Developing a QSAR model for hepatotoxicity screening of the active compounds in traditional Chinese medicines

数量结构-活动关系 中医药 医学 药品 生物信息学 传统医学 药理学 计算机科学 机器学习 替代医学 化学 生物化学 基因 病理
作者
Shan-Han Huang,Chun-Wei Tung,Ferenc Fülöp,Jih‐Heng Li
出处
期刊:Food and Chemical Toxicology [Elsevier]
卷期号:78: 71-77 被引量:66
标识
DOI:10.1016/j.fct.2015.01.020
摘要

The perception that natural substances are deemed safe has made traditional Chinese medicine (TCM) popular in the treatment and prevention of disease globally. However, such an assumption is often misleading owing to a lack of scientific validation. To assess the safety of TCM, in silico screening provides major advantages over the classical laboratory approaches in terms of resource- and time-saving and full reproducibility. To screen the hepatotoxicity of the active compounds of TCMs, a quantitative structure-activity relationship (QSAR) model was firstly established by utilizing drugs from the Liver Toxicity Knowledge Base. These drugs were annotated with drug-induced liver injury information obtained from clinical trials and post-marketing surveillance. The performance of the model after nested 10-fold cross-validation was 79.1%, 91.2%, 53.8% for accuracy, sensitivity, and specificity, respectively. The external validation of 91 well-known ingredients of common herbal medicines yielded a high accuracy (87%). After screening the TCM Database@Taiwan, the world's largest TCM database, a total of 6853 (74.8%) ingredients were predicted to have hepatotoxic potential. The one-hundred chemical ingredients predicted to have the highest hepatotoxic potential by our model were further verified by published literatures. Our study indicated that this model can serve as a complementary tool to evaluate the safety of TCM.
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