ABSTRACT
Objective:To explore the potential targets and pathways of steroid alkaloids<italic> </italic>from<italic> Solanum</italic> <italic>nigrum</italic> （SASN） in the treatment of non-small cell lung cancer （NSCLC） and analyze the possible mechanism. Method:The active SASN against NSCLC were searched from literature. Then potential targets of SASN were screened through SwissTargetPrediction and PharmMapper， and those of NSCLC through GeneCards. Venny was employed to yield the common targets of the two， and Cytoscape to construct the 'medicinal-component-disease-target' network. Metascape was applied to enrich the Gene Ontology （GO） terms and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathways of the common targets， and STRING was used to generate the protein-protein interaction （PPI） network， followed by screening of key targets by Cytoscape. Finally， Western blot was used to verify the effects of the medicinal on key targets. Result:A total of 6 active SASN were screened out： solasonine， solamargine， solasodine， solanocapsine， solanidine， and <italic>N</italic>-methylsolasodine， which had 96 potential anti-NSCLC targets. These targets mainly involved the pathways in cancer， proteoglycans in cancer， and Forkhead box protein O （FoxO） pathway. PPI network analysis demonstrated 15 key anti-NSCLC targets of SASN， such as mitogen-activated protein kinase （MAPK）1， MAPK8， MAPK14， protein kinase B （Akt1）， signal transducer and activator of transcription 3 （STAT3）， and proto-oncogene tyrosine protein kinase （SRC）. Meanwhile， Western blot results showed that SASN could significantly down-regulate the expression of the key proteins Akt1， SRC， and STAT3. Conclusion:We predicted the potential targets and pathways of SASN against NSCLC and obtained 15 key targets， from which we selected three key proteins for validation. The validation results were consistent with the prediction results. This paper is expected to lay a scientific basis for the subsequent in-depth study of the mechanisms of SASN against NSCLC.
ABSTRACT
Objective: To evaluate the quality differences between Mongolian medicine and traditional Chinese medicine (TCM) Veratri Nigri Radix et Rhizoma in HPLC fingerprint and acute toxicity, as a fundamental research for quality standazation. Methods: HPLC fingerprint methods were used to analyze the steroid alkaloids and stilbenes of Veratri Nigri Radix et Rhizoma from different origins. A total of 14 batches of crude drugs, including eight Mongolian and six TCM samples, were examined, and their common pattern were established by authoritative software "fingerprint similarity evaluation system". Characteristic peaks in these fingerprints, including 32 steroid alkaloids and 16 stilbenes, were selected to performing cluster analysis, using SPSS 20.0 software with relative peak area as variables. Through the experiments of acute toxicity in mice, their toxicities were examined. Results: HPLC fingerprint methods of steroid alkaloids and stilbenes were established for the quality evaluation of Veratri Nigri Radix et Rhizoma, and their common patterns of Mongolian medicines (RMJ, RMZ) and TCMs (RZJ, RZZ) with high similarities between groups were obtained. In clustering analysis, 14 batches of Veratri Nigri Radix et Rhizoma were divided into two categories distinctly, as Mongolian medicine and TCM groups. Mongolian medicine showed stronger toxicity than TCM with the LD50 values as 0.503 0 and 17.934 3 g/kg, respectively. Conclusion: The quality of Mongolian medicine and TCM Veratri Nigri Radix et Rhizoma in the aspects of efficacy and idications, producing area, chemical composition and acute toxicity were of significant differences. It is necessary and emergency to distinguish the two crude drugs, and establish quality standard of Mongolian medicine Veratri Nigri Radix et Rhizoma.
ABSTRACT
Objective To design and synthesize derivatives of wanpeinine A, the main steroidal alkaloid isolated from the plant Fritillaria shuchengensis, and further study on the structure-activity relationship of the steroidal alkaloid. Methods Acylation and alkylation were used to synthesize the derivatives and their structures were identified via NMR and MS.Results The acylation of wanpeinine A (1) produced 3β,6α-diacetylwanpeinine A (2), 3β,6α-dipropionylwanpeinine A (3), 3β,6α-dichloracetylwanpeinine A (4), 3β,6α-dibenzoylwanpeinine A (5), and 3β-methoxyacylwanpeinine A (6). The alkylation of wanpeinine A formed 3β,6α-dimethoxymethylwanpeinine A (7). Conclusion All compounds are new except for 3β,6α-diacetylwanpeinine A.