Dataset Information

Drug-likeness analysis of traditional Chinese medicines: 2. Characterization of scaffold architectures for drug-like compounds, non-drug-like compounds, and natural compounds from traditional Chinese medicines.

ABSTRACT:

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Background

In order to better understand the structural features of natural compounds from traditional Chinese medicines, the scaffold architectures of drug-like compounds in MACCS-II Drug Data Report (MDDR), non-drug-like compounds in Available Chemical Directory (ACD), and natural compounds in Traditional Chinese Medicine Compound Database (TCMCD) were explored and compared.

Results

First, the different scaffolds were extracted from ACD, MDDR and TCMCD by using three scaffold representations, including Murcko frameworks, Scaffold Tree, and ring systems with different complexity and side chains. Then, by examining the accumulative frequency of the scaffolds in each dataset, we observed that the Level 1 scaffolds of the Scaffold Tree offer advantages over the other scaffold architectures to represent the scaffold diversity of the compound libraries. By comparing the similarity of the scaffold architectures presented in MDDR, ACD and TCMCD, structural overlaps were observed not only between MDDR and TCMCD but also between MDDR and ACD. Finally, Tree Maps were used to cluster the Level 1 scaffolds of the Scaffold Tree and visualize the scaffold space of the three datasets.

Conclusion

The analysis of the scaffold architectures of MDDR, ACD and TCMCD shows that, on average, drug-like molecules in MDDR have the highest diversity while natural compounds in TCMCD have the highest complexity. According to the Tree Maps, it can be observed that the Level 1 scaffolds present in MDDR have higher diversity than those presented in TCMCD and ACD. However, some representative scaffolds in MDDR with high frequency show structural similarities to those in TCMCD and ACD, suggesting that some scaffolds in TCMCD and ACD may be potentially drug-like fragments for fragment-based and de novo drug design.

SUBMITTER: Tian S

PROVIDER: S-EPMC3561156 | biostudies-literature | 2013 Jan

REPOSITORIES: biostudies-literature

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Publications

Drug-likeness analysis of traditional Chinese medicines: 2. Characterization of scaffold architectures for drug-like compounds, non-drug-like compounds, and natural compounds from traditional Chinese medicines.

Tian Sheng S Li Youyong Y Wang Junmei J Xu Xiaojie X Xu Lei L Wang Xiaohong X Chen Lei L Hou Tingjun T

Journal of cheminformatics 20130121 1

<h4>Unlabelled</h4><h4>Background</h4>In order to better understand the structural features of natural compounds from traditional Chinese medicines, the scaffold architectures of drug-like compounds in MACCS-II Drug Data Report (MDDR), non-drug-like compounds in Available Chemical Directory (ACD), and natural compounds in Traditional Chinese Medicine Compound Database (TCMCD) were explored and compared.<h4>Results</h4>First, the different scaffolds were extracted from ACD, MDDR and TCMCD by usin ...[more]

PMID: 23336706

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Project description:Traditional Chinese medicines (TCMs) represent one form of complementary and alternative medicine. The popularity and complexity in production make them attractive and vulnerable to adulteration in stages ranging from planting to production. Adulteration refers to the addition of extraneous, improper, or inferior ingredients that should not be present in TCMs. To detect and combat adulterated TCMs, supplementary testing methods (STMs), which expand the capability of routine testing standards, have been applied in China since 2003. From 2003 to 2017, a total of 184 STMs for TCMs were approved by the Chinese national drug regulatory authority. By assessing these STMs, this research intends to identify those TCMs vulnerable to adulteration, to list common adulterants, and to characterize the techniques of analysis. The results show that adulteration of TCMs can be classified into three main categories: the addition of undeclared drugs/chemical substances, substitution with non-drug components, and the addition of foreign non-drug materials. The top five therapeutic areas of TCMs vulnerable to adulteration are diabetes, calm and sleep, sexual dysfunction, pain relief, and rheumatism. A total of 166 adulterants were detected in the adulterated TCM preparations and herbal products studied here, with 158 adulterants in TCM preparations and 43 in herbal products, with 35 adulterants in common. Each STM consists of different pharmaceutical analysis techniques, including tests for physical-chemical properties, chromatography, spectroscopic techniques, and mass spectrometry. The analytical methodology of STMs relies on the combination of these techniques, with HPLC ranking the highest percentage (76.1%) and physical-chemical techniques the lowest percentage (11.4%). This research shows that STMs have played a crucial role in combating adulterated TCMs. However, STMs represent merely a product testing-centered regulatory strategy. The inspection of cultivation and manufacturing processes should also be strengthened. More importantly, the awareness and self-discipline of TCM manufacturers in implementing good manufacturing practices and regulating the planting and cultivation of raw materials should be improved.

Dataset Information

Drug-likeness analysis of traditional Chinese medicines: 2. Characterization of scaffold architectures for drug-like compounds, non-drug-like compounds, and natural compounds from traditional Chinese medicines.

Unlabelled

Background

Results

Conclusion

Publications

Drug-likeness analysis of traditional Chinese medicines: 2. Characterization of scaffold architectures for drug-like compounds, non-drug-like compounds, and natural compounds from traditional Chinese medicines.

Similar Datasets

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