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作为抗感染和抗炎药物发现化学资源库的传统中药。

Traditional Chinese herbs as chemical resource library for drug discovery of anti-infective and anti-inflammatory.

作者信息

Ding Weixian, Gu Jiangyong, Cao Liang, Li Na, Ding Gang, Wang Zhengzhong, Chen Lirong, Xu Xiaojie, Xiao Wei

机构信息

National Key Laboratory of Pharmaceutical New Technology for Chinese Medicine, Kanion Pharmaceutical Corporation, Lianyungang, China.

Beijing National Laboratory for Molecular Sciences (BNLMS), State Key Laboratory of Rare Earth Materials Chemistry and Applications, College of Chemistry and Molecular Engineering, Peking University, Beijing, China.

出版信息

J Ethnopharmacol. 2014 Aug 8;155(1):589-98. doi: 10.1016/j.jep.2014.05.066. Epub 2014 Jun 11.

Abstract

ETHNOPHARMACOLOGICAL RELEVANCE

Infection is a major group of diseases which caused significant mortality and morbidity worldwide. Traditional Chinese herbs have been used to treat infective diseases for thousands years. The numerous clinical practices in disease therapy make it a large chemical resource library for drug discovery.

MATERIALS AND METHODS

In this study, we collected 1156 kinds of herbs and 22,172 traditional Chinese medicinal compounds (Tcmcs). The chemical informatics and network pharmacology were employed to analyze the anti-infective effects of herbs and Tcmcs. In order to evaluate the drug likeness of Tcmcs, the molecular descriptors of Tcmcs and FDA-approved drugs were calculated and the chemical space was constructed on the basis of principal component analysis in the eight descriptors. On purpose to estimate the effects of Tcmcs to the targets of FDA-approved anti-infective or anti-inflammatory drugs, the molecular docking was employed. After that, docking score weighted predictive models were used to predict the anti-infective or anti-inflammatory efficacy of herbs.

RESULTS

The distribution of herbs in the phylogenetic tree showed that most herbs were distributed in family of Asteraceae, Fabaceae and Lamiaceae. Tcmcs were well coincide with drugs in chemical space, which indicated that most Tcmcs had good drug-likeness. The predictive models obtained good specificity and sensitivity with the AUC values above 0.8. At last, 389 kinds of herbs were obtained which were distributed in 100 families, by using the optimal cutoff values in ROC curves. These 389 herbs were widely used in China for treatment of infection and inflammation.

CONCLUSION

Traditional Chinese herbs have a considerable number of drug-like natural products and predicted activities to the targets of approved drugs, which would give us an opportunity to use these herbs as a chemical resource library for drug discovery of anti-infective and anti-inflammatory.

摘要

民族药理学相关性

感染是一类主要疾病,在全球范围内导致了显著的死亡率和发病率。传统中草药用于治疗感染性疾病已有数千年历史。在疾病治疗中的大量临床实践使其成为一个用于药物发现的大型化学资源库。

材料与方法

在本研究中,我们收集了1156种草药和22172种传统中药化合物(TCMcs)。采用化学信息学和网络药理学分析草药和TCMcs的抗感染作用。为了评估TCMcs的类药性质,计算了TCMcs和美国食品药品监督管理局(FDA)批准药物的分子描述符,并基于八个描述符的主成分分析构建了化学空间。为了评估TCMcs对FDA批准的抗感染或抗炎药物靶点的作用,采用了分子对接。之后,使用对接分数加权预测模型预测草药的抗感染或抗炎疗效。

结果

草药在系统发育树中的分布表明,大多数草药分布在菊科、豆科和唇形科。TCMcs在化学空间中与药物吻合良好,这表明大多数TCMcs具有良好的类药性质。预测模型获得了良好的特异性和敏感性,曲线下面积(AUC)值高于0.8。最后,通过使用ROC曲线中的最佳截断值,获得了分布在100个科的389种草药。这389种草药在中国广泛用于治疗感染和炎症。

结论

传统中草药有相当数量的类药天然产物以及对已批准药物靶点的预测活性,这将为我们提供机会将这些草药用作抗感染和抗炎药物发现的化学资源库。

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