scholarly journals Exploring the Comorbidity Mechanisms Between Asthma and Idiopathic Pulmonary Fibrosis and the Pharmacological Mechanisms of Bu-Shen-Yi-Qi Decoction Therapy via Network Pharmacology

2021 ◽  
Author(s):  
Yuanyuan Zhong ◽  
Lingli Hu ◽  
Wenjing Chen ◽  
Bin Wang ◽  
Jingcheng Dong ◽  
...  
Keyword(s):  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Complex Molecule ◽  
Network Pharmacology ◽  
Active Ingredients ◽  
Core Potential ◽  
Potential Binding ◽  
The Common ◽  
Molecule Docking ◽  
Related Proteins

Abstract Backgrounds. Asthma and idiopathic pulmonary fibrosis (IPF) are common chronic diseases of the respiratory system in clinical practice. However, the relationship and molecular links between them remain unclear, and the current treatment's efficacy is disappointing. Bu-Shen-Yi-Qi (BSYQ) decoction has clinically proved to be effective in treating various chronic airway inflammatory diseases, including asthma and IPF. But the underlying pharmacological mechanisms are still to be elucidated. Methods. This study searched the proteins related to asthma and IPF via TTD, CTD, and DisGeNET database. We then submitted them to the STRING database to establish the protein-protein interaction (PPI) network. The co-bioinformatics analysis was conducted by Metascape. The active ingredients of BSYQ decoction were screened from TCMSP，ETCM，BATMAN-TCM database and HPLC/MS experiment. Then we predicted the corresponding targets based on TCMSP，ETCM, and BATMAN-TCM database. The common targets for asthma and IPF treatment were recognized, and further GO and KEGG analyses were conducted with the DAVID platform. Finally, molecule docking via Autodock Vina was employed to predict the potential binding mode between core potential compounds and targets.Results. One thousand three hundred thirty-three asthma-related targets and 404 IPF-related proteins were retrieved, 120 were overlapped between them, and much of the asthma-related proteins fall into the same statistically significant GO terms with IPF. One hundred sixteen active ingredients of BSYQ decoction were acquired, and 1535 corresponding targets were retrieved. Eighty-three potential compounds and 56 potential targets were recognized for both asthma and IPF treatment. GO and KEGG analysis indicated that the inflammation response, cytokine production, leukocyte differentiation, oxygen level response, etc., were the common pathological processes in asthma and IPF, which were regulated by BSYQ decoction. Molecule docking further predicted the potential binding modes between the core potential compounds and targets.Conclusion. The current study successfully clarified the complex molecule links between asthma and IPF and found the potential common targets between them. Then we demonstrated the efficacy of BSYQ decoction for asthma and IPF treatment from the angle of network pharmacology, which may provide valuable references for further studies and clinical use.

scholarly journals Network Pharmacology-Based Study on the Mechanism of Aloe Vera for Treating Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Jing Xie ◽  
Jun Wu ◽  
Sihui Yang ◽  
Huaijun Zhou
Keyword(s):  
Molecular Docking ◽  
Drug Targets ◽  
Aloe Vera ◽  
Beta Carotene ◽  
Network Pharmacology ◽  
Potential Mechanism ◽  
Active Ingredients ◽  
Protein Protein Interaction ◽  
Target Network ◽  
Molecule Docking

Background. Aloe vera has long been considered an anticancer herb in different parts of the world. Objective. To explore the potential mechanism of aloe vera in the treatment of cancer using network pharmacology and molecule docking approaches. Methods. The active ingredients and corresponding protein targets of aloe vera were identified from the TCMSP database. Targets related to cancer were obtained from GeneCards and OMIM databases. The anticancer targets of aloe vera were obtained by intersecting the drug targets with the disease targets, and the process was presented in the form of a Venn plot. These targets were uploaded to the String database for protein-protein interaction (PPI) analysis, and the result was visualized by Cytoscape software. Go and KEGG enrichment were used to analyze the biological process of the target proteins. Molecular docking was used to verify the relationship between the active ingredients of aloe vera and predicted targets. Results. By screening and analyzing, 8 active ingredients and 174 anticancer targets of aloe vera were obtained. The active ingredient-anticancer target network constructed by Cytoscape software indicated that quercetin, arachidonic acid, aloe-emodin, and beta-carotene, which have more than 4 gene targets, may play crucial roles. In the PPI network, AKT1, TP53, and VEGFA have the top 3 highest values. The anticancer targets of aloe vera were mainly involved in pathways in cancer, prostate cancer, bladder cancer, pancreatic cancer, and non-small-cell lung cancer and the TNF signaling pathway. The results of molecular docking suggested that the binding ability between TP53 and quercetin was the strongest. Conclusion. This study revealed the active ingredients of aloe vera and the potential mechanism underlying its anticancer effect based on network pharmacology and provided ideas for further research.

scholarly journals Mechanism of Fei-Xian Formula in the Treatment of Pulmonary Fibrosis on the Basis of Network Pharmacology Analysis Combined with Molecular Docking Validation

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Xiao-Li Chen ◽  
Cheng Tang ◽  
Qing-Ling Xiao ◽  
Zhong-Hua Pang ◽  
Dan-Dan Zhou ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Virus Infection ◽  
Pulmonary Fibrosis ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Core Network ◽  
Active Ingredients ◽  
Molecular Docking Study ◽  
The Core ◽  
Target Network

Objective. This study aimed to clarify the mechanism of Fei-Xian formula (FXF) in the treatment of pulmonary fibrosis based on network pharmacology analysis combined with molecular docking validation. Methods. Firstly, ingredients in FXF with pharmacological activities, together with specific targets, were identified based on the BATMA-TCM and TCMSP databases. Then, targets associated with pulmonary fibrosis, which included pathogenic targets as well as those known therapeutic targets, were screened against the CTD, TTD, GeneCards, and DisGeNet databases. Later, Cytoscape was employed to construct a candidate component-target network of FXF for treating pulmonary fibrosis. In addition, for nodes within the as-constructed network, topological parameters were calculated using CytoHubba plug-in, and the degree value (twice as high as the median degree value for all the nodes) was adopted to select core components as well as core targets of FXF for treating pulmonary fibrosis, which were subsequently utilized for constructing the core network. Furthermore, molecular docking study was carried out on those core active ingredients together with the core targets using AutoDock Vina for verifying results of network pharmacology analysis. At last, OmicShare was employed for enrichment analysis of the core targets. Results. Altogether 12 active ingredients along with 13 core targets were identified from our constructed core component-target network of FXF for the treatment of pulmonary fibrosis. As revealed by enrichment analysis, the 13 core targets mostly concentrated in regulating biological functions, like response to external stimulus (from oxidative stress, radiation, UV, chemical substances, and virus infection), apoptosis, cell cycle, aging, immune process, and protein metabolism. In addition, several pathways, like IL-17, AGE-RAGE, TNF, HIF-1, PI3K-AKT, NOD-like receptor, T/B cell receptor, and virus infection-related pathways, exerted vital parts in FXF in the treatment of pulmonary fibrosis. Conclusions. FXF can treat pulmonary fibrosis through a “multicomponent, multitarget, and multipathway” mean. Findings in this work lay foundation for further exploration of the FXF mechanism in the treatment of pulmonary fibrosis.

scholarly journals A Network Pharmacology Approach to Explore the Potential Mechanisms of Yifei Sanjie Formula in Treating Pulmonary Fibrosis

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Bo Qiao ◽  
Yueying Wu ◽  
Xiaoya Li ◽  
Zhenyuan Xu ◽  
Weigang Duan ◽  
...  
Keyword(s):  
Pulmonary Fibrosis ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Cell Receptor ◽  
Network Pharmacology ◽  
Active Ingredients ◽  
Kegg Pathways ◽  
Th17 Cell Differentiation ◽  
Associated Proteins ◽  
Cellular Components

Objective. Yifei Sanjie Formula (YFSJF) is an effective formula on pulmonary fibrosis (PF), which has been used in clinic for more than 30 years. In order to investigate the molecular mechanism of YFSJF in treating PF, network pharmacology was used to predict the cooperative ingredients and associated pathways. Methods. Firstly, we collected potential active ingredients of YFSJF by TCMSP databases. Secondly, we obtained PF-associated targets through OMIM and Genecards database. Finally, metascape was applied for the analysis of GO terms and KEGG pathways. Results. We screened out 76 potential active ingredients and 98 associated proteins. A total of 5715 items were obtained by GO enrichment analysis ( P < 0.05 ), including 4632 biological processes, 444 cellular components, and 639 molecular functions. A total of 143 related KEGG pathways were enriched ( P < 0.05 ), including IL-17 signaling pathway, T cell receptor signaling pathway, TNF signaling pathway, calcium signaling pathway, TH17 cell differentiation, HIF-1 signaling pathway, and PI3K-Akt signaling pathway. Conclusion. YFSJF can interfere with immune and inflammatory response through multiple targets and pathways, which has a certain role in the treatment of PF. This study lays a foundation for future experimental research.

Repurposing anticancer drugs for the treatment of idiopathic pulmonary fibrosis and antifibrotic drugs for the treatment of cancer: state of the art

2020 ◽  
Vol 27 ◽  
Author(s):  
Panagiotis Paliogiannis ◽  
Sara Solveig Fois ◽  
Alessandro Giuseppe Fois ◽  
Antonio Cossu ◽  
Giuseppe Palmieri ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
State Of The Art ◽  
Future Research ◽  
Clinical Aspects ◽  
Research Perspectives ◽  
Combined Use ◽  
The Common ◽  
Antifibrotic Drugs

: Idiopathic pulmonary fibrosis (IPF) is an aggressive pulmonary disease which shares several molecular, patho-physiological and clinical aspects with lung cancer, including high mortality rates. The anti-fibrotic drugs Nintedanib and Pirfenidone have been recently introduced in clinical practice for the treatment of IPF. Nintedanib is also used for the treatment of several malignancies, including non-small cell lung cancer (NSCLC) in combination with Docetaxel, while Pirfenidone showed some anti-neoplastic effects in preclinical studies. On the other hand, novel targeted agents and immunotherapies have been introduced in the last decade for the treatment of NSCLC, and some of them showed anti-fibrotic properties in recent studies. These evidences, based on the common pathophysiological backgrounds of IPF and lung cancer, make possible the mutual or combined use of anti-fibrotic and anti-neoplastic drugs to treat these highly lethal diseases. The aim of the present review is to depict the current scientific landscape regarding the repurposing of anti-neoplastic drugs in IPF and antifibrotic drugs in lung cancer, and to identify future research perspectives on the topic.

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

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.

scholarly journals IDIOPATHIC PULMONARY FIBROSIS. CORRECTION OF ERRORS

2018 ◽  
Vol 99 (5) ◽  
pp. 269-278
Author(s):  
A. L. Yudin ◽  
Yu. A. Abovich ◽  
N. I. Afanas’eva
Keyword(s):  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Usual Interstitial Pneumonia ◽  
Concept Of Disease ◽  
Computer Tomographic ◽  
X Ray ◽  
Common Causes ◽  
Causes Of Errors ◽  
The Common ◽  
Made In

Substantial changes have been recently made in the concept of the diagnosis of idiopathic pulmonary fibrosis. The concept of disease pathogenesis and the pathomorphologic criteria for diagnosing usual interstitial pneumonia have been revised. All idiopathic pulmonary fibrosis treatments that existed prior to 2011 have been found to be ineffective. This article analyzes the currently existing computer tomographic criteria for the diagnosis and differential diagnosis of idiopathic pulmonary fibrosis and considers the common causes of errors and the possibilities of improving the existing X-ray criteria.

scholarly journals A Network Pharmacology Approach and Molecular Docking Technology to Uncover the Potential Molecular Mechanism of Astragalus -Scorpion on Prostate Cancer

2021 ◽  
Author(s):  
Litong Wu ◽  
Ying Chen ◽  
Mingjing Chen ◽  
Yueqin Yang ◽  
Zuzhao Che ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Molecular Docking ◽  
Active Ingredient ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Active Ingredients ◽  
Disease Network ◽  
The Core ◽  
Target Disease ◽  
The Common

Abstract Objective: To investigate the molecular mechanism of Astragalus-Scorpion in the treatment of prostate cancer by network pharmacology and molecular docking technology.Methods: Using TCMSP, BATMAN-TCM, TCMID and Swiss TargetPrediction Databases to retrieve the active ingredients and corresponding targets of Astragalus-Scorpion. The targets related to prostate cancer were retrieved through GeneCards, so as to obtain the common targets of Astragalus-Scorpion and prostate cancer. The common targets were input into the STRING database for protein interaction analysis. Cytoscape software was used to construct the active “ingredient-target-disease” network, and GO and KEGG enrichment analysis were performed on the common targets. To screen the core ingredients and targets that play therapeutic roles, Autodock software was used for molecular docking verification. Results: 27 active ingredients, 340 potential targets related to active ingredients, 898 targets related to disease and 122 common targets were screened from Astragalus-Scorpion totally. The core targets of PPI network were JUN, AKT1, IL6, MAPK1 and RELA, while the core active ingredients in the active ingredient-target-disease network were quercetin, kaempferol, formononetin, 7-o-methylisomucronulatol and calycosin.762 GO entries and 154 pathways were obtained by enrichment analysis totally. The molecular docking results showed that quercetin binds to AKT1 and RELA, kaempferol to AKT1, and formononetin to RELA, all of which were stable. Conclusion: Quercetin, kaempferol and others in the Astragalus-Scorpion can regulate multiple signaling pathways such as PI3K-Akt signaling pathway by binding to targets such as AKT1 related to prostate cancer, inhibit the proliferation of tumor to play a role for prostate cancer.

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