预测其作用靶点,并据此构建附子多成分-多靶点网络。结果:以附子的22个化学成分预测出多个作用靶点,预测结果得到文献数据印证。所建网络模型中每个化合物的平均靶点数为16.3,平均每个靶点与4.77个化合物相关联,反映出中药"多成分、多靶点"特点。结论:本方法可用于发现中药的某些潜在作用靶点。
Objective： To predict multi-targets by multi-compounds found in Aconiti Lateralis Radix Praeparata and construct the corresponding multi-compound-multi-target network. Method ： 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. Result： 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＂ char- acteristic of Chinese medicine. Conclusion： The proposed approach can be used to find potential targets of Chinese medicine.
出处
《中国中药杂志》
CAS
CSCD
北大核心
2011年第21期2907-2910,共4页
China Journal of Chinese Materia Medica
基金
科技部国际合作项目(2009DFB03510)
关键词
网络药理学
附子
靶点预测
网络中药药理学
多成分-多靶点网络
network pharmacology
Aconiti Lateralis Radix Praeparata
target prediction
network pharmacology of Chinese medicine
multi-compound-multi-target network
