RESUMO
Traditional Chinese medicines (TCMs), as a unique natural medicine resource, were used to prevent and treat bacterial diseases in China with a long history. To provide a prediction model of screening antibacterial TCMs for the design and discovery of novel antibacterial agents, the literature about antibacterial TCMs in the China National Knowledge Infrastructure (CNKI) and Web of Science database was retrieved. The data were extracted and standardized. A total of 28,786 pieces of data from 904 antibacterial TCMs were collected. The data of plant medicine were the most numerous. The result of association rules mining showed a high correlation between antibacterial activity with cold nature, bitter and sour tastes, hemostatic, and purging fire efficacies. Moreover, TCMs with antibacterial activity showed a specific aggregation in the phylogenetic tree; 92% of them came from Tracheophyta, of which 74% were mainly concentrated in rosids, asterids, Liliopsida, and Ranunculales. The prediction models of anti-Escherichia coli and anti-Staphylococcus aureus activity, with AUC values (the area under the ROC curve) of 77.5 and 80.0%, respectively, were constructed by the Neural Networks (NN) algorithm after Bagged Classification and Regression Tree (Bagged CART) and Linear Discriminant Analysis (LDA) selection. The in vitro experimental results showed the prediction accuracy of these two models was 75 and 60%, respectively. Four TCMs (Cirsii Japonici Herba Carbonisata, Changii Radix, Swertiae Herba, Callicarpae Formosanae Folium) were proposed for the first time to show antibacterial activity against E. coli and/or S. aureus. The results implied that the prediction model of antibacterial activity of TCMs based on properties and families showed certain prediction ability, which was of great significance to the screening of antibacterial TCMs and can be used to discover novel antibacterial agents.
RESUMO
The golden buckwheat Fagopyrum dibotrys produced in Yunnan has a unique anti-cancer effects. It is a main raw material of "Wei Mai ning" capsules which is the national second-class anti-cancer drug. The present paper used (5 : 1) mixed acid as digestive juice to process the sample, and determine the twelve elements including K, Ca, Cu, Na, Mg, Mn, Fe, Zn, Pb, Cr, Cd and Co in the Fagopyrum dibotrys by inductively coupled plasma atomic emission spectrometry(ICP-AES). The detection limits of this method were 0.017-0.084 microg x mL(-1), the RSDs (n = 8) were all 0.09%-1.87%, and the addition standard recoveries(ASR) (n = 8) were 98.2%-107.4% for all elements. The research results showed that there is rich K(1 477.3 microg x g(-1)) in the Fagopyrum dibotrys, there are not harmful elements Cd and Pb, and this result is mainly related to the geochemistry background where the sample lived. The contents of seven remaining kinds of elements ranked as Na (826.1) > Ca (765.2 > Mg (493.4) > Zn (112.7) > Fe (56.5) > Cu (11.4) > Mn (4.49 microg x g(-1)). This result provides some theoretical basis for the study of internal relations between trace elements in Fagopyrum dibotrys and efficacy. It' s also useful for better development and utilization of the resource.