New perspective: the multi-targets mechanism of hydroxychloroquine in the treatment of rheumatoid arthritis based on network pharmacology

Abstract Background Network pharmacology is a new method of bioinformatics in exploring drug targets in recent 3 years. Hydroxychloroquine (HCQ) is a multi-targets drug that are clinically effective in rheumatoid arthritis (RA) but whose mechanism is not well understood. Methods The predicted targets of HCQ and the proteins related to RA were returned from databases. Followed by protein-protein interaction (PPI) network, the intersection of the two group of proteins was conducted. Furthermore, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment was used to analyse these proteins in a macro perspective. Finally, the candidate targets were verified by molecular docking. Results The results suggest that the efficacy of HCQ against RA is mainly associated with 4 targets of smoothened homolog (SMO), sphingosine kinase (SPHK) 1, SPHK2 and gatty-acid amide hydrolase (FAAH), with their related 3316 proteins’ network which regulate ErbB, HIF-1, NF-κB, FoxO, Chemokine, MAPK, PI3K/Akt pathways and so forth. Biological process are mainly concentrated in the regulation of cell activation, myeloid leukocyte activation, regulated exocytosis and so forth. Molecular docking analysis shows that hydrogen bonding and π-π stacking are the main forms of chemical force. Conclusions Our research provides protein targets affected by HCQ in the treatment of RA. SMO, SPHK1, SPHK2 and FAAH involving 3316 proteins become the multi-targets mechanism of HCQ in the treatment of RA. As well, the research also provides a new idea for introducing network pharmacology into the evaluation of the multi-target drugs in internal medicine.

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

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2021/6077698 ◽

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.

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Virtual Screening Technique Used to Estimate the Mechanism of Adhatoda vasica Nees for the Treatment of Rheumatoid Arthritis Based on Network Pharmacology and Molecular Docking

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2020/5872980 ◽

2020 ◽

Vol 2020 ◽

pp. 1-12

Author(s):

Wenxiang Wang ◽

Yunsen Zhang ◽

Jie Luo ◽

Rushan Wang ◽

Ce Tang ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Molecular Docking ◽

Drug Targets ◽

Molecular Mechanisms ◽

Experimental Studies ◽

Interaction Network ◽

Network Pharmacology ◽

Chemical Components ◽

Chemical Compositions ◽

Adhatoda Vasica

Adhatoda vasica Nees (AVN) is commonly used to treat joint diseases such as rheumatoid arthritis (RA) in ethnic minority areas of China, especially in Tibetan and Dai areas, and its molecular mechanisms on RA still remain unclear. Network pharmacology, a novel strategy, utilizes bioinformatics to predict and evaluate drug targets and interactions in disease. Here, network pharmacology was used to investigate the mechanism by which AVN acts in RA. The chemical compositions and functional targets of AVN were retrieved using the systematic pharmacological analysis platform PharmMapper. The targets of RA were queried through the DrugBank database. The protein-protein interaction network (PPI), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of key targets were constructed in the STRING database, and the network visualization analysis was performed in Cytoscape. Maestro 11.1, a type of professional software, was used for verifying prediction and analysis based on network pharmacology. By comparing the predicted target information with the targets of RA-related drugs, 25 potential targets may be related to the treatment of RA, among which MAPK1, TNF, DHODH, IL2, PTGS2, and JAK2 may be the main potential targets for the treatment of RA. Finally, the chemical components and potential target proteins were scored by molecular docking, and compared with the ligands of the protein, the prediction results of network pharmacology were preliminarily verified. The active ingredients and mechanism of AVN against RA were firstly investigated using network pharmacology. Additionally, this research provided a solid foundation for further experimental studies.

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

10.21203/rs.3.rs-21103/v2 ◽

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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Mechanistic Investigation of Glycyrrhiza uralensis Effects against Respiratory Ailments: Application of Network Pharmacology and Molecular Docking Approaches

Letters in Drug Design & Discovery ◽

10.2174/1570180818666211119113853 ◽

2021 ◽

Vol 18 ◽

Author(s):

Munazza Ijaz ◽

Xianju Huang ◽

Manal Buabeid ◽

Tahir Ali Chohan ◽

Ghulam Murtaza ◽

...

Keyword(s):

Gene Ontology ◽

Molecular Docking ◽

Herbal Remedy ◽

Database Search ◽

Glycyrrhiza Uralensis ◽

Network Pharmacology ◽

Careful Study ◽

Protein Targets ◽

Go Enrichment ◽

Mechanistic Investigation

Background: Glycyrrhiza uralensis, also known as liquorice, is a herbal remedy that is traditionally used worldwide for treating respiratory ailments and ameliorating breathing. Objective: The objective of this systematic study was to investigate active ingredients of Glycyrrhiza uralensis and determine its mode of action in silico against severe and acute respiratory complications of respiratory ailments through network pharmacology and molecular docking studies. Methods: TCMSP database search helped retrieve the compounds of Glycyrrhiza uralensis and their protein targets, especially related to respiratory ailments. Subsequently, the protein-protein association was attained as a network by using the STITCH database. Cytoscape and its ClueGO plugin were used to study gene ontology (GO) enrichment. In addition, seven natural compounds were docked in the active site of four different molecular targets; JUN-FOS, COX2, MAPK14 and IL-6, to identify the binding mechanism of ligands under study. Results: TCMSP database search resulted in the retrieval of 280 compounds of Glycyrrhiza uralensis (including formononetin, naringenin, sitosterol, isorhamnetin, kaempferol, quercetin and Glycyrrhizin) and 135 protein targets. A careful study of targets showed that 26 prospective targets (including JUN, FOS, IL6, MAPK14 and PTGS2) related to respiratory ailments were identified. Gene ontology (GO) enrichment analysis resulted in the retrieval of 176 GO terms, which were associated with respiratory ailments. This study proposed that Glycyrrhiza uralensis acts against respiratory ailments through various proteins, such as JUN, FOS, IL6, MAPK14 and PTGS2. Docking results revealed that among all studied ligands, the flavonoid-based compounds isorhamnetin and kaempferol form stronger complexes with JUN-FOS-DNA, MAPK-14, and IL-6 proteins (Cscore=6.81, 4.27, and 4.77, respectively) and the saponin based compound glycyrrhizin (Cscore=13.07) demonstrated stronger binding affinity towards COX2 enzyme. Conclusion: Conclusively, isorhamnetin, kaempferol and glycyrrhizin in Glycyrrhiza uralensis may regulate several signaling pathways through JUN-FOS-DNA, MAPK-14, and IL-6, which might play a therapeutic role against respiratory ailments.

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Integrating Network Pharmacology with Molecular Docking to Unravel the Active Compounds and Potential Mechanism of Simiao Pill Treating Rheumatoid Arthritis

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2020/5786053 ◽

2020 ◽

Vol 2020 ◽

pp. 1-16

Author(s):

Mengshi Tang ◽

Xi Xie ◽

Pengji Yi ◽

Jin Kang ◽

Jiafen Liao ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Molecular Docking ◽

Signaling Pathway ◽

Target Genes ◽

Enrichment Analysis ◽

Binding Activity ◽

New Combination ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Potential Mechanism

Objective. To explore the main components and unravel the potential mechanism of simiao pill (SM) on rheumatoid arthritis (RA) based on network pharmacological analysis and molecular docking. Methods. Related compounds were obtained from TCMSP and BATMAN-TCM database. Oral bioavailability and drug-likeness were then screened by using absorption, distribution, metabolism, and excretion (ADME) criteria. Additionally, target genes related to RA were acquired from GeneCards and OMIM database. Correlations about SM-RA, compounds-targets, and pathways-targets-compounds were visualized through Cytoscape 3.7.1. The protein-protein interaction (PPI) network was constructed by STRING. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed via R packages. Molecular docking analysis was constructed by the Molecular Operating Environment (MOE). Results. A total of 72 potential compounds and 77 associated targets of SM were identified. The compounds-targets network analysis indicated that the 6 compounds, including quercetin, kaempferol, baicalein, wogonin, beta-sitosterol, and eugenol, were linked to ≥10 target genes, and the 10 target genes (PTGS1, ESR1, AR, PGR, CHRM3, PPARG, CHRM2, BCL2, CASP3, and RELA) were core target genes in the network. Enrichment analysis indicated that PI3K-Akt, TNF, and IL-17 signaling pathway may be a critical signaling pathway in the network pharmacology. Molecular docking showed that quercetin, kaempferol, baicalein, and wogonin have good binding activity with IL6, VEGFA, EGFR, and NFKBIA targets. Conclusion. The integrative investigation based on bioinformatics/network topology strategy may elaborate on the multicomponent synergy mechanisms of SM against RA and provide the way out to develop new combination medicines for RA.

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Potential Molecular Target Prediction and Docking Verification of Hua-Feng-Dan in Stroke Based on Network Pharmacology

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2020/8872593 ◽

2020 ◽

Vol 2020 ◽

pp. 1-12

Author(s):

Ping Yang ◽

Haifeng He ◽

Shangfu Xu ◽

Ping Liu ◽

Xinyu Bai

Keyword(s):

Molecular Docking ◽

Signaling Pathways ◽

Target Genes ◽

Target Prediction ◽

Interaction Network ◽

Network Pharmacology ◽

Core Network ◽

Active Ingredients ◽

Protein Protein Interaction ◽

Highly Correlated

Objective. Hua-Feng-Dan (HFD) is a Chinese medicine for stroke. This study is to predict and verify potential molecular targets and pathways of HFD against stroke using network pharmacology. Methods. The TCMSP database and TCMID were used to search for the active ingredients of HFD, and GeneCards and DrugBank databases were used to search for stroke-related target genes to construct the “component-target-disease” by Cytoscape 3.7.1, which was further filtered by MCODE to build a core network. The STRING database was used to obtain interrelationships by topology and to construct a protein-protein interaction network. GO and KEGG were carried out through DAVID Bioinformatics. Autodock 4.2 was used for molecular docking. BaseSpace was used to correlate target genes with the GEO database. Results. Based on OB ≥ 30% and DL ≥ 0.18, 42 active ingredients were extracted from HFD, and 107 associated targets were obtained. PPI network and Cytoscape analysis identified 22 key targets. GO analysis suggested 51 cellular biological processes, and KEGG suggested that 60 pathways were related to the antistroke mechanism of HFD, with p53, PI3K-Akt, and apoptosis signaling pathways being most important for HFD effects. Molecular docking verified interactions between the core target (CASP8, CASP9, MDM2, CYCS, RELA, and CCND1) and the active ingredients (beta-sitosterol, luteolin, baicalein, and wogonin). The identified gene targets were highly correlated with the GEO biosets, and the stroke-protection effects of Xuesaitong in the database were verified by identified targets. Conclusion. HFD could regulate the symptoms of stroke through signaling pathways with core targets. This work provided a bioinformatic method to clarify the antistroke mechanism of HFD, and the identified core targets could be valuable to evaluate the antistroke effects of traditional Chinese medicines.

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Molecular docking analysis of phytocompounds from Acacia farnesiana with protein targets linked to bronchitis

Bioinformation ◽

10.6026/97320630017557 ◽

2021 ◽

Vol 17 (5) ◽

pp. 557-567

Author(s):

Mallikarjun S Beelagi ◽

Keyword(s):

Molecular Docking ◽

Drug Targets ◽

Acute Bronchitis ◽

Analysis Data ◽

Dna Topoisomerase ◽

Protein Targets ◽

Docking Analysis ◽

Acacia Farnesiana ◽

Bronchial Inflammation ◽

Molecular Docking Analysis

Acute bronchitis is a lower respiratory tract lung infection that causes bronchial inflammation. The known protein drug targets are peptidoglycan D, Dtranspeptidase, and DNA topoisomerase 4 subunit A for bronchitis linked infections. These are the membrane associated macromolecules which takes a major role in the formation of cell wall membrane by synthesising the cross-linked peptidoglycan. Therefore, it is of interest to design molecules with improved binding features with these protein targets. Hence, we document the molecular docking analysis data of four phytocompounds from Acacia farnesiana having optimal binding features with these targets linked to bronchitis for further consideration.

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Myrtenal and β-caryophyllene oxide screened from Liquidambaris Fructus suppress NLRP3 inflammasome components in rheumatoid arthritis

BMC Complementary Medicine and Therapies ◽

10.1186/s12906-021-03410-2 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Wen-xuan Li ◽

Ping Qian ◽

Yi-tong Guo ◽

Li Gu ◽

Jessore Jurat ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Molecular Docking ◽

Nlrp3 Inflammasome ◽

Network Pharmacology ◽

Caryophyllene Oxide ◽

Active Ingredients ◽

Caspase 1 ◽

Tnf Α ◽

Cartilage Erosion ◽

And Cartilage

Abstract Background Liquidambaris Fructus (LF) is the infructescence of Liquidambar formosana. In Traditional Chinese Medicine, LF has been used to treat joint pain, a common symptom of arthritis and rheumatism; however, a lack of pharmacological evidence has limited its applications in modern clinics. Therefore, this study aims to explore the protective effect of LF on rheumatoid arthritis (RA) and to identify its active ingredients. Methods Rats with adjuvant-induced arthritis (AIA) were divided into 4 groups and administered petroleum ether extract of LF (PEL), ethyl acetate extract of LF (EEL), water extract of LF (WEL), or piroxicam (PIR) respectively for 3 weeks. Two additional groups were used as normal control (NC) and model control (MC) and administered distilled water as a placebo. The clinical scores for arthritis, bone surface, synovial inflammation and cartilage erosion were used to evaluate the therapeutic efficacy of each treatment. The serum IL-1β and TNF-α level and the expression of NLRP3, IL-1β and caspase-1 p20 in the synovial tissue of AIA rats were evaluated by ELISA and Western blot. The active ingredients of LF were investigated using network pharmacology and molecular docking methods, and their inhibition of NLRP3 inflammasome activation was verified in the human rheumatoid arthritis fibroblast-like synovial cells (RA-FLS) model. Results PEL could alleviate paw swelling, bone and joint destruction, synovial inflammation and cartilage erosion in the AIA rats, with significantly superior efficacy to that of EEL and WEL. PEL reduced IL-1β and TNF-α serum levels, and attenuated the upregulation of NLRP3, IL-1β and caspase-1 p20 expression in the synovial tissue of AIA rats. Network pharmacology and molecular docking results indicated that myrtenal and β-caryophyllene oxide were the main two active ingredients of PEL, and these two compounds showed significant inhibition on TNF-α, NLRP3, IL-1β and caspase-1 p20 expression in RA-FLS. Conclusions Myrtenal and β-caryophyllene oxide screened from PEL could suppress the activation of NLRP3 inflammasome, thereby alleviating RA symptoms.

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Investigating the Mechanism of Guizhi Fuling Formula in the Treatment of Primary Dysmenorrhea based on Network Pharmacology and Molecular Docking

10.21203/rs.3.rs-151904/v1 ◽

2021 ◽

Author(s):

Lu Sun ◽

Zining Wang ◽

Jian Li ◽

Li Xu ◽

Xiaoou Xue

Keyword(s):

Molecular Docking ◽

Enrichment Analysis ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Primary Dysmenorrhea ◽

Potential Mechanism ◽

Protein Protein Interaction ◽

Long Time ◽

Hormone Biosynthesis ◽

Relationship Of

Abstract Background: Primary dysmenorrhea(PD)is the most common gynecologic disorder.Despite the prevalence is high, it is often underdiagnosed,undertreated and normalized even by patients themselves. Guizhi Fuling Formula (GFF) is experientially used for the treatment of PD in a long time. Therefore, the efficiency and potential mechanism are waiting to identify.Methods: We adopted network pharmacology integrated molecular docking strategy in this study.Based on published literatures, the relative compounds of GFF were selected preliminarily. Secondly, the putative targets of PD were obtained by wide-searching DisGeNET, OMIM, Drugbank and GeneCards databases.With protein-protein interaction(PPI) analysis, GO and KEGG pathway enrichment analysis and molecular docking ,we systematically evaluated the relationship of herb ingredients and disease targets.Results: The results showed that 30 ingredients of GFF and 43 hub targets made a difference.Under the further analysis,8 targets(EGFR,AKT1,PTGS2,TNF,ESR1,AHR,CTNNB1,CXCL8) were recognized as key therapeutic targets with excellent binding. The enrichment analyses indicated that the GFF had the potential to influence varieties of biological pathways, especially the pathways in cancer and steroid hormone biosynthesis, which play an important part in the pathogenesis of primary dysmenorrhea.Conclusion: GFF influenced primary dysmenorrhea through the synergistic effect of multiple components, multiple targets, and multiple pathways.This study predictedthe potential mechanism, hope that could made contribution for clinical application and scientific research.

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Molecular docking and network connections of active compounds from the classical herbal formula Ding Chuan Tang

PeerJ ◽

10.7717/peerj.8685 ◽

2020 ◽

Vol 8 ◽

pp. e8685

Author(s):

Allison Clyne ◽

Liping Yang ◽

Ming Yang ◽

Brian May ◽

Angela Wei Hong Yang

Keyword(s):

Molecular Docking ◽

Song Dynasty ◽

Network Pharmacology ◽

Herbal Formula ◽

Protein Targets ◽

The Song Dynasty ◽

Network Connections ◽

Asthma Drug ◽

Cellular Pathways ◽

Disease Pathways

Background Ding Chuan Tang (DCT), a traditional Chinese herbal formula, has been consistently prescribed for the therapeutic management of wheezing and asthma-related indications since the Song Dynasty (960–1279 AD). This study aimed to identify molecular network pharmacology connections to understand the biological asthma-linked mechanisms of action of DCT and potentially identify novel avenues for asthma drug development. Methods Employing molecular docking (AutoDock Vina) and computational analysis (Cytoscape 3.6.0) strategies for DCT compounds permitted examination of docking connections for proteins that were targets of DCT compounds and asthma genes. These identified protein targets were further analyzed to establish and interpret network connections associated with asthma disease pathways. Results A total of 396 DCT compounds and 234 asthma genes were identified through database search. Computational molecular docking of DCT compounds identified five proteins (ESR1, KDR, LTA4H, PDE4D and PPARG) mutually targeted by asthma genes and DCT compounds and 155 docking connections associated with cellular pathways involved in the biological mechanisms of asthma. Conclusions DCT compounds directly target biological pathways connected with the pathogenesis of asthma including inflammatory and metabolic signaling pathways.

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