论文部分内容阅读
研究建立的中草药重要成分的QSAR预测毒性数据库,共包括984个中草药重要成分。数据库分为4个子库:基本化学信息子库,化学结构式图子库,毒性实验数据子库和毒性QSAR预测数据子库。研究利用多种公开的和商业QSAR预测软件,预测多个终点:经口急性毒性、慢性毒性、致癌性(遗传毒性和非遗传毒性)、致突变性(Ames试验和骨髓微核试验)、发育毒性及毒理学关注阈值(TTC)。研究将对中草药成分的毒性QSAR预测进行可靠性评价。研究将对中草药成分的毒性预测方法进行探索,以促进中草药的毒性识别和中药现代化。
The QSAR predictive toxicity database was established to study the important components of Chinese herbal medicines, which included 984 important components of Chinese herbal medicines. The database is divided into four sub-libraries: the basic chemical information sub-library, the chemical structural sub-library, the virulence experimental data sub-library and the toxic QSAR prediction data sub-library. The study used a variety of published and commercial QSAR prediction software to predict multiple endpoints: oral acute toxicity, chronic toxicity, carcinogenicity (genotoxic and non-genotoxic), mutagenicity (Ames test and bone marrow micronucleus test), development Toxicity and Toxicology Concern Threshold (TTC). The study will evaluate the reliability of the toxic QSAR prediction of herbal ingredients. The research will explore the method for the prediction of the toxicity of Chinese herbal medicine to promote the identification of Chinese herbal medicine and the modernization of traditional Chinese medicine.