Literature DB >> 31386897

The NCI library of traditional Chinese medicinal plant extracts - Preliminary assessment of the NCI-60 activity and chemical profiling of selected species.

Min He1, Tanja Grkovic2, Jason R Evans3, Christopher C Thornburg2, Rhone K Akee2, Jerell R Thompson2, James A Whitt2, Matthew J Harris2, Jasmine A Loyal2, John R Britt2, Libin Jia4, Jeffrey D White4, David J Newman5, Barry R O'Keefe6.   

Abstract

Botanical-based natural products are an important resource for medicinal drug discovery and continue to provide diverse pharmacophores with therapeutic potential against cancer and other human diseases. A prototype Traditional Chinese Medicine (TCM) plant extract library has been established at the US National Cancer Institute, which contains both the organic and aqueous extracts of 132 authenticated medicinal plant species that collectively represent the potential therapeutic contents of most commonly used TCM herbal prescriptions. This library is publicly available in 96- and 384- well plates for high throughput screening across a broad array of biological targets, as well as in larger quantities for isolation of active chemical ingredients. Herein, we present the methodology used to generate the library and the preliminary assessment of the anti-proliferative activity of this crude extract library in NCI-60 human cancer cell lines screen. Particularly, we report the chemical profiling and metabolome comparison analysis of four commonly used TCM plants, namely Brucea javanica, Dioscorea nipponica, Cynanchum atratum, and Salvia miltiorrhiza. Bioassay-guided isolation resulted in the identification of the active compounds, and different extraction methods were compared for their abilities to extract cytotoxic compounds and to concentrate biologically active natural products. Published by Elsevier B.V.

Entities:  

Keywords:  Anti-proliferative activity; NCI-60; Natural product; Traditional Chinese medicine

Mesh:

Substances:

Year:  2019        PMID: 31386897      PMCID: PMC7391999          DOI: 10.1016/j.fitote.2019.104285

Source DB:  PubMed          Journal:  Fitoterapia        ISSN: 0367-326X            Impact factor:   2.882


  26 in total

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Authors:  Song-Yi Lee; Doo-Youn Choi; Eun-Rhan Woo
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9.  TCM Database@Taiwan: the world's largest traditional Chinese medicine database for drug screening in silico.

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