Use of a Systematic Pharmacological Methodology to Explore the Mechanism of Shengmai Powder in Treating Diabetic Cardiomyopathy.

BACKGROUND Cardiovascular complications, such as diabetic cardiomyopathy (DCM), are the leading cause of death in diabetic patients. Shengmai Powder (SMP) was found to have cardioprotective effects. MATERIAL AND METHODS Based on the systematic pharmacological methodology, this research determined the genes of DCM and the known targets of SMP, predicted potential compounds and targets of SMP, constructed networks for DCM and SMP, and performed network analysis. RESULTS Five network were constructed: (1) the DCM gene PPI network; (2) the Compound-compound target network of SMP; (3) the SMP-DCM PPI network; (4) the Compound-known target network of SMP; (5) and the SMP known target-DCM PPI network. Several DCM and treatment related targets, clusters, signaling pathways, and biological processes were found. CONCLUSIONS SMP is able to regulate glycometabolism-related, lipid metabolism-related, inflammatory response-related, oxidative stress-related signaling pathways, and biological processes and targets, which suggests that SMP may have a therapeutic effect on DCM.

Research on the Mechanism of Liuwei Dihuang Decoction for Osteoporosis Based on Systematic Biological Strategies.

Background: Osteoporosis is an important health problem worldwide. Liuwei Dihuang Decoction (LDD) and its main ingredients may have a good clinical effect on osteoporosis. Meanwhile, its mechanism for treating osteoporosis needs to be further revealed in order to provide a basis for future drug development. Methods: A systematic biological methodology was utilized to construct and analyze the LDD-osteoporosis network. After that, the human transcription data of LDD intervention in patients with osteoporosis and protein arrays data of LDD intervention in osteoporosis rats were collected. The human transcription data analysis, protein arrays data analysis, and molecular docking were performed to validate the findings of the prediction network (LDD-osteoporosis PPI network). Finally, animal experiments were conducted to verify the prediction results of systematic pharmacology. Results: (1) LDD-osteoporosis PPI network shows the potential compounds, potential targets (such as ALB, IGF1, SRC, and ESR1), clusters, biological processes (such as positive regulation of calmodulin 1-monooxygenase activity, estrogen metabolism, and endothelial cell proliferation), and signaling and Reactome pathways (such as JAK-STAT signaling pathway, osteoclast differentiation, and degradation of the extracellular matrix) of LDD intervention in osteoporosis. (2) Human transcriptomics data and protein arrays data validated the findings of the LDD-osteoporosis PPI network. (3) The animal experiments showed that LDD can improve bone mineral density (BMD), increase serum estradiol (E2) and alkaline phosphatase (ALP) levels, and upregulate Wnt3a and ß-catenin mRNA expression (P < 0.05). (4) Molecular docking results showed that alisol A, dioscin, loganin, oleanolic acid, pachymic acid, and ursolic acid may stably bind to JAK2, ESR1, and CTNNB1. Conclusion: LDD may have a therapeutic effect on osteoporosis through regulating the targets (such as ALB, IGF1, SRC, and ESR1), biological processes (such as positive regulation of calmodulin 1-monooxygenase activity, estrogen metabolism, and endothelial cell proliferation), and pathways (such as JAK-STAT signaling pathway, osteoclast differentiation, and degradation of the extracellular matrix) found in this research.