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 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 Pharmacological Mechanisms Underlying the Anti-asthmatic Effects of Modified Guomin Decoction Determined by Network Pharmacology and Molecular Docking

2021 ◽  
Vol 8 ◽  
Author(s):  
Guishu Wang ◽  
Bo Zhou ◽  
Zheyi Wang ◽  
Yufeng Meng ◽  
Yaqian Liu ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Molecular Mechanism ◽  
Airway Remodeling ◽  
Enrichment Analysis ◽  
Chronic Inflammatory Disease ◽  
Network Pharmacology ◽  
Active Components ◽  
Active Compounds ◽  
Protein Protein Interaction ◽  
Pathway Annotation

BackgroundAsthma is a chronic inflammatory disease characterized by Th2-predominant inflammation and airway remodeling. Modified Guo Min decoction (MGMD) has been an extensive practical strategy for allergic disorders in China. Although its potential anti-asthmatic activity has been reported, the exact mechanism of action of MGMD in asthma remains unexplored.MethodsNetwork pharmacology approach was employed to predict the active components, potential targets, and molecular mechanism of MGMD for asthma treatment, including drug-likeness evaluation, oral bioavailability prediction, protein–protein interaction (PPI) network construction and analysis, Gene Ontology (GO) terms, and Reactome pathway annotation. Molecular docking was carried out to investigate interactions between active compounds and potential targets.ResultsA total of 92 active compounds and 72 anti-asthma targets of MGMD were selected for analysis. The GO enrichment analysis results indicated that the anti-asthmatic targets of MGMD mainly participate in inflammatory and in airway remolding processes. The Reactome pathway analysis showed that MGMD prevents asthma mainly through regulation of the IL-4 and IL-13 signaling and the specialized pro-resolving mediators (SPMs) biosynthesis. Molecular docking results suggest that each bioactive compounds (quercetin, wogonin, luteolin, naringenin, and kaempferol) is capable to bind with STAT3, PTGS2, JUN, VEGFA, EGFR, and ALOX5.ConclusionThis study revealed the active ingredients and potential molecular mechanism by which MGMD treatment is effective against airway inflammation and remodeling in asthma through regulating IL-4 and IL-13 signaling and SPMs biosynthesis.

scholarly journals Exploring the Mechanism of Quercetin for the Treatment of Atrial Fibrillation by Geo Gene Chip Combined With Network Pharmacology and Molecular Docking

2021 ◽  
Author(s):  
tan xin ◽  
Wei Xian ◽  
Xiaorong Li ◽  
Yongfeng Chen ◽  
Jiayi Geng ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Mechanism Of Action ◽  
Target Prediction ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Binding Activity ◽  
Network Pharmacology ◽  
Chemical Structures ◽  
Drug Mechanism

Abstract PurposeAtrial fibrillation (AF) is a common atrial arrhythmia. Quercetin (Que) has some advantages in the treatment of cardiovascular disease arrhythmias, but its specific drug mechanism of action needs further investigation. To explore the mechanism of action of Que in AF, core target speculation and analysis were performed using network pharmacology and molecular docking methods.MethodsQue chemical structures were obtained from Pubchem. TCMSP, Swiss Target Prediction, Drugbank , STITCH, Binding DB, Pharmmapper, CTD, GeneCards, DISGENET and TTD were used to obtain drug component targets and AF-related genes, and extract AF from normal tissues by GEO database differentially expressed genes. Then, the intersecting genes were obtained by online Wayne mapping tool. The intersection genes were introduced into the top five targets selected for molecular docking via protein-protein interaction (PPI) network to verify the binding activity between Que and the target proteins. GO and KEGG enrichment analysis of the intersected genes using program R was performed to further screen for key genes and key pathways.ResultsThere were 65 effective targets for Que and AF. Through further screening, the top 5 targets were IL6, VEGFA, JUN, MMP9 and EGFR. Que treatment of AF may involve signaling pathways such as lipid and atherosclerosis pathway, AGE-RAGE signaling pathway in diabetic complications, MAPK signaling pathway and IL-17 signaling pathway. Molecular docking suggests that Que has strong binding to key targets.ConclusionThis study systematically elucidates the key targets of Que treatment for AF and the specific mechanisms through network pharmacology as well as molecular docking, providing a new direction for further basic experimental exploration and clinical treatment.

A Network Pharmacology Approach to Explore the Underlying Mechanism of Tufuling Qiwei Tangsan in Treating Psoriasis

2021 ◽  
Vol 16 ◽  
Author(s):  
Xiaolei Ma ◽  
Yinan Lu ◽  
Yang Lu ◽  
Zhili Pei
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Mechanism Of Action ◽  
Enrichment Analysis ◽  
Underlying Mechanism ◽  
Mapk Signaling ◽  
Binding Activity ◽  
Network Pharmacology ◽  
Active Components ◽  
Active Compounds

Background: Tufuling Qiwei Tangsan (TQTS) is a commonly used Mongolian medicine preparation against psoriasis in China. However, its mechanism of action and molecular targets for the treatment of psoriasis is still unclear. Network pharmacology can reveal the synergistic mechanism of drugs at the molecular, target and pathway levels, and is suitable for the complex study of traditional Chinese medicine formulations. However, it is rarely involved in the application of Mongolian medicine with the same holistic concept of traditional Chinese medicine. Method: In this paper, the active compounds of TQTS were collected and their targets were identified. Psoriasis-related targets were obtained by analyzing the differential expressed genes between psoriasis patients and healthy individuals. Then, the network concerning the interactions of potential targets of TQTS with well-known psoriasis-related targets was built. The core targets were selected according to topological parameters. And the enrichment analysis was carried out to explore the mechanism of action of TQTS. Moreover, molecular docking was performed to study the interaction between the selected ligands and receptors related to psoriasis. Result and Conclusion: Eighty-five active compounds of TQTS were screened, with corresponding 270 targets, and 313 differentially expressed genes were identified. Additionally, enrichment analysis showed that the targets of TQTS for treating psoriasis were mainly concentrated in multiple biological processes, including apoptosis, growth factor response,etc., and related pathways including PI3K-Akt and MAPK signaling pathway, and so on. Genes such as NFKB1, TP53 and MAPK1 are the key genes in the gene pathway network of TQTS against psoriasis. The 4 main active components of TQTS have certain binding activity with 13 potential targets, and the stability of interaction with AKT1 is the best, which indicate the potential mechanism of TQTS on psoriasis.

scholarly journals Exploring the Pharmacological Mechanism of Cassiae Semen a Cting on Cataracts Based on a Network Pharmacology Approach

2020 ◽  
Author(s):  
Ying Zhong ◽  
Youfa Fang
Keyword(s):  
Signaling Pathway ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Network Pharmacology ◽  
Active Compounds ◽  
Pharmacological Mechanism ◽  
Ppi Networks ◽  
Target Network ◽  
Central Network

Abstract BackgroundCassiae Semen (CS) is one of the most well-known herbs used in the treatment of cataracts in China. However, the potential mechanisms of its anti-cataracts effects have not been fully explored.MethodThe active compounds of CS were obtained from TCMSP database, and their targets were retrieved from the TCMSP, STITCH and DrugBank databases. Cataracts related target genes were identified from the GeneCard, Malacard, and OMIM databases. GO and KEGG analysis were performed using DAVID online tools, and Cytoscape were used to construct compound-targets network and protein-protein interaction (PPI) networks, cluster analysis were carried out using MCODE plugin for Cytoscape.ResultsWe obtained 13 active compounds from CS and 105 targets in total to construct a compound-target network, which indicated that emodin, stigmastero, and rhein served as the main ingredients in CS. A total of 238 cataracts related targets were identified from public databases. PPI networks of compound targets and cataract-related targets were constructed and merged to obtained the central network, enrichment analysis showed 50 key targets in the central network enriched in several important signaling pathways, such as thyroid hormone signaling pathway, MAPK signaling pathway, PI3K-Akt signaling pathway. The top 4 genes with higher degree in the central network were TP53, HSP90, ESR1, EGFR, indicating their important roles in the treatment of cataracts.ConclusionsThe present study systematically revealed the multi-target mechanisms of CS on cataracts using network pharmacology approach, and provided indications for further mechanistic studies and also for the development of CS as a potential treatment for cataracts patients.

scholarly journals To explore the material basis and mechanism of Lianhua Qingwen Prescription against COVID-19 based on network pharmacology

2020 ◽  
Vol 1 ◽  
pp. 3
Author(s):  
Wenpan Peng ◽  
Di Han ◽  
Yong Xu ◽  
Fanchao Feng ◽  
Zhichao Wang ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
T Cell Activation ◽  
Mechanism Of Action ◽  
Cell Activation ◽  
Chemical Constituents ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Mapk Signaling Pathway ◽  
Network Pharmacology ◽  
Material Basis

Objective: In the treatment of COVID-19, the application of Lianhua Qingwen Prescription has become growingly widespread, however, the mechanism of action is still unclear. To explore the material basis and mechanism of Lianhua Qingwen Prescription against SARS-CoV-2, to provide a reference for the treatment of COVID-19. Methods: Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), SwissTargetPrediction, and Similarity Ensemble Approach (SEA) database were used to search the chemical constituents and targets of Lianhua Qingwen Prescription. The targets of COVID-19 were screened by GeneCards, Therapeutic Target Database (TTD), and Comparative Toxicogenomics Database (CTD). Cytoscape software was used to construct a “drug-component-target” network diagram and the mechanism of action was predicted by enrichment analysis. Results: Two hundred and twenty four active components, 246 drug therapeutic targets, and 16,611 potential targets of Lianhua Qingwen Prescription were mined out. Moreover, 163 common targets were obtained, including PTGS2, IL6, CASP3, mapk1, EGFR, ACE2, etc. Thirty seven items were obtained by Gene Ontology (GO) enrichment analysis, mainly involving T-cell activation, virus receptor, and inflammatory reaction, etc. One hundred and forty items were obtained by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enriched analysis, including TNF signaling pathway, MAPK signaling pathway, and IL-17 signaling pathway. Conclusion: Compounds such as quercetin and kaempferol play an important role in anti-COVID-19 through the TNF signaling pathway and MAPK signaling pathway.

Bioinformatics Analysis Reveals Functions of MicroRNAs in Rice Under the Drought Stress

2021 ◽  
Vol 15 (8) ◽  
pp. 927-936 ◽  
Author(s):  
Yan Peng ◽  
Yuewu Liu ◽  
Xinbo Chen
Keyword(s):  
Drought Stress ◽  
Target Genes ◽  
Hot Spot ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Protein Protein Interaction ◽  
Promising Tool ◽  
Differentially Expressed Mirnas ◽  
Aba Biosynthesis

Background: Drought is one of the most damaging and widespread abiotic stresses that can severely limit the rice production. MicroRNAs (miRNAs) act as a promising tool for improving the drought tolerance of rice and have become a hot spot in recent years. Objective: In order to further extend the understanding of miRNAs, the functions of miRNAs in rice under drought stress are analyzed by bioinformatics. Method: In this study, we integrated miRNAs and genes transcriptome data of rice under the drought stress. Some bioinformatics methods were used to reveal the functions of miRNAs in rice under drought stress. These methods included target genes identification, differentially expressed miRNAs screening, enrichment analysis of DEGs, network constructions for miRNA-target and target-target proteins interaction. Results: (1) A total of 229 miRNAs with differential expression in rice under the drought stress, corresponding to 73 rice miRNAs families, were identified. (2) 1035 differentially expressed genes (DEGs) were identified, which included 357 up-regulated genes, 542 down-regulated genes and 136 up/down-regulated genes. (3) The network of regulatory relationships between 73 rice miRNAs families and 1035 DEGs was constructed. (4) 25 UP_KEYWORDS terms of DEGs, 125 GO terms and 7 pathways were obtained. (5) The protein-protein interaction network of 1035 DEGs was constructed. Conclusion: (1) MiRNA-regulated targets in rice might mainly involve in a series of basic biological processes and pathways under drought conditions. (2) MiRNAs in rice might play critical roles in Lignin degradation and ABA biosynthesis. (3) MiRNAs in rice might play an important role in drought signal perceiving and transduction.

scholarly journals Decoding the molecular mechanism of parthenocarpy in Musa spp. through protein–protein interaction network

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Suthanthiram Backiyarani ◽  
Rajendran Sasikala ◽  
Simeon Sharmiladevi ◽  
Subbaraya Uma
Keyword(s):  
Candidate Genes ◽  
Protein Interaction ◽  
Target Genes ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Auxin Signaling ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Protein Protein Interaction ◽  
The Difference

AbstractBanana, one of the most important staple fruit among global consumers is highly sterile owing to natural parthenocarpy. Identification of genetic factors responsible for parthenocarpy would facilitate the conventional breeders to improve the seeded accessions. We have constructed Protein–protein interaction (PPI) network through mining differentially expressed genes and the genes used for transgenic studies with respect to parthenocarpy. Based on the topological and pathway enrichment analysis of proteins in PPI network, 12 candidate genes were shortlisted. By further validating these candidate genes in seeded and seedless accession of Musa spp. we put forward MaAGL8, MaMADS16, MaGH3.8, MaMADS29, MaRGA1, MaEXPA1, MaGID1C, MaHK2 and MaBAM1 as possible target genes in the study of natural parthenocarpy. In contrary, expression profile of MaACLB-2 and MaZEP is anticipated to highlight the difference in artificially induced and natural parthenocarpy. By exploring the PPI of validated genes from the network, we postulated a putative pathway that bring insights into the significance of cytokinin mediated CLAVATA(CLV)–WUSHEL(WUS) signaling pathway in addition to gibberellin mediated auxin signaling in parthenocarpy. Our analysis is the first attempt to identify candidate genes and to hypothesize a putative mechanism that bridges the gaps in understanding natural parthenocarpy through PPI network.

scholarly journals Elucidating the Mechanisms of Action of Lianhua Qingwen decoction for the Treatment of COVID-19 via Systems Pharmacology Approaches

2021 ◽  
Author(s):  
Xiting Wang ◽  
Tao Lu
Keyword(s):  
Molecular Docking ◽  
Blood Circulation ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Detection Algorithm ◽  
Network Pharmacology ◽  
Systems Pharmacology ◽  
Protein Protein Interaction ◽  
Further Development ◽  
Protein Protein Interaction Network

Abstract Due to the severity of the COVID-19 epidemic, to identify a proper treatment for COVID-19 is of great significance. Traditional Chinese Medicine (TCM) has shown its great potential in the prevention and treatment of COVID-19. One of TCM decoction, Lianhua Qingwen decoction displayed promising treating efficacy. Nevertheless, the underlying molecular mechanism has not been explored for further development and treatment. Through systems pharmacology and network pharmacology approaches, we explored the potential mechanisms of Lianhua Qingwen treating COVID-19 and acting ingredients of Lianhua Qingwen decoction for COVID-19 treatment. Through this way, we generated an ingredients-targets database. We also used molecular docking to screen possible active ingredients. Also, we applied the protein-protein interaction network and detection algorithm to identify relevant protein groupings of Lianhua Qingwen. Totally, 605 ingredients and 1,089 targets were obtained. Molecular Docking analyses revealed that 35 components may be the promising acting ingredients, 7 of which were underlined according to the comprehensive analysis. Our enrichment analysis of the 7 highlighted ingredients showed relevant significant pathways that could be highly related to their potential mechanisms, e.g. oxidative stress response, inflammation, and blood circulation. In summary, this study suggests the promising mechanism of the Lianhua Qingwen decoction for COVID-19 treatment. Further experimental and clinical verifications are still needed.

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