Potential Targets and Mechanisms of Jiedu Quyu Ziyin Decoction for Treating SLE-GIOP: Based on Network Pharmacology and Molecular Docking.

Background: Systemic lupus erythematosus (SLE) is characterized by poor regulation of the immune response leading to chronic inflammation and multiple organ dysfunction. Glucocorticoid (GC) is currently one of the main treatments. However, a high dose or prolonged use of GC may result in glucocorticoid-induced osteoporosis (GIOP). Jiedu Quyu Ziyin decoction (JP) is effective in treating SLE and previous clinical studies have proved that JP can prevent and treat SLE steroid osteoporosis (SLE-GIOP). We aim to examine JPs main mechanism on SLE-GIOP through network pharmacology and molecular docking. Methods: TCMSP and TCMID databases were used to screen potential active compounds and targets of JP. The SLE-GIOP targets are collected from GeneCards, OMIM, PharmGkb, TTD, and DrugBank databases. R software was used to obtain the cross-targets of JP and SLE-GIOP and to perform GO and KEGG enrichment analysis. Cytoscape software was used to make the Chinese Medicines-Active Ingredient-Intersection Targets network diagram. STRING database construct protein-protein interaction network and obtain the core targets. Auto Dock Tools and Pymol software were used for docking. Results: Fifty eight targets overlapped between JP and SLE-GIOP were suggested as potential targets of JP in the treatment of SLE-GIOP. Network topology analysis identified five core targets. GO enrichment analysis was obtained 1,968 items, and the top 10 biological process, closeness centrality, and molecular function were displayed. A total of 154 signaling pathways were obtained by KEGG enrichment analysis, and the top 30 signaling pathways were displayed. JP was well bound by MAPK1, TP53, and MYC according to the molecular docking results. Conclusion: We investigated the potential targets and signaling pathways of JP against SLE-GIOP in this study. It shows that JP is most likely to achieve the purpose of treating SLE-GIOP by promoting the proliferation and differentiation of osteoblasts. A solid theoretical foundation will be provided for the future study of clinical and experimental topics.

[Multi-index optimization of extraction process of Fengyin Decoction based on BAS-GA-BP neural network combined with entropy weight method].

To optimize the ethanol extraction technology parameters of Fengyin Decoction by orthogonal experiment combined with beetle antennae search(BAS)-genetic algorithm(GA)-back propagation neural network(BPNN). Based on single factor investigation, the extraction temperature, ethanol volume, extraction time, and ethanol concentration were used as orthogonal experiment factors, and entropy weight method was used to calculate the comprehensive scores of aloe-emodin, glycyrrhizic acid ammonium salt, rhein, emodin, chrysophanol, physcion, cinnamaldehyde, 6-gingerol, extraction ratio and fingerprint similarity. BAS-BPNN model was established, and then, GA was used to predict the optimal extraction process. The results showed that BAS-BPNN was optimized to obtain the optimal ethanol extraction process of Fengyin Decoction as follows: extraction temperature of 87 ℃, adding 9 times of 75 % ethanol, and extracting for 47 minutes, with a comprehensive score of 1.052 9. Meanwhile, the optimal process parameters obtained by orthogonal design were as follows: the extraction temperature of 80 ℃, adding 10 times of 75% ethanol, extracting for 30 minutes, with a comprehensive score of 1.003 7. The comprehensive score of the process obtained from the BAS-BPNN model was slightly better than that from the orthogonal test, indicating that the optimized process from BAS-BPNN model was more ideal, so it was finally determined as the best extraction process for Fengyin Decoction. The process of Fengyin Decoction obtained from BAS-GA-BPNN has high extraction efficiency and good stability, which provides reference for the subsequent development and quality control.