Deciphering the Active Ingredients and Molecular Mechanisms of Tripterygium hypoglaucum (Levl.) Hutch against Rheumatoid Arthritis Based on Network Pharmacology

Tripterygium hypoglaucum (Levl.) Hutch (THH) shows well clinical effect on rheumatoid arthritis (RA), but the active ingredients and molecular mechanisms remain unclear. This work was designed to explore these issues by network pharmacology. Compounds from THH were gathered by retrieving literatures. Compound-related and RA-related genes were identified using databases, and the overlapping genes were identified by Venn diagram. The active ingredients and genes of THH against RA were confirmed by dissecting interactions between overlapping genes and compounds using Cytoscape. SystemsDock website was used to further verify the combining degree of key genes with active ingredients. Pathway enrichment analysis was performed to decipher the mechanisms of THH against RA by Database for Annotation, Visualization and Integrated Discovery. A total of 123 compounds were collected, and 110 compounds-related and 1871 RA-related genes were identified, including 64 overlapping genes. The target genes and active ingredients of THH against RA comprised 64 genes and 17 compounds, the focus of which was PTGS2, triptolide, and celastrol. SystemsDock website indicated that the combing degree of PTGS2 with triptolide or celastrol was very good. The mechanisms of THH against RA were linked to 31 signaling pathways, and the key mechanism was related to inhibition of inflammation response through inactivating TNF and NF-kappa B signaling pathways. This work firstly explored the active ingredients and mechanisms of THH against RA by network pharmacology and provided evidence to support clinical effects of THH on RA.

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Network Pharmacology Identifies the Mechanisms of Sang-Xing-Zhi-Ke-Fang against Pharyngitis

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2020/2421916 ◽

2020 ◽

Vol 2020 ◽

pp. 1-12

Author(s):

Yinhe Deng ◽

Quanjiang Li ◽

Menglin Li ◽

Tiantian Han ◽

Guixian Li ◽

...

Keyword(s):

Signaling Pathway ◽

Influenza A ◽

Molecular Mechanisms ◽

Mapk Signaling ◽

Venn Diagram ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Ras Signaling ◽

Clinical Effects ◽

Overlapping Genes

Background. Sang-Xing-Zhi-Ke-Fang (SXZKF) demonstrates good therapeutic effect against pharyngitis. Nevertheless, the pharmacological mechanism underlying its effectiveness is still unclear. Objective. To investigate the underlying mechanisms of SXZKF against pharyngitis using network pharmacology method. Methods. Bioactive ingredients of SXZKF were collected and screened using published literature and two public databases. Using four public databases, the overlapping genes between these bioactive compound-related and pharyngitis-related genes were identified by Venn diagram. Protein-protein interaction (PPI) was obtained using “Search Tool for the Retrieval of Interacting Genes (STRING)” database. “Database for Annotation, Visualization, and Integrated Discovery ver. 6.8 (DAVID 6.8)” was used to perform Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis to explore the molecular mechanisms of SXZKF against pharyngitis. Finally, Cytoscape 3.7.2 software was used to construct and visualize the networks. Result. A total of 102 bioactive compounds were identified. Among them, 886 compounds-related and 6258 pharyngitis-related genes were identified, including 387 overlapping genes. Sixty-three core targets were obtained, including ALB, PPARγ, MAPK3, EGF, and PTGS2. Signaling pathways closely related to mechanisms of SXZKF for pharyngitis were identified, including serotonergic synapse, VEGF signaling pathway, Fc epsilon RI signaling pathway, Ras signaling pathway, MAPK signaling pathway, and influenza A. Conclusion. This is the first identification of in-depth study of SXZKF against pharyngitis using network pharmacology. This new evidence could be informative in providing new support on the clinical effects of SXZKF on pharyngitis and for the development of personalized medicine for pharyngitis.

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Network pharmacology to investigate the pharmacological mechanisms of muscone in Xingnaojing injections for the treatment of severe traumatic brain injury

PeerJ ◽

10.7717/peerj.11696 ◽

2021 ◽

Vol 9 ◽

pp. e11696

Author(s):

Zhuohang Liu ◽

Hang Li ◽

Wenchao Ma ◽

Shuyi Pan

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

Chinese Medicine ◽

Signaling Pathways ◽

Neuronal Apoptosis ◽

Molecular Mechanisms ◽

Venn Diagram ◽

Network Pharmacology ◽

Active Ingredients ◽

Hub Proteins

Background Xingnaojing injections (XNJI) are widely used in Chinese medicine to mitigate brain injuries. An increasing number of studies have shown that XNJI may improve neurological function. However, XNJI’s active ingredients and molecular mechanisms when treating traumatic brain injury (TBI) are unknown. Methods XNJI’s chemical composition was acquisited from literature and the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. We used the “absorption, distribution, metabolism, and excretion” (ADME) parameter-based virtual algorithm to further identify the bioactive components. We then screened data and obtained target information regarding TBI and treatment compounds from public databases. Using a Venn diagram, we intersected the information to determine the hub targets. Cytoscape was used to construct and visualize the network. In accordance with the hub proteins, we then created a protein–protein interaction (PPI) network using STRING 11.0. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were analyzed according to the DAVID bioinformatics resource database (ver. 6.8). We validated the predicted compound’s efficacy using the experimental rat chronic constriction injury (CCI) model. The neuronal apoptosis was located using the TUNEL assay and the related pathways’ hub proteins were determined by PCR, Western blot, and immunohistochemical staining. Results We identified 173 targets and 35 potential compounds belonging to XNJI. STRING analysis was used to illustrate the protein–protein interactions and show that muscone played a fundamental role in XNJI’s efficacy. Enrichment analysis revealed critical signaling pathways in these components’ potential protein targets, including PI3K/AKT1, NF-kB, and p53. Moreover, the hub proteins CASP3, BCL2L1, and CASP8 were also involved in apoptosis and were associated with PI3K/AKT, NF-kB, and p53 signaling pathways. We showed that muscone and XNJI were similarly effective 168 h after CCI, demonstrating that the muscone in XNJI significantly attenuated neuronal apoptosis through the PI3K/Akt1/NF-kB/P53 pathway. Conclusion We verified the neuroprotective mechanism in muscone for the first time in TBI. Network pharmacology offers a new approach for identifying the potential active ingredients in XNJI.

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Network Pharmacology-Based Prediction of Active Ingredients and Mechanisms of Tongxinluo Against Acute Myocardial Infarction

10.21203/rs.3.rs-673133/v1 ◽

2021 ◽

Author(s):

Meng-Jin Hu ◽

Gui-Hao Chen ◽

Yue-Jin Yang

Keyword(s):

Myocardial Infarction ◽

Acute Myocardial Infarction ◽

Scientific Evidence ◽

Interaction Network ◽

Enrichment Analysis ◽

Venn Diagram ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Overlapping Genes ◽

Active Ingredients

Abstract Purpose: The aim of this network pharmacology was to explore the potential active ingredients and mechanisms of Tongxinluo (TXL) against acute myocardial infarction (AMI).Methods: We selected active ingredients and targets of TXL according to TCMSP database and converted protein targets into gene symbol by UniProt database. Therapeutic gene targets on AMI were collected from DisGeNET and GeneCards databases. The overlapping genes between ingredients and AMI were identified using Venn diagram. Then, the interaction network between ingredients and overlapping genes was constructed, visualized, and analyzed by Cytoscape software. Protein-protein interaction (PPI) was analyzed by String database. Finally, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of overlapping genes were carried out by metascape platform.Results: A total of 111 active ingredients, 184 ingredient-related genes, and 1020 AMI-related genes were retrieved using public databases. Eventually, 79 overlapping genes between TXL and AMI were identified. Cytoscape and PPI results suggested that the active ingredients and genes of TXL against AMI consisted of 66 active ingredients and 79 genes, among them beta-sitosterol and IL-6 were the uppermost active ingredient and hub gene, respectively. Metascape results exhibited that the key mechanism of TXL against AMI might be reducing oxidative stress in cell membrane by inactivating pathways in cancer.Conclusion: This network pharmacology study reveals potential mechanisms of multi-target and multi-component TXL in the treatment of AMI, providing scientific evidence for further expounding the active ingredients and mechanisms of TXL against AMI.

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Analysis of the Molecular Mechanisms of the Effects of Prunella vulgaris against Subacute Thyroiditis Based on Network Pharmacology

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2020/9810709 ◽

2020 ◽

Vol 2020 ◽

pp. 1-13

Author(s):

Xin Shen ◽

Rui Yang ◽

Jianpeng An ◽

Xia Zhong

Keyword(s):

Signaling Pathways ◽

Molecular Mechanisms ◽

Kegg Pathway ◽

Enrichment Analysis ◽

Subacute Thyroiditis ◽

Network Pharmacology ◽

Pharmacokinetic Parameters ◽

Pathway Enrichment Analysis ◽

Prunella Vulgaris ◽

Protein Protein Interaction

Prunella vulgaris (PV) has a long history of application in traditional Chinese and Western medicine as a remedy for the treatment of subacute thyroiditis (SAT). This study applied network pharmacology to elucidate the mechanism of the effects of PV against SAT. Components of the potential therapeutic targets of PV and SAT-related targets were retrieved from databases. To construct a protein-protein interaction (PPI) network, the intersection of SAT-related targets and PV-related targets was input into the STRING platform. Gene ontology (GO) analysis and KEGG pathway enrichment analysis were carried out using the DAVID database. Networks were constructed by Cytoscape for visualization. The results showed that a total of 11 compounds were identified according to the pharmacokinetic parameters of ADME. A total of 126 PV-related targets and 2207 SAT-related targets were collected, and 83 overlapping targets were subsequently obtained. The results of the KEGG pathway and compound-target-pathway (C-T-P) network analysis suggested that the anti-SAT effect of PV mainly occurs through quercetin, luteolin, kaempferol, and beta-sitosterol and is most closely associated with their regulation of inflammation and apoptosis by targeting the PIK3CG, MAPK1, MAPK14, TNF, and PTGS2 proteins and the PI3K-Akt and TNF signaling pathways. The study demonstrated that quercetin, luteolin, kaempferol, and beta-sitosterol in PV may play a major role in the treatment of SAT, which was associated with the regulation of inflammation and apoptosis, by targeting the PI3K-Akt and TNF signaling pathways.

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Network Pharmacology Analysis on the Mechanism of Huangqi Sijunzi Decoction in Treating Cancer-Related Fatigue

Journal of Healthcare Engineering ◽

10.1155/2021/9780677 ◽

2021 ◽

Vol 2021 ◽

pp. 1-10

Author(s):

Yixin Cui ◽

Haiming Wang ◽

Decai Wang ◽

Jiwei Mi ◽

Gege Chen ◽

...

Keyword(s):

Topological Analysis ◽

Enrichment Analysis ◽

Venn Diagram ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Active Ingredients ◽

Protein Protein Interaction ◽

Kegg Pathways ◽

Cancer Related Fatigue ◽

Tumor Gene Expression

Objective. This study aimed to determine the active ingredients of Huangqi Sijunzi Decoction (HQSJZD) and the targets in treating cancer-related fatigue (CRF) so as to investigate the treatment mechanism of HQSJZD for CRF. Methods. This study adopted the method of network pharmacology. The active ingredients and targets of HQSJZD were retrieved, and the targets of HQSJZD in treating CRF were obtained using a Venn diagram. Next, a protein-protein interaction (PPI) network was constructed using the String database. The core targets of HQSJZD in treating CRF were identified through topological analysis, and functional annotation analysis and pathway enrichment analysis were carried out. Subsequently, a compound-disease-target regulatory network was constructed using Cystoscape 3.8.0 software. Results. A total of 250 targets of HQSJZD ingredients, 1447 CRF-related genes, and 144 common targets were obtained. Through topological analysis, 61 core targets were screened. Bioinformatics annotation of these genes identified 2366 gene ontology (GO) terms and 172 enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Conclusion. The active ingredients in HQSJZD, that is, quercetin, luteolin, kaempferol, and naringenin, may act on AKT1, IL-6, VEGFA, MAPK3, CASP3, JUN, and EGFR to regulate the PI3K-Akt, TNF, and IL-17 signaling pathways, thereby suppressing inflammatory response, tumor gene expression, and tumor angiogenesis to treat CRF. This study investigated the pharmacological basis and mechanism of HQSJZD in the treatment of CRF using systematic pharmacology, which provides an important reference for further elucidation of the anti-CRF mechanism and clinical applications of HQSJZD, and also provides a method protocol for similar studies in the future.

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Therapeutic mechanism of Toujie Quwen granules in COVID-19 based on network pharmacology

BioData Mining ◽

10.1186/s13040-020-00225-8 ◽

2020 ◽

Vol 13 (1) ◽

Author(s):

Ying Huang ◽

Wen-jiang Zheng ◽

Yong-shi Ni ◽

Mian-sha Li ◽

Jian-kun Chen ◽

...

Keyword(s):

Chinese Medicine ◽

Signaling Pathways ◽

Signaling Pathway ◽

Mapk Signaling ◽

Venn Diagram ◽

Network Pharmacology ◽

Active Ingredients ◽

Integrated Network ◽

Therapeutic Mechanism ◽

The World

Abstract Background Chinese medicine Toujie Quwen granule (TJQW) has proven to be effective in the treatment of mild coronavirus disease 2019 (COVID-19) cases by relieving symptoms, slowing the progression of the disease, and boosting the recovery of patients. But the bioactive compounds and potential mechanisms of TJQW for COVID-19 prevention and treatment are unclear. This study aimed to explore the potential therapeutic mechanism of TJQW in coronavirus disease 2019 (COVID-19) based on an integrated network pharmacology approach. Methods TCMSP were used to search and screen the active ingredients in TJQW. The Swiss TargetPrediction was used to predict the potential targets of active ingredients. Genes co-expressed with ACE2 were considered potential therapeutic targets on COVID-19. Venn diagram was created to show correlative targets of TJQW against COVID-19. Cytoscape was used to construct a “drug-active ingredient-potential target” network, STRING were used to construct protein-protein interaction network, and cytoHubba performed network topology analysis. Enrichment of biological functions and signaling pathways of core targets was performed by using the clusterProfiler package in R software and ClueGO with CluePedia plugins in Cytoscape. Results A total of 156 active ingredients were obtained through oral bioavailability and drug-likeness screenings. Two hundred twenty-seven potential targets of TJQW were related to COVID-19. The top ten core targets are EGFR, CASP3, STAT3, ESR1, FPR2, F2, BCL2L1, BDKRB2, MPO, and ACE. Based on that, we obtained 19 key active ingredients: umbelliprenin, quercetin, kaempferol, luteolin, praeruptorin E, stigmasterol, and oroxylin A. And the enrichment analysis obtained multiple related gene ontology functions and signaling pathways. Lastly, we constructed a key network of “drug-component-target-biological process-signaling pathway”. Our findings suggested that TJQW treatment for COVID-19 was associated with elevation of immunity and suppression of inflammatory stress, including regulation of inflammatory response, viral process, neutrophil mediated immunity, PI3K-Akt signaling pathway, MAPK signaling pathway, Jak-STAT signaling pathway, Complement and coagulation cascades, and HIF-1 signaling pathway. Conclusions Our study uncovered the pharmacological mechanism underlying TJQW treatment for COVID-19. These results should benefit efforts for people around the world to gain more knowledge about Chinese medicine TJQW in the treatment of this vicious epidemic COVID-19, and help to address this pressing problem currently facing the world.

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Exploring the Mechanisms Underlying the Therapeutic Effect of Salvia Miltiorrhiza Against Diabetic Nephropathy Using Network Pharmacology and Molecular Docking

10.21203/rs.3.rs-85980/v1 ◽

2020 ◽

Author(s):

Li-Li Zhang ◽

Lin Han ◽

Xin-Miao Wang ◽

Yu Wei ◽

Jing-Hui Zheng ◽

...

Keyword(s):

Diabetic Nephropathy ◽

Molecular Docking ◽

Therapeutic Effect ◽

Molecular Mechanisms ◽

Function Analysis ◽

Salvia Miltiorrhiza ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Ppi Network ◽

Active Ingredients

Abstract BackgroundThe mechanisms underlying the therapeutic effect of Salvia Miltiorrhiza (SM) against diabetic nephropathy (DN) using systematic network pharmacology and molecular docking methods were examined.MethodsTCMSP database was used to screen the active ingredients of SM. Gene targets were obtained using Swiss Target Prediction and TCMSP databases. Related targets of DN were retrieved from the Genecards and DisGeNET databases. Next, a PPI network was constructed using the common targets of SM-DN in the STRING database. The Metascape platform was used for GO function analysis and Cytoscape plug-in ClueGO was used for KEGG pathway enrichment analysis. Molecular docking was performed using iGEMDOCK and AutoDock Vina software. Pymol and LigPlos were used for mapping the network. ResultsSixty-six active ingredients and 189 targets were screened from SM. Among them, 64 targets overlapped with DN targets. The PPI network diagram revealed that AKT1, VEGFA, IL6, TNF, MAPK1, TP53, EGFR, STAT3, MAPK14, and JUN were the top 10 relevant targets. GO and KEGG analyses mainly focused on advanced glycation end products, oxidative stress, inflammatory response, and immune regulation. Molecular docking revealed that the potential target genes closely related to DN, including TNF, NOS2, and AKT1, were more stable in combination with salvianolic acid B, and their stability was better than that of tanshinone IIA.ConclusionThis study reveals the active components and potential molecular mechanisms involved in the therapeutic effect of SM against DN and provides a reference for the wide application of SM in clinically managing DN.

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Use of Network Pharmacology to Investigate the Mechanism of the Compound Xuanju Capsule in the Treatment of Rheumatoid Arthritis

BioMed Research International ◽

10.1155/2021/5568791 ◽

2021 ◽

Vol 2021 ◽

pp. 1-14

Author(s):

Wenyang Wei ◽

Wanpeng Lu ◽

Xiaolong Chen ◽

Yunfeng Yang ◽

Mengkai Zheng

Keyword(s):

Rheumatoid Arthritis ◽

Signaling Pathways ◽

Active Ingredient ◽

Network Pharmacology ◽

Ppi Network ◽

Active Ingredients ◽

Related Disease ◽

Ppi Networks ◽

Target Network ◽

The Common

Objective. To clarify the therapeutic mechanisms of compound Xuanju capsule-treated rheumatoid arthritis (RA) based on network pharmacology tactics. Method. The TCMSP, TCMID and STITCH databases were used to screen the active ingredients and targets in the compound Xuanju capsule; the OMIM, TTD, PharmGKB and GeneCards databases were applied to screen the RA-related disease targets. Then, the obtained targets were imported into Cytoscape 3.7.1 software to construct the active ingredient-target network and the RA-related disease-target network. The active ingredient-target PPI network, the RA-related disease-target PPI network and the common target PPI network were built by using the STRING platform and Cytoscape 3.7.1 software. The GO and KEGG analyses of the common targets were analyzed by using the Metascape and Bioinformatics online tools. Results. A total of 51 active ingredients and 513 corresponding ingredient targets were harvested from the compound Xuanju capsule; 641 RA-related disease targets were obtained. After two PPI networks were constructed and merged, 116 RA-related targets of compound Xuanju capsules were identified and analyzed. 116 RA-related targets of compound Xuanju capsules are mainly involved in the biological processes and molecular functions, such as the cytokine-mediated signaling pathways, the response to lipopolysaccharide and the blood vascular development, the cytokine activity, the cytokine receptor binding and the receptor regulator activity. Furthermore, 116 RA-related targets of compound Xuanju capsules are concentrated in signaling pathways such as the IL-17, TNF, Th17 cell differentiation, Toll receptor and RA signaling pathway. Conclusion. The compound Xuanju capsule had the action characteristics of multiple components, multiple targets, and multiple pathways in the treatment of RA, which might primarily reduce the release of proinflammatory factors (such as IL-6 and TNF-α) and increase the production of anti-inflammatory factors (such as IL-10) by regulating inflammation-related signaling pathways (such as IL-17), thereby alleviating the inflammatory damage and improving the bone tissue repair.

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A network pharmacology analysis on drug-like compounds from Ganoderma lucidum for alleviation of Atherosclerosis

10.21203/rs.3.rs-236410/v1 ◽

2021 ◽

Author(s):

Ki Kwang Oh ◽

Md. Adnan ◽

Dong Ha Cho

Keyword(s):

Signaling Pathways ◽

Signaling Pathway ◽

Ganoderma Lucidum ◽

Mapk Signaling ◽

Mendelian Inheritance ◽

Chronic Inflammatory Disease ◽

Mapk Signaling Pathway ◽

Venn Diagram ◽

Network Pharmacology ◽

Overlapping Genes

Abstract Background: Ganoderma lucidum (GL) is known as a potent alleviator against chronic inflammatory disease like atherosclerosis (AS), but its critical bioactive compounds and their mechanisms against AS have not been unveiled. This research aimed to identify the key compounds(s) and mechanism(s) of GL against AS through network pharmacology.Methods: The compounds from GL were identified by gas chromatography-mass spectrum (GC-MS), and SwissADME screened their physicochemical properties. Then, the gene(s) associated with the screened compound(s) or AS related genes were identified by public databases, and we selected the overlapping genes using a Venn diagram. The networks between overlapping genes and compounds were visualized, constructed, and analyzed by RStudio. Finally, we performed molecular docking test (MDT) to identify key gene(s), compound(s) on AutoDockVina.Results: A total of 35 compounds in GL was detected via GC-MS, and 34 compounds (accepted by the Lipinski's rule) were selected as drug-like compounds (DLCs). A total of 34 compounds were connected to the number of 785 genes and 2,606 AS-related genes were identified by DisGeNET and Online Mendelian Inheritance in Man (OMIM). The final 98 overlapping genes were extracted between the compounds-genes network and AS-related genes. On Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, the number of 27 signaling pathways were sorted out, and a hub signaling pathway (MAPK signaling pathway), a core gene (PRKCA), and a key compound (Benzamide, 4-acetyl-N-(2,6-dimethylphenyl)) were selected among the 27 signaling pathways via MDT. Conclusion: Overall, we found that the identified 3 DLCs from GL have potent anti-inflammatory efficacy, improving AS by inactivating the MAPK signaling pathway.

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Network Pharmacology Analysis of the Identification of Phytochemicals and Therapeutic Mechanisms of Paeoniae Radix Alba for the Treatment of Asthma

Journal of Immunology Research ◽

10.1155/2021/9659304 ◽

2021 ◽

Vol 2021 ◽

pp. 1-11

Author(s):

Jingwei Wang ◽

Ling Peng ◽

Lu Jin ◽

Huiying Fu ◽

Qiyang Shou

Keyword(s):

Enrichment Analysis ◽

Biological Information ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Clinical Effects ◽

Active Ingredients ◽

Annotation Database ◽

Kegg Pathways ◽

Therapeutic Mechanisms ◽

Paeoniae Radix

Background. Paeoniae Radix Alba (PRA), the root of the plant Paeonia lactiflora Pall., has been suggested to play an important role for the treatment of asthma. A biochemical understanding of the clinical effects of Paeoniae Radix Alba is needed. Here, we explore the phytochemicals and therapeutic mechanisms via a systematic and comprehensive network pharmacology analysis. Methods. Through TCMSP, PubChem, GeneCards database, and SwissTargetPrediction online tools, potential targets of active ingredients from PRA for the treatment of asthma were obtained. Cytoscape 3.7.2 was used to determine the target of active ingredients of PRA. Target protein interaction (PPI) network was constructed through the STRING database. The Gene Ontology (GO) biological process and Kyoto Encyclopedia of Genes and Genes (KEGG) pathway enrichment analysis were analyzed through the biological information annotation database (DAVID). Results. Our results indicate that PRA contains 21 candidate active ingredients with the potential to treat asthma. The enrichment analysis of GO and KEGG pathways found that the treatment of asthma by PRA may be related to the process of TNF (tumor necrosis factor) release, which can regulate and inhibit multiple signaling pathways such as ceramide signaling. Conclusions. Our work provides a phytochemical basis and therapeutic mechanisms of PRA for the treatment of asthma, which provides new insights on further research on PRA.

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