ABSTRACT
To explore the mechanism of Hedyotis Diffusae Herba-Smilacis Glabrae Rhizoma(HDH-SGR) in treating lung adenocarcinoma based on big data bioinformatics combined with network pharmacology analysis and molecular docking technology. The chemical components and potential therapeutic targets of HDH-SGR were obtained from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP). Lung adenocarcinoma-related genes were obtained from The Cancer Genome Atlas(TCGA), Therapeutic Target Database(TTD), Pharmacogenetics and Pharmacogenomics Knowledge Base(PharmGKB), Online Mendelian Inheritance in Man(OMIM), DrugBank, and GeneCards. "Drug component-target" network was constructed using Cytoscape to screen out key compounds. STRING was used to build protein-protein interaction(PPI) network and core targets were screened out by Cytoscape-CytoNCA topology analysis. Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) analyses of target genes were performed by R-clusterProfiler. Finally, key compounds were docked to core target genes using AutoDock. The results showed that 22 active compounds and 499 potential therapeutic targets were obtained from HDH-SGR. A total of 14 332 lung adenocarcinoma-related targets were screened out through six data platforms, including 182 common targets. Fifteen core targets were screened out from the PPI network. GO and KEGG analyses revealed significant enrichment of relevant target genes in various biological processes, cellular functions(e.g., response to lipopolysaccharide, nuclear receptor activity, and ligand-activated transcription factor activity) and close relationship between target genes and non-small cell lung cancer signaling pathways. Based on the results of molecular docking validation, diosgenin, quercetin, naringenin, taxifolin, 2-methoxy-3-methyl-9,10-anthraquinone, stigmasterol, and β-sitosterol were able to bind tightly to the core targets. HDH-SGR can intervene in lung adenocarcinoma through multiple targets and signaling pathways, such as non-small cell lung cancer signaling pathways. The binding of active components in Chinese medicine to key targets is presumedly one of the mechanisms that produce therapeutic effects.
Subject(s)
Humans , Adenocarcinoma of Lung/genetics , Carcinoma, Non-Small-Cell Lung , Drugs, Chinese Herbal , Hedyotis , Lung Neoplasms/genetics , Medicine, Chinese Traditional , Molecular Docking Simulation , Network PharmacologyABSTRACT
OBJECTIVE: To develop a method for determining 12 constituents in Yigan Jiedu Capsules by HPLC. METHODS: The quantitative analysis was carried out on a Waters Atlantic T3 C18column maintained at 40 ℃, using mobile phase consisting of acetonitrile(A)and 0.1% phosphoric acid solution(B)by a gradient elution program(0-10 min, 4%→13%A; 10-20 min, 13%→15%A; 20-25 min, 15%→19%A; 25-35 min, 19%A; 35-36 min, 19%→23%A; 36-45 min, 23%→27%A; 45-56 min, 27%→43%A; 56-65 min, 43%→65%A) at a flow rate of 1 mL•min-1. The detection wavelength was set at 270 nm in the first 22 min, and then changed to 290 nm between 22 and 44 min, and last changed to 270 nm. RESULTS: The linear ranges of gallic acid, vanillic acid, picroside Ⅱ, astilbin, engeletin, picroside, baicalin, berberine hydrochloride, wogonoside, emodin, chrysophanol and wogonin fell with in the range of 0.012 19-0.243 8 μg, 0.036 70-0.734 0 μg, 0.033 77-0.675 4 μg, 0.057 38-1.147 6 μg, 0.006 580-0.131 6 μg, 0.015 38-0.307 6 μg, 0.067 11-1.342 2 μg, 0.028 04-0.560 8 μg, 0.041 48-0.829 6 μg, 0.006 310-0.126 2 μg, 0.013 64-0.272 8 μg and 0.014 22-0.284 4 μg. The recoveries were 98.7%, 98.9%, 99.4%, 99.2%, 98.9%, 99.1%, 98.9%, 99.6%, 99.3%, 98.9%, 98.6% and 99.0%, respectively. The relative standard deviations were 1.02%, 0.46%, 0.64%, 0.86%, 1.1%, 1.3%, 0.60%, 0.92%, 0.61%, 1.5%, 0.93%and 0.98%, respectively(n=6). CONCLUSION: This method is simple, accurate, reproducible and convenient for the quality control over Yigan Jiedu Capsules.
ABSTRACT
OBJECTIVE: To investigate the chemical differences between Smilacis Glabrae Rhizoma and its adulterants, and provide a basis for the identification and quality evaluation of Tufuling samples purchased from the markets. METHODS: The method of HPLC fingerprinting was used to analyze Smilacis Glabrae Rhizoma, Heterosmilacis Chinensis Rhizoma, Heterosmilacis Yunnanensis Rhizoma, and 102 Tufuling samples which were collected around China. The fingerprints were analyzed by the methods of similarity and principal component analysis (PCA). RESULTS: The analytical method of HPLC fingerprinting was established. Eleven, fifteen and eight common peaks were selected in the fingerprints of Smilacis Glabrae Rhizoma, Heterosmilacis Chinensis Rhizoma, and Heterosmilacis Yunnanensis Rhizoma, respectively. Only five common peaks were found in the fingerprints of the three species, which were No. 1, 2, 3, 13, and 14 peaks. A total of twelve peaks were characterized in the three fingerprints. Nine peaks were characterized in the fingerprint of Smilacis Glabrae Rhizoma, among which, four constituents were characterized for the first time. Six and two constituents were for the first time characterized in the fingerprints of Heterosmilacis Chinensis Rhizoma and Heterosmilacis Yunnanensis Rhizoma, respectively. The result of PCA analysis showed that the chemical differences between the three species were quite obvious and they could be distinguished from each other. The established method was used for the analysis of Tufuling samples purchased from the markets. Sixty-five samples were identified as Smilacis Glabrae Rhizoma, seventeen samples were identified as Heterosmilacis Yunnanensis Rhizoma, and twenty samples were identified as Heterosmilacis Chinensis Rhizoma. CONCLUSION: The established method is simple and reliable, and the development of fingerprint and its chemical pattern recognition provide the way and basis for identification of Smilacis Glabrae Rhizoma and its adulterants.
ABSTRACT
OBJECTIVE:To optimize the extraction technology of astilbin from medicinal herbs in Puling penyankang cap-sules. METHODS:The extraction technology of astilbin from ingredients(Smilacis glabrae rhizoma,chuanxiong rhizoma,Eucom-miae cortex,notoginseng radix et rhizoma,Plantaginis semen)of Puling penyankang capsules was optimized with concentration of ethanol,immersion time and percolation speed as factors,and using the yield of extractum and the extraction amount of astilbin as index. RESULTS:The optimized extraction technology was as follows as 2-fold 70% ethanol,immersed for 24 h,percolated with 70% ethanol with percolation speed of 3 ml/min,10-fold percolate volume was colleted. In verification test,the yield of extractum were 6.79%,6.92% and 6.84%,respectively,with average value of (6.85 ± 0.96)%(n=3);the extraction amounts of astilbin were 39.23,39.67 and 39.69 mg,with average value of (39.53 ± 0.66) mg (n=3). CONCLUSIONS:The optimized extraction technology of astilbin in Puling penyankang capsules is stable and practical.
ABSTRACT
Aim: To develop and compare the ultra-performance liquid chromatography( UPLC) and HPLC methods for the determination of dihydroflavonoids in Smilacis glabrae Rhizoma, and establish the quality evaluation system of the above-mentioned crude drug. Methods: Four dihydroflavonoids in the crude drugs collected from 15 localities were determined using the UPLC and HPLC methods, respectively. The resolution, sensitivity, precision, accuracy and the content determination results of the four compounds were compared between the two methods. Results: The UPLC method was more fast and sensitive than the HPLC method with no significant differences among the linearity range, precision, accuracy and the content determination results between the two methods. Conclusion: The developed HPLC method was proved practicable and reliable for the quality control of Smilacis glabrae Rhizoma. The UPLC method was provided to be a more sensitive, fast and solvent-saving method compared to HPLC and can be applied in the quality evaluation of Chinese medicines.