Identification of the Main Chemical constituents and mechanism of Renshen Guben oral liquid against Renal Fibrosis.

BACKGROUND: Renal fibrosis is the late stage of many chronic kidney diseases (CKD). Clinically, there is almost no effective treatment for renal fibrosis except dialysis. Renshen Guben oral liquid (RSGB) is a Chinese patent medicine approved by National Medical Products Administration (NMPA), which is suitable for clinical patients with chronic nephritis. Currently, the chemical constituents of RSGB remains unclear, and its efficacy and mechanism on renal fibrosis have not been reported. METHODS: In our research, ultra-high performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS/MS) was employed to describe the chemical profile of RSGB, unilateral ureteral obstruction (UUO) model in mice was established to evaluate the beneficial effect of RSGB on renal fibrosis by biochemical indexes, HE and Masson staining. RNA sequencing and "constituents-targets-pathways" multi-dimensional network was established to mine the mechanisms of RSGB. Key targets were verified by quantitative real-time PCR (qRT-PCR) and western bolt (WB). RESULTS: A total of 201 constituents were identified or tentatively characterized, 15 of which were confirmed with standards. The number of triterpenes was the highest with 49, followed by phenols with 46. RSGB ameliorated the blood urea nitrogen (BUN) and serum creatinine (Scr) levels in serum, normalizing pathological structure of kidney tissue. RNA sequencing revealed that RSGB regulates 226 differential genes, which were involved in kidney development. According to the "constituents-targets-pathways" network, 26 key active constituents may mainly regulate the inflammatory immune system through 88 corresponding targets. qRT-PCR and WB results showed that RSGB inhibited the activation of the Tgfß1/Smad2/3 pathway, Wnt4/ß-Catenin pathway and NGFR/NF-κB pathway. CONCLUSIONS: Overall, our study, for the first time, characterized 201 chemical constituents in RSGB, and 26 of them were screened out to alleviates renal fibrosis mainly through Tgfß1/Smad2/3 pathway, Wnt4/ß-catenin pathway and NGFR/NF-κB pathway, which may provide a new research strategy for research on the mechanism of traditional Chinese Medicine.

The mechanisms of Qizhu Tangshen formula in the treatment of diabetic kidney disease: Network pharmacology, machine learning, molecular docking and experimental assessment.

BACKGROUND: Qizhu Tangshen Formula (QZTS) has been shown therapeutic effects on diabetic kidney disease (DKD). However, to date, the pharmacological mechanisms remain vague. METHODS: To explore the underlying mechanisms of QZTS in treating DKD using network pharmacology, machine learning, molecular docking and experimental assessment. RESULTS: First, we found that QZTS improved glycolipid metabolism disorder, decreased proteinuria and alleviated kidney tissue injury in DKD model KKAy mice. Then, by integrating multiple databases, a total of 96 targets of 74 active compounds in QZTS and 759 DKD-related genes were acquired. Next, we identified 13 hub targets of QZTS in DKD by three rank algorithms, including functional similarity, topological similarity and shortest path. Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses demonstrated that the pathways mainly centered on the processes of glycolipid metabolism disorder, inflammation and angiogenesis. Among them, VEGF signaling pathway was significantly enriched. Molecular docking showed that key active compounds of QZTS all had relatively good binding affinity with predicted hub targets. Finally, animal experiments found that QZTS significantly inhibited the secretion of plasma VEGF and downregulated the protein and mRNA expression levels of AKT, p38MAPK and VEGFR2. CONCLUSION: Our results indicated that QZTS treated DKD via multiple targets and pathways and the VEGF signaling pathway may be highly involved in this process.

[Research on function of Feilike Mixture in stopping cough, eliminating phlegm and relieving asthma based on animal experiments and network pharmacology].

This study observed the pharmacological effects of Feilike Mixture(FLKM) in stopping cough, eliminating phlegm, and relieving asthma through animal experiments, and explored its mechanism using network pharmacology. The antitussive effect was detected by citric acid-induced guinea pig cough model, the expectorant effect by mouse phenol red excretion experiment and lipopolysaccharide-induced mucus hypersecretion rat model, and the antiasthmatic effect by histamine phosphate-induced guinea pig asthma model. The chemical components of FLKM were collected by TCMSP, TCMID, TCMIP, and BATMAN-TCM databases and literature search, and the potential active components were screened through ADMETlab 2.0. The targets of FLKM were obtained by STITCH, SwissTargetPrediction, and TCMSP, and the symptom targets of cough, phlegm, and asthma were acquired through SymMap database. After taking the intersection of FLKM targets and symptom targets, this study used the OECloud tool to perform Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) enrichment analysis. RESULTS:: demonstrated that FLKM 0.43-1.74 g·kg~(-1) reduced the number of coughs in guinea pigs within 3 min(P<0.05, P<0.01), and FLKM 6-12 g·kg~(-1) increased the tracheal phenol red excretion in mice(P<0.01). Moreover, FLKM 2-8 g·kg~(-1) inhibited the number of goblet cells(P<0.05, P<0.01), and FLKM 7-11.2 g·kg~(-1) prolonged the incubation period of asthma(P<0.05). A total of 115 potential active components and 910 targets of FLKM were obtained through network pharmacological analysis. FLKM had 27, 12, and 7 targets for stopping cough, eliminating phlegm, and relieving asthma, respectively. The GO and KEGG enrichment analysis found that there were commonalities and characteristics, among which cytokine-cytokine receptor interaction and infectious disease-related signaling pathway were shared. FLKM has a good effect of stopping cough, eliminating phlegm, and relieving asthma through animal experiments and network pharmacology.

The TCM Preparation Feilike Mixture for the Treatment of Pneumonia: Network Analysis, Pharmacological Assessment and Silico Simulation.

The Feilike mixture (FLKM) is a valid prescription that is frequently used to assist in the clinical treatment of pneumonia. However, the mechanisms of its effects remain unclear. First, through literature evaluation, it was preliminarily determined that FLKM improved clinical symptoms, regulated immune inflammation response and ameliorated pulmonary function. Then, via database search and literature mining, 759 targets of the 104 active compounds of FLKM were identified. The component-target (CT) network showed that the key active compositions were resveratrol, stigmasterol, beta-sitosterol, sesamin, and quercetin. 115 targets overlapped with pneumonia-related targets. The protein-protein interaction (PPI) network identified TNF, AKT1, IL6, JUN, VEGFA and MAPK3 as hub targets. KEGG analyses found that they were mainly enriched in immune related pathway. Next, in vivo experiment, we observed that FLKM ameliorated pathological injury of lung tissue and reduced neutrophil infiltration in rats with LPS-induced pneumonia. And FLKM decreased the concentration of TNF-α and IL-6 in BALF and downregulated the expression of p38MAPK, AKT and VEGFA in lung tissue. Finally, Molecular docking tests showed tight docking of these predicted targeted proteins with key active compounds. Molecular dynamics simulation was employed to assess stability and flexibility of receptor-ligand. Among them, AKT1- stigmasterol bound more stably, and their binding free energies were -47.91 ± 1.62 kcal/mol. This study revealed core compositions and targets for FLKM treating pneumonia and provided integrated pharmacological evidence to support its clinical efficacy.

[Application prospects of single-cell transcriptome sequencing in traditional Chinese medicine research].

Single-cell transcriptome sequencing(scRNA-seq) can be used to analyze the expression characteristics of the transcriptome at the level of individual cell, and discover the heterogeneity of gene expression in individual cell that is "diluted" or averaged in study of group organization. The scRNA-seq, with the characteristics of standardization, high-throughput, and high integration, can greatly simplify the experimental operation and significantly reduce the consumption of reagents. At the same time, a variety of cells are screened and the gene expression patterns are analyzed at the single-cell level to provide a more efficient detection technique and more rich and accurate information for drug research. In the field of traditional Chinese medicine(TCM), the scRNA-seq is still a new technology, but the individual and precision concepts embodied by scRNA-seq and the theory of TCM syndrome differentiation and treatment have reached the same effect between the micro and macro aspects. This study tried to broaden the thinking for the modernization of TCM by introducing the development of scRNA-seq technology and its application in modern drug research and discussing the application prospects of scRNA-seq in TCM research.