scholarly journals Systems Study on the Antirheumatic Mechanism of Tibetan Medicated-Bath Therapy Using Wuwei-Ganlu-Yaoyu-Keli

2017 ◽  
Vol 2017 ◽  
pp. 1-10
Author(s):  
Tianhong Wang ◽  
Jian Yang ◽  
Xing Chen ◽  
Kehui Zhao ◽  
Jing Wang ◽  
...  
Keyword(s):  
Mechanism Of Action ◽  
Protein Interactions ◽  
Animal Experiment ◽  
Tibetan Medicine ◽  
Network Pharmacology ◽  
Expression Data ◽  
Protein Protein Interactions ◽  
Microarray Experiments ◽  
Traditional Tibetan Medicine ◽  
Bath Therapy

In clinical practice at Tibetan area of China, Traditional Tibetan Medicine formula Wuwei-Ganlu-Yaoyu-Keli (WGYK) is commonly added in warm water of bath therapy to treat rheumatoid arthritis (RA). However, its mechanism of action is not well interpreted yet. In this paper, we first verify WGYK’s anti-RA effect by an animal experiment. Then, based on gene expression data from microarray experiments, we apply approaches of network pharmacology to further reveal the mechanism of action for WGYK to treat RA by analyzing protein-protein interactions and pathways. This study may facilitate our understanding of anti-RA effect of WGYK from perspective of network pharmacology.

scholarly journals Network Pharmacology-Based Strategy to Investigate Pharmacological Mechanisms of the Drug Pair Astragalus-Angelica for Treatment of Male Infertility

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Feng Zhao ◽  
Yingjun Deng ◽  
Guanchao Du ◽  
Shengjing Liu ◽  
Jun Guo ◽  
...  
Keyword(s):  
Male Infertility ◽  
Signaling Pathway ◽  
Mechanism Of Action ◽  
Protein Interactions ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Protein Protein Interactions ◽  
Drug Pair ◽  
Effective Components ◽  
New Ideas

Background. The traditional Chinese medicines Astragalus and Angelica are often combined to treat male infertility, but the specific therapeutic mechanism is not clear. Therefore, this study applies a network pharmacology approach to investigate the possible mechanism of action of the drug pair Astragalus-Angelica (PAA) in the treatment of male infertility. Methods. Relevant targets for PAA treatment of male infertility are obtained through databases. Protein-protein interactions (PPIs) are constructed through STRING database and screen core targets, and an enrichment analysis is conducted through the Metascape platform. Finally, molecular docking experiments were carried out to evaluate the affinity between the target protein and the ligand of PAA. Results. The active ingredients of 112 PAA, 980 corresponding targets, and 374 effective targets of PAA for the treatment of male infertility were obtained, which are related to PI3K-Akt signaling pathway, HIF-1 signaling pathway, AGE-RAGE signaling pathway, IL-17 signaling pathway, and thyroid hormone signaling pathway. Conclusion. In this study, using a network pharmacology method, we preliminarily analyzed the effective components and action targets of the PAA. We also explored the possible mechanism of action of PAA in treating male infertility. They also lay a foundation for expanding the clinical application of PAA and provide new ideas and directions for further research on the mechanisms of action of the PAA and its components for male infertility treatment.

scholarly journals Network Pharmacology study on the mechanism of MKA Polyherbal Formulation in combating Respiratory Diseases

2020 ◽  
Vol 9 (6) ◽  
pp. 385-391
Author(s):  
T Poongodi ◽  
◽  
TH Nazeema ◽  
Keyword(s):  
Mechanism Of Action ◽  
Protein Interactions ◽  
Respiratory Diseases ◽  
Functional Enrichment ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Protein Protein Interactions ◽  
Egfr Inhibition ◽  
Protein Protein Interaction ◽  
Polyherbal Formulation

The Multi-targeted action of Polyherbal formulation is responsible for enhanced therapeutic efficacy in combating various diseases. But, understanding the mode of action of herbal medicine remains a challenge because of its complex metabolomics. Network pharmacology-based approach enables to explore the mechanism of action of polyherbal formulation in biological system. In present investigation, we have explored the molecular mechanism of action of the Polyherbal formulation MKA comprising of three botanicals Mimusops elengi L., Kedrostis foetidissima (Jacq.) Cogn. and Artemisia vulgaris L. in treating respiratory diseases by network pharmacology-based approach. The protein targets were mined from Binding database for the bioactive present in MKA. The disease associated targets were identified using Open target Platform. Based on ligand-target interactions, it was interpreted that MKA could alleviate the symptoms of respiratory disease by multiple mechanisms like EGFR inhibition by Quercetin and Quercetin-3-O-rhamnoside, KDR inhibition by Quercetin, STAT-3 inhibition by β-sitosterol- β-Dglucoside, TRPV1 inhibition by phytol acetate, etc. The Protein-protein interaction (PPI) network was constructed using STRING database. KEGG pathway based functional enrichment was also predicted for the PPI network. It was found that multiple ligand-target interactions and protein-protein interactions is responsible for pharmacological activity of MKA in respiratory diseases.

scholarly journals Cloning, functional characterization, and mechanism of action of the B-cell-specific transcriptional coactivator OCA-B.

1995 ◽  
Vol 15 (8) ◽  
pp. 4115-4124 ◽  
Author(s):  
Y Luo ◽  
R G Roeder
Keyword(s):  
B Cell ◽  
Mechanism Of Action ◽  
Protein Interactions ◽  
Functional Characterization ◽  
Indirect Evidence ◽  
Transcriptional Coactivator ◽  
Protein Protein Interactions ◽  
Biochemical Purification ◽  
Activation Domain ◽  
Sequence Relationships

Biochemical purification and cognate cDNA cloning studies have revealed that the previously described transcriptional coactivator OCA-B consists of a 34- or 35-kDa polypeptide with sequence relationships to known coactivators that function by protein-protein interactions. Studies with a recombinant protein have proved that a single OCA-B polypeptide is the main determinant for B-cell-specific activation of immunoglobulin (Ig) promoters and provided additional insights into its mechanism of action. Recombinant OCA-B can function equally well with Oct-1 or Oct-2 on an Ig promoter, but while corresponding POU domains are sufficient for OCA-B interaction, and for octamer-mediated transcription of a histone H2B promoter, an additional Oct-1 or Oct-2 activation domain(s) is necessary for functional synergy with OCA-B. Further studies additional Oct-1 or Oct-2 activation domain(s) is necessary for functional synergy with OCA-B. Further studies show that Ig promoter activation by Oct-1 and OCA-B requires still other general (USA-derived) cofactors and also provide indirect evidence that distinct Oct-interacting cofactors regulate H2B transcription.

scholarly journals PrismExp: Predicting Human Gene Function by Partitioning Massive RNA-seq Co-expression Data

2021 ◽  
Author(s):  
Alexander Lachmann ◽  
Kaeli Rizzo ◽  
Alon Bartal ◽  
Minji Jeon ◽  
Daniel J. B. Clarke ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Gene Function ◽  
Covariance Structure ◽  
Tissue Type ◽  
Specific Gene ◽  
Expression Data ◽  
Rna Seq ◽  
Protein Protein Interactions ◽  
Predict Gene Function ◽  
Mammalian Genes

Gene co-expression correlations from mRNA-sequencing (RNA-seq) can be used to predict gene function based on the covariance structure that exists within such data. In the past, we showed that RNA-seq co-expression data is highly predictive of gene function and protein-protein interactions. We demonstrated that the performance of such predictions is dependent on the source of the gene expression data. Furthermore, since genes function in different cellular contexts, predictions derived from tissue-specific gene co-expression data outperform predictions derived from cross-tissue gene co-expression data. However, the identification of the optimal tissue type to maximize gene function predictions for all mammalian genes is not trivial. Here we introduce and validate an approach we term Partitioning RNA-seq data Into Segments for Massive co-EXpression-based gene function Predictions (PrismExp), for improved gene function prediction based on RNA-seq co-expression data. With coexpression data from ARCHS4, we apply PrismExp to predict a wide variety of gene functions, including pathway membership, phenotypic associations, and protein-protein interactions. PrismExp outperforms the cross-tissue co-expression correlation matrix approach on all tested domains. Hence, PrismExp can enhance machine learning methods that utilize RNA-seq coexpression correlations to impute knowledge about understudied genes and proteins.

scholarly journals Tanshinone IIA Affects the Malignant Growth of Cholangiocarcinoma Cells by Inhibiting the PI3K-Akt-mTOR Pathway

2021 ◽  
Author(s):  
Huayuan Liu ◽  
Caiyun Liu ◽  
Mengya Wang ◽  
Dongxu Sun ◽  
Pengcheng Zhu ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Tanshinone Iia ◽  
Network Pharmacology ◽  
Protein Protein Interactions ◽  
Anticancer Effects ◽  
Anti Cancer ◽  
Cholangiocarcinoma Cell ◽  
And Migration ◽  
Proliferation And Migration

Abstract Purpose: In the present study, we aimed to find the target of Tanshinone IIA (Tan-IIA) in Cholangiocarcinoma by network pharmacology-based prediction and investigate the possible mechanism through experimental verification. Methods: In this study, we combined Tan-IIA-specific and Cholangiocarcinoma-specific targets with protein-protein interactions (PPI) to construct a Tan-IIA targets-Cholangiocarcinoma network, and network pharmacology approach was applied to identify potential targets and mechanisms of Tan-IIA in the treatment of Cholangiocarcinoma. The anti-cancer effects of Tan-IIA were investigated by using subcutaneous tumorigenic model in nude mice and in the human Cholangiocarcinoma cell lines in vitro. Results: Our results showed that Tan-IIA treatment considerably suppressed the proliferation and migration of Cholangiocarcinoma cells while inducing apoptosis of Cholangiocarcinoma cells. Western blot results demonstrated that the expression of PI3K, p-Akt, p-mTOR, and mTOR were inhibited by Tan-IIA. Meanwhile, After treatment with Tan-IIA, the level of Bcl2 was downregulated and cleaved caspase-3 expression increased. Further studies revealed that the anticancer effects of Tan-IIA were severely mitigated by pretreatment with a PI3K agonist.Conclusion: Our research provides a new anticancer strategy and strengthens support for the use of Tan-IIA as an anticancer drug for the treatment of CCA.

scholarly journals Use of Network Pharmacology and Molecular Docking Technology to Analyze the Mechanism of Action of Velvet Antler in the Treatment of Postmenopausal Osteoporosis

2021 ◽  
Vol 2021 ◽  
pp. 1-22
Author(s):  
Kuiting Guo ◽  
Tiancheng Wang ◽  
Enjing Luo ◽  
Xiangyang Leng ◽  
Baojin Yao
Keyword(s):  
Postmenopausal Osteoporosis ◽  
Mechanism Of Action ◽  
Protein Interactions ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Network Pharmacology ◽  
Protein Protein Interaction ◽  
Pathway Annotation ◽  
Velvet Antler

Deer velvet antlers are the young horns of male deer that are not ossified and densely overgrown. Velvet antler and its preparations have been widely used in the treatment of postmenopausal osteoporosis (PMOP) in recent years, although its mechanism of action in the human body remains unclear. To screen the effective ingredients and targets of velvet antler in the treatment of PMOP using network pharmacology and to explore the potential mechanisms of velvet antler action in such treatments, we screened the active ingredients and targets of velvet antler in the BATMAN-TCM database. We also screened the relevant targets of PMOP in the GeneCards and OMIM databases and then compared the targets at the intersection of both velvet antler and PMOP. We used Cytoscape 3.7.2 software to construct a network diagram of “disease-drug-components-targets” and a protein-protein interaction (PPI) network through the STRING database and screened out the core targets; the R language was then used to analyze the shared targets between antler and PMOP for GO-enrichment analysis and KEGG pathway-annotation analysis. Furthermore, we used the professional software Maestro 11.1 to verify the predictive analysis based on network pharmacology. Hematoxylin-eosin (H&E) staining and micro-CT were used to observe the changes in trabecular bone tissue, further confirming the results of network pharmacological analysis. The potentially effective components of velvet antler principally include 17β-E2, adenosine triphosphate, and oestrone. These components act on key target genes such as AKT1, IL6, MAPK3, TP53, EGFR, SRC, and TNF and regulate the PI3K/Akt-signaling and MAPK-signaling pathways. These molecules participate in a series of processes such as cellular differentiation, apoptosis, metabolism, and inflammation and can ultimately be used to treat PMOP; they reflect the overall regulation, network regulation, and protein interactions.

scholarly journals Exploring the Antitumor Mechanisms of Zingiberis Rhizoma Combined with Coptidis Rhizoma Using a Network Pharmacology Approach

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Meng Wang ◽  
Youke Qi ◽  
Yongning Sun
Keyword(s):  
Gene Expression ◽  
Molecular Docking ◽  
Protein Interactions ◽  
Disease Free Survival ◽  
Network Pharmacology ◽  
Protein Protein Interactions ◽  
Active Components ◽  
Antitumor Effects ◽  
Coptidis Rhizoma ◽  
Underlying Mechanisms

Background. Although the combination of Zingiberis rhizoma (ZR) and Coptidis rhizoma (CR) is a classic traditional Chinese medicine-based herbal pair used for its antitumor effect, the material basis and underlying mechanisms are unclear. Here, a network pharmacology approach was used to elucidate the antitumor mechanisms of ZR-CR. Materials and Methods. To predict the targets of ZR-CR in treating tumors, we constructed protein–protein interactions and hub component-target networks and performed pathway and process enrichment and molecular docking analysis. We used a surface plasmon resonance (SPR) assay to validate the predicted component-target affinities. Hub gene expression and survival analysis in patients with tumors were used to predict the clinical significance. Results. The active components of ZR-CR—shogaol, daucosterol, ginkgetin, berberine, quercetin, chlorogenic acid, and vanillic acid—exhibited antitumor activities via the MAPK, PI3K-AKT, TNF, FOXO, HIF-1, and VEGF signaling pathways. Molecular docking and SPR analyses suggested direct binding of berberine with AKT1 and TP53; quercetin with EGFR and VEGF165; and ginkgetin, isoginkgetin, and daucosterol with VEGF165 with weak affinities. Gene expression levels of the hub targets of ZR-CR were associated with overall survival and disease-free survival in patients with various tumor types. Conclusions. The antitumor components of the ZR-CR herbal pair and the mechanisms underlying their antitumor effects were identified. These antitumor components deserve to be explored further in experimental and clinical studies.

Sign in / Sign up

Export Citation Format

Share Document