中医药信息2026，Vol.43Issue(3)：29-37,9.DOI:10.19656/j.cnki.1002-2406.20260305
食药物质定量结构-活性关系肺毒性预测与评估方法研究——以甘草为例
Prediction and Evaluation Method of Pulmonary Toxicity in Food-Medicine Substances by Quantitative Structure-Activity Relationship——Taking Glycyrrhiza uralensis as an example
摘要
Abstract
Objective To construct a quantitative structure-activity relationship(QSAR)-based method for predicting and evaluating the pulmonary toxicity in food-medicine substances,and apply it to the prediction of pulmonary toxicity in Glycyrrhiza uralensis.Methods A total of 864 chemical structures related to 45 types of pulmonary adverse reactions were collected from the SIDER database,and molecular images of 87 compounds contained in Glycyrrhiza uralensis were collected from the TCMSP database.These molecular images were screened and converted into SMILES format using Stone MIND Collector software.Finally,a QSAR model for pulmonary toxicity was established by the DrugFlow artificial intelligence-aided drug design platform,and the five-fold cross-validation method was used to verify the accuracy and robustness of the established model.87 compounds contained in Glycyrrhiza uralensis were collected,by searching from the TCMSP database and Yaozhi Network database,and the QSAR model for pulmonary toxicity was applied to predict and evaluate the pulmonary toxicity of Glycyrrhiza uralensis.Results The constructed QSAR model for pulmonary toxicity was evaluated,with an accuracy(ACC)of 0.910,and the Receiver Operating Characteristic-Area Under the Curve(ROC-AUC)was 0.816(close to 1),indicating that the model had a relatively high overall prediction accuracy.The prediction results revealed that the Pmax of Glycyrrhiza uralensis was 0.436,classifying it as a substance of"low possibility of causing pulmonary toxicity".Glycyrrhiza uralensis induced pulmonary toxicity was most likely associated with the following compounds:(2R)-2-[(E)-1-butenyl]-5-(methylethoxy)-7H-isoflavone(C22H32O3),(2'R,3'S)-2',2'-dimethyl-7,3',5'-trihydroxy-2',3'-dihydroflavone-4-lactone(C24H24O6),and(3β)-lanosta-8,24-dien-3-ol(C30H50O).Conclusion The QSAR model established in this study can reasonably accurately predict the potential pulmonary toxicity of food-medicine substances and identify the compounds possibly related to pulmonary toxicity,which can provide a basis for the early identification and warning of pulmonary toxicity of food-medicine substances.关键词
分子指纹/定量结构-活性关系/肺毒性/食药物质/药食同源Key words
Molecular fingerprint/Quantitative structure-activity relationship/Pulmonary toxicity/Food-medicine substance/Homology of food and medicine引用本文复制引用
闵捷,付芳,李莹,吴地尧..食药物质定量结构-活性关系肺毒性预测与评估方法研究——以甘草为例[J].中医药信息,2026,43(3):29-37,9.基金项目
江西省自然科学基金项目(20224BAB206115) （20224BAB206115）
江西省中医药管理局科技计划项目(2023A0398) （2023A0398）
南昌市医疗卫生引导性科技计划项目(2023YLWS034) （2023YLWS034）
江西省卫健委科技计划项目(202311134) （202311134）
