Application Of Network Pharmacology Research Articles

Network pharmacology combined with affinity ultrafiltration to elucidate the potential compounds of Shaoyao Gancao Fuzi Decoction for the treatment of rheumatoid arthritis

Ethnopharmacological relevanceShaoyao Gancao Fuzi Decoction (SGFD), has been employed for thousands of years in the treatment of rheumatoid arthritis (RA) with remarkable clinical efficacy. However, the material basis underlying the effectiveness of SGFD still remains unclear. Aim of the reviewThis study aims to elucidate the material basis of SGFD through the application of network pharmacology and biological affinity ultrafiltration. ResultsUPLC-Q-TOF-MS/MS was employed to characterize the components in SGFD, the identified 145 chemical components were mainly categorized into alkaloids, flavonoids, triterpenoids, and monoterpenoids according to the structures. Network pharmacology method was utilized to identify potential targets and signaling pathways of SGFD in the RA treatment, and the anti-inflammatory and anti-RA effects of SGFD were validated through in vivo and in vitro experiments. Moreover, as the significant node in the pharmacology network, TNF-α, a classical therapeutic target in RA, was subsequent employed to screen the interacting compounds in SGFD via affinity ultrafiltration screening method, 6 active molecules (i.e.,glycyrrhizic acid, paeoniflorin, formononetin, isoliquiritigenin, benzoyl mesaconitine, and glycyrrhetinic acid) were exhibited significant interactions. Finally, the significant anti-inflammatory and anti-TNF-α effects of these compounds were validated at the cellular level. ConclusionsIn conclusion, this study comprehensively elucidates the pharmacodynamic material basis of SGFD, offering a practical reference model for the systematic investigation of traditional Chinese medicine formulas.

Active substance and mechanisms of Actinidia chinensis Planch for the treatment of breast cancer was explored based on network pharmacology and in silico study.

In this paper, our objective was to investigate the potential mechanisms of Actinidia chinensis Planch (ACP) for breast cancer treatment with the application of network pharmacology, molecular docking, and molecular dynamics. "Mihoutaogen" was used as a key word to query the Traditional Chinese Medicine Systems Pharmacology database for putative ingredients of ACP and its related targets. DrugBank, GeneCards, Online Mendelian Inheritance in Man, and therapeutic target databases were used to search for genes associated with "breast cancer." Using Cytoscape 3.9.0 we then constructed the protein-protein interaction and drug-ingredient-target-disease networks. An enrichment analysis of Kyoto encyclopedia of genes and genomes pathway and gene ontology were performed to exploration of the signaling pathways associated with ACP for breast cancer treatment. Discovery Studio software was applied to molecular docking. Finally, the ligand-receptor complex was subjected to a 50-ns molecular dynamics simulation using the Desmond_2020.4 tools. Six main active ingredients and 176 targets of ACP and 2243 targets of breast cancer were screened. There were 118 intersections of targets for both active ingredients and diseases. Tumor protein P53 (TP53), AKT serine/threonine kinase 1 (AKT1), estrogen receptor 1 (ESR1), Erb-B2 receptor tyrosine kinase 2 (ERBB2), epidermal growth factor receptor (EGFR), Jun Proto-Oncogene (JUN), and Heat Shock Protein 90 Alpha Family Class A Member 1 (HSP90AA1) selected as the most important genes were used for verification by molecular docking and molecular dynamics simulation. The primary active compounds of ACP against breast cancer were predicted preliminarily, and its mechanism was studied, thereby providing a theoretical basis for future clinical studies.

Elucidation of the Molecular Mechanism of Compound Danshen Dripping Pills Against Angina Pectoris based on Network Pharmacology and Molecular Docking.

Compound Danshen dripping pills (CDDP), a traditional Chinese medicine, has had an extensive application in the treatment of angina pectoris (AP) in China. However, research on the bioactive ingredients and underlying mechanisms of CDDP in AP remains unclear. In the present study, we explored the major chemical components and potential molecular mechanisms linked to the anti-angina effects of CDDP through the application of network pharmacology and molecular docking. The potential targets of active ingredients in CDDP were sourced from the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP) and the Swiss Target Prediction Database (STPD). Additionally, targets related to angina pectoris (AP) were retrieved from various databases, including Gene Cards, DisGeNET, Dis Genet, the Drug Bank database (DBD), and the Therapeutic Target Database (TDD). Protein- protein interaction [1] networks were also established, and core targets were identified based on their topological significance. GO enrichment analysis and KEGG pathway analysis were conducted using the R software. Interactions between active ingredients and potential targets selected through the above process were investigated through molecular docking. Seventy-six active ingredients were selected with the following criteria: OB ≥ 30%, DL ≥ 0.18. 383 targets of CDDP and 1488 targets on AP were gathered, respectively. Afterwards, 194 common targets of CDDP and anti-AP targets were defined, of which 12 were core targets. GO enrichment analysis indicated that CDDP acted on AP by response to lipopolysaccharide, regulating the reactive oxygen species and metal ion metabolism, and epithelial cell proliferation. In addition, KEGG enrichment analysis indicated that the signaling pathways were notably enriched in lipid and atherosclerosis, fluid shear stress and atherosclerosis, IL-17 signaling pathway, EGFR tyrosine kinase inhibitor resistance, PI3K-Akt signaling pathway, and TNF signaling pathway. Moreover, the molecular docking manifested excellent binding capacity between the active ingredients and targets on AP. This study comprehensively illustrated the bioactive, potential targets, and molecular mechanisms of CDDP against AP, offering fresh perspectives into the molecular mechanisms of CDDP in preventing and treating AP.

Application of network pharmacology and molecular docking to explore the mechanism of Danggui Liuhuang Tang against hyperthyroidism.

To investigate the mechanism of Danggui Liuhuang Tang (DGLHT) in the treatment of hyperthyroidism (HT), we explored the multi-component, multi-target, and multi-pathway mechanism based on the network pharmacology method of traditional Chinese medicine. To take DGLHT into the blood components as the research object, we used GeneCards, Drungbank, Therapeutic Target Database (TTD), Online Mendelian Inheritance in Man (OMIM), Pharmacogenetics and Pharmacogenomics Knowledge Base (PharmGKB), and other databases to predict the potential target of the components. Then, it was integrated with the predicted targets of HT disease to obtain the potential targets of DGLHT in the treatment of HT. We used String database and Cytoscape software for protein-protein interaction network (PPI) construction, and DAVID platform for Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation, the Cytoscape software was used to construct a "component-target-pathway" network; the AutoDock Vina platform was used to conduct molecular docking between the blood entry components and key targets. According to the analysis, a total of 93 active ingredients, 348 disease-related targets, and 36 potential targets were screened out. Among them, key targets such as MAPK1, CCND1, AKT1, and TNF exert curative effects, and the main pathways are the HIF-1 signaling pathway, FoxO signaling pathway, Chemokine signaling pathway, TNF signaling pathway, Toll-like receptor signaling pathway, T cell receptor signaling pathway, Jak-STAT signaling pathway, and other pathways. Molecular docking results verified the interaction between active ingredients and key targets, among which rustication and quercetin had high docking affinity with key target proteins MAPK1 and CCND1. This study preliminary revealed that DGLHT has the characteristics of multi-component, multi-target, and multi-pathway in the treatment of HT, and it established a scientific foundation for a more detailed investigation of DGLHT's molecular mechanism in the treatment of HT.

Exploring the Molecular Mechanisms of Astragalus Membranaceus in Treating Pre-eclampsia Using Network Pharmacology and Molecular Docking

Background: Pre-eclampsia (PE) is a pregnancy-related complication that has a global prevalence of 3-5% among pregnant women. Objective: The objective of this study is to examine the molecular mechanism underlying the therapeutic effects of Astragalus membranaceus (AE) in the treatment of PE through the application of network pharmacology and molecular docking. Methods: The databases, including TCMSP, Uniprot, Genecards, STRING, and DAVID, and software, including jvenn, Cytoscape, and AutoDock Vina, were used to do the analysis. Results: Sixteen AE-related active ingredients were screened, involving 127 targets, among which the main active ingredients included kaempferol, quercetin, and jaranol, etc. The primary targets of AE for the management of PE encompassed AKT1, CASP3, EGFR, IL1B, IL6, MMP9, PTGS2, TNF, TP53, and VEGFA. The outcomes of the enrichment analysis revealed that AE was predominantly implicated in pathways such as the IL-17 signaling pathway and PI3K-Akt signaling pathway, among others. The molecular docking findings confirmed that the principal active constituents exhibit favorable binding to their central targets. Specifically, the molecular docking results evinced that the primary active ingredients evince robust binding activity towards the core targets. Conclusion: AE has the potential to act synergistically in the management of PE by engaging multiple components, targets, and pathways, thereby establishing a basis for further exploration of its material basis and mechanism of action.

Exploring the mechanism of Nigella sativaagainst colorectal cancer by network pharmacology and molecular docking

Background:Nigella sativa, generally known as black seed or black cumin, has a rich historical background in traditional medicine for its diverse health benefits.Objective:The aim of the study explore the potential effects of Nigella sativa (NS) on colorectal cancer (CC) through the application of network pharmacology and molecular docking.Methods: Network pharmacology (NP) analysis was conducted to identify pertinent colorectal cancer targets and compounds sourced from relevant databases. Subsequently, protein-protein interaction (PPI) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were employed to delineate critical molecular pathways, while molecular docking simulations study were employed to validate the binding interactions at active sites.Results:Network analysis of compound-target interactions revealed a network comprising 319 nodes and 410 edges, indicating a complex interplay between the derivatives and their associated targets. The PPI analysis underscored the significant interactions within the network, particularly with targets known to be involved in colorectal cancer regulation. KEGG pathway analysis highlighted the importance of EGFR and PI3K pathways in the context of colorectal cancer. Notably, molecular docking studies identified Nigellicine as having the highest affinity for key colorectal cancer-related targets, including AKT1(-7.6 kcal/mol), IL6(-6.2 kcal/mol), ALB(-7.1 kcal/mol) and HSP90AA1(-8.2).Conclusion: The integration of network analysis and molecular docking studies provided collectively support the colorectal cancer characteristics of the compounds, emphasizing the need for further research to develop novel pharmacological interventions for colorectal cancer management.

Analysis of the mechanism of action of Euphorbia fischeriana Steud on cirrhosis based on network pharmacology.

This study aimed to employ network pharmacology to elucidate the mechanism by which Euphorbia fischeriana Steud (EFS) exhibits the efficacy on cirrhosis. The compounds and targets of EFS were retrieved from Traditional Chinese Medicine Integrated Database and Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). Next, these compounds and targets were analyzed based on protein-protein interaction (PPI) network. Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling network was established based on KEGG database. We constructed a compound-compound target-intersection target-pathway PPI network, including 20 compounds, 19 intersection targets between compound targets and EFS targets. Among the 20 compounds, 8-Isopentenyl-kaempferol has the most targets, with 27 targets, followed by 3,4',5-Trihydroxy-7-methoxy-8-isopentenylflavone, Formononetin, Isoxanthohumol, and Isokurarinone with potential targets of 26, 22, 18, and 14, respectively. Top 5 targets are HSP90AA1, PTGS2, NOS2, MAPK14, and PPARG. KEGG pathway enrichment analysis showed that pathways such as Hepatitis B, Hepatitis C, Lipid and atherosclerosis, and AGE-RAGE signaling pathway in diabetic complications were closely related to the infection and abnormal metabolism of the liver. The application of network pharmacology could identify potential targets of EFS with a low false-positive rate and provide novel insight into the mechanism of action of EFS on cirrhosis.

Raddeanin A promotes autophagy-induced apoptosis by inactivating PI3K/AKT/mTOR pathway in lung adenocarcinoma cells.

Non-small-cell lung cancer (NSCLC) is the most common cancer in the world. Previous studies have shown that Raddeanin A (RA) exhibited distinct antitumor properties in gastric and colon cancer. This study aimed to investigate the pharmacological actions and intrinsic mechanisms of RA in NSCLC. Through the application of network pharmacology, the potential targets of RA for NSCLC therapy such as SRC, MAPK1, and STAT3 were excavated. Enrichment analyses showed that these targets were concerned with the regulation of cell death, regulation of MAPK cascade, Ras signaling pathway, and PI3K/AKT signaling pathway. Meanwhile, 13 targets of RA were identified as autophagy-related genes. Our experiment data showed that RA effectively inhibited proliferation and induced apoptosis in lung cancer cells A549. We also found that RA could induce autophagy simultaneously. Furthermore, the autophagy induced by RA had a synergistic effect with apoptosis and contributed to cell death. Additionally, RA could downregulate the activity of the PI3K/AKT/mTOR pathway. Generally, our results indicated the antitumor effect and underlying mechanisms of RA on apoptosis and autophagy in A549 cells, suggesting that RA could be used as an effective antineoplastic agent.

Application of network pharmacology in the study of mechanism of Chinese medicine in the treatment of ulcerative colitis: A review.

Network pharmacology is a research method based on a multidisciplinary holistic analysis of biological systems, which coincides with the idea of the holistic view of traditional Chinese medicine. In this review, we summarized the use of network pharmacology technology through studying Chinese medicine single medicine or Chinese medicine compound research ideas and methods for the treatment of ulcerative colitis, based on the application of the current network pharmacology in Chinese medicine research, including the important role in the mechanism of the prediction and verification, to search for new ideas for disease diagnosis and treatment, this study summarizes the application of network pharmacology in the treatment of ulcerative colitis in traditional Chinese medicine, including monotherapy and compound therapy, and considers that relevant research studies have fully demonstrated the function characteristics of the multi-component, multi-target, and multi-pathway of traditional Chinese medicine, and can also explain the connotation of “selecting appropriate treatment methods according to the differences and similarities of pathogenesis” of traditional Chinese medicine. Finally, we raised important questions about the prospects and limitations of network pharmacology, such as differences caused by different data collection methods, a considerable lag, and so on.

Application of network pharmacology and molecular docking approach to explore active compounds and potential pharmacological mechanisms of Aconiti Lateralis Radix Praeparata and Lepidii Semen Descurainiae Semen for treatment of heart failure.

Background:Heart failure (HF) is the end stage of the development of heart disease, whose prognosis is poor. The previous research of our team indicated that the formulae containing Aconiti Lateralis Radix Praeparata and Lepidii Semen Descurainiae Semen (ALRP-LSDS) could inhibit myocardial hypertrophy, inhibit cardiomyocyte apoptosis, delay myocardial remodeling (REM), and improve the prognosis of patients with HF effectively. In order to explore the mechanism of ALRP-LSDS for the treatment of HF, a combined approach of network pharmacology and molecular docking was conducted.Methods:Public database TCMSP was used to screen the active compounds of ALRP-LSDS. The targets of screened active compounds were obtained from the TCMSP database and predicted using the online analysis tool PharmMapper. The targets of HF were obtained from 6 databases including GeneCards, OMIM, DrugBank, TTD, PharmGKB, and DisGeNET. Protein–protein interaction and enrichment analysis were performed, respectively, by STRING and Metascape online tools after merging the targets of active compounds and HF. Cytoscape software was used to conduct networks. Finally, molecular docking was performed by Vina to verify the correlation between key targets and active compounds.Results:Final results indicated that the active compounds including β-sitosterol, isorhamnetin, quercetin, kaempferol, and (R)-norcoclaurine, the targets including AKT1, CASP3, and MAPK1 might be the main active compounds and key targets of ALRP-LSDS for the treatment of HF separately. The binding ability of AKT1 to the main active compounds was better compared with the other 2 key targets, which means it might be more critical. The pathways including AGE-RAGE signaling pathway in diabetic complications, Pathways in cancer, and Fluid shear stress and atherosclerosis might play important roles in the treatment of HF with ALRP-LSDS. In general, ALRP-LSDS could inhibit cardiomyocyte apoptosis, delay REM, and improve cardiac function through multicompound, multitarget, and multipathway, which contributes to the treatment of HF.Conclusions:Based on the combined approach of network pharmacology and molecular docking, this study screened out the main active compounds, key targets, and main pathways of ALRP-LSDS for the treatment of HF, and revealed its potential mechanisms, providing a theoretical basis for further research.

Optimizing component formula suppresses lung cancer by blocking DTL-mediated PDCD4 ubiquitination to regulate the MAPK/JNK pathway

Ethnopharmacological relevanceSalvia miltiorrhiza Bunge and Panax ginseng C. A. Meyer have special curative effect on cancer treatment. The optimizing component formula (OCF) extracted from those two herbs was in line with the anti-lung cancer treatment principle of activating blood and supplementing ‘Qi’. However, the study on the mechanism of component formula has always been an insurmountable challenge. Nowadays, the application of network pharmacology and artificial intelligence (AI) in the field of TCM provides new ideas for the study of new targets and mechanisms of TCM, which promotes the modernization of TCM. Aim of the studyThis study aims to further explore the anti-lung cancer mechanism of OCF by using an integrated strategy of network pharmacology and AI technology. Materials and methodsBioinformatic analysis was used to analyze the expression levels, prognosis and survival of DTL and PDCD4 in cancer patients. The binding strength of OCF and DTL was simulated by molecular docking, and the affinity between them was detected by Bio-layer interferometry. Network pharmacology was used to predict the active components, potential targets and pathways of OCF. The association between key targets and their corresponding components and DTL was analyzed by Ingenuity Pathway Analysis (IPA). MTT assay, colony formation assay, wound-healing assay and transwell assay were used to verify the inhibitory effects of OCF on lung cancer cells in vitro. qRT-PCR and Western blot assay were used to detect the effects of OCF on mRNA and protein expression of DTL, PDCD4 and key genes in MAPK/JNK pathways. ResultsBioinformatics analysis showed that DTL was significantly up-regulated in lung cancer, which was associated with high malignancy rate, high metastasis rate and poor prognosis of primary tumor. PDCD4 was down-regulated in lung cancer, and associated with high metastasis rate and poor prognosis. The good affinity between OCF and DTL was predicted and verified by molecular docking and Bio-layer interferometry. Based on the network pharmacological databases, 40 active components and 220 corresponding targets of OCF were screened out. KEGG analysis showed that OCF component targets were mainly enriched in MAPK signaling pathway. IPA results showed the interrelationship between DTL, PDCD4, MAPK pathway genes and their corresponding OCF components. In addition, in vitro experiments demonstrated anti-lung cancer activity of OCF, as validated, via impairing cell viability and cell proliferation, as well as inhibiting migration and invasion abilities in lung cancer cells. qRT-PCR showed that OCF down-regulated the mRNA expression of DTL, MAP4K1, JNK, c-Jun and c-Myc, and up-regulated the mRNA expression of PDCD4 and P53 genes in A549 lung cancer cells. Western blot suggested that OCF suppressed the protein level of DTL and blocked the ubiquitination of PDCD4 in A549 lung cancer cells, and down-regulated the protein levels of MAP4K1, p-JNK and p-c-Jun while up-regulated the proteins expression level of P53. ConclusionsOCF might elicit an anti-lung cancer effect by blocking DTL-mediated PDCD4 ubiquitination and suppression of the MAPK/JNK pathway. Meanwhile, our work revealed that network pharmacology and AI technology strategy are cogent means of studying the active components and mechanism of TCM.

Network Pharmacology and In Vitro Experimental Verification Reveal the Mechanism of the Hirudin in Suppressing Myocardial Hypertrophy.

Background: Myocardial hypertrophy is a complex pathological process, which is a common manifestation during the development of various cardiovascular diseases. Hirudin has been shown to have therapeutic effects on a variety of cardiovascular diseases, however, its therapeutic effect on myocardial hypertrophy is still unknown, and its chemical and pharmacological characteristics remain to be elucidated. Methods: In this study, the network pharmacology method was used to characterize the mechanism of hirudin on myocardial hypertrophy. The potential protein targets of hirudin and myocardial hypertrophy were both obtained from the Genecards database, and potential pathways associated with genes were identified by Gene Ontology and pathway enrichment analysis, and the data were displayed in a visual manner. Subsequently, the potential mechanism of action of hirudin on myocardial hypertrophy predicted by network pharmacology analysis was verified by molecular docking, and finally, the main findings were further verified by in vitro experiments by molecular biology techniques. Based on the results obtained from the study of H9c2 cell line, the inhibitory effect of hirudin on myocardial hypertrophy was further proved in the primary rat cardiomyocytes. Results: A total of 250 targets of hirudin, and 5,376 targets related to myocardial hypertrophy after deduplication were collected. The drug-disease network showed the relationship between hirudin, myocardial hypertrophy, and the targets. Further, systematic analysis from the PPI network indicated that blood coagulation, vesicle lumen, and signaling receptor activator activity may be the potential mechanisms of hirudin in the treatment of myocardial hypertrophy, and the PI3K/AKT signaling pathway may be the most relevant to the therapeutic effect of hirudin. Then, three therapeutic targets that were highly related to myocardial hypertrophy were extracted. Hirudin can be highly bound to STAT3, IL-6, and MAPK1 and found by molecular docking, which may be the basis for its inhibitory effect on myocardial hypertrophy. In addition, in vitro experiments showed that hirudin could inhibit AngII-induced hypertrophy and death of H9c2 cells, and significantly reduce the mRNA and protein expression levels of STAT3, MAPK1, and IL-6. The above conclusions were verified in primary rat cardiomyocytes. Conclusion: Hirudin can be used to treat myocardial hypertrophy through a complex mechanism. The application of network pharmacology and experimental validation can promote the application of hirudin in cardiovascular diseases and the interpretation and understanding of molecular biological mechanisms.

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

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.

Luteolin Potentially Treating Prostate Cancer and COVID-19 Analyzed by the Bioinformatics Approach: Clinical Findings and Drug Targets.

Coronavirus disease 2019 (COVID-19) is a serious epidemic, characterized by potential mutation and can bring about poor vaccine efficiency. It is evidenced that patients with malignancies, including prostate cancer (PC), may be highly vulnerable to the SARS-CoV-2 infection. Currently, there are no existing drugs that can cure PC and COVID-19. Luteolin can potentially be employed for COVID-19 treatment and serve as a potent anticancer agent. Our present study was conducted to discover the possible drug target and curative mechanism of luteolin to serve as treatment for PC and COVID-19. The differential gene expression of PC cases was determined via RNA sequencing. The application of network pharmacology and molecular docking aimed to exhibit the drug targets and pharmacological mechanisms of luteolin. In this study, we found the top 20 up- and downregulated gene expressions in PC patients. Enrichment data demonstrated anti-inflammatory effects, where improvement of metabolism and enhancement of immunity were the main functions and mechanism of luteolin in treating PC and COVID-19, characterized by associated signaling pathways. Additional core drug targets, including MPO and FOS genes, were computationally identified accordingly. In conclusion, luteolin may be a promising treatment for PC and COVID-19 based on bioinformatics findings, prior to future clinical validation and application.

Application of network pharmacology in uncovering the biological basis of using the Banxia Baizhu Tianma decoction for hypertension treatment

Application of network pharmacology in uncovering the biological basis of using the Banxia Baizhu Tianma decoction for hypertension treatment

Application of network pharmacology in the prevention and treatment of COVID-19 by traditional Chinese medicine

Application of network pharmacology in the prevention and treatment of COVID-19 by traditional Chinese medicine

INPUT: An intelligent network pharmacology platform unique for traditional Chinese medicine

The application of network pharmacology has greatly promoted the scientific interpretation of disease treatment mechanism of traditional Chinese medicine (TCM). However, the data required by network pharmacology analysis were scattered in different resources. In the present work, by integrating and reorganizing the data from multiple resources, we developed the intelligent network pharmacology platform unique for traditional Chinese medicine, called INPUT (http://cbcb.cdutcm.edu.cn/INPUT/), for automatically performing network pharmacology analysis. Besides the curated data collected from multiple resources, a series of bioinformatics tools for network pharmacology analysis were also embedded in INPUT, which makes it become the first automatic platform able to explore the disease treatment mechanisms of TCM. With the built-in tools, researchers can also analyze their own in-house data and obtain the results of pivotal ingredients, GO and KEGG pathway, protein-protein interactions, etc. In addition, as a proof-of-principle, INPUT was applied to decipher the antidepressant mechanism of a commonly used prescription. In summary, INPUT is a powerful platform for network pharmacology analysis and will facilitate the researches on drug discovery.

Network Pharmacology Study on Molecular Mechanisms of Zhishi Xiebai Guizhi Decoction in the Treatment of Coronary Heart Disease.

Background Coronary heart disease is characterized by the formation of arterial plaque. If not taken seriously, it will cause serious consequences such as myocardial infarction and heart failure. Zhishi Xiebai Guizhi Decoction first appeared in “Synopsis of Prescriptions of the Golden Chamber” and is a representative prescription for the treatment of coronary heart disease. This study aims to explain the mechanism of Zhishi Xiebai Guizhi Decoction in the treatment of coronary heart disease through network pharmacology and clinical trials. Methods We first identified the core compounds of Zhishi Xiebai Guizhi Decoction and their potential targets through TCMSP. Then, We analyzed the molecular targets of Zhishi Xiebai Guizhi Decoction in coronary heart disease with OMIM and GeneCards databases. After the common targets were screened out, we manage to figure out the pathways of these target genes through STRING. Finally, we verify the treatment results in clinical trials. Results Through network pharmacology analysis, we discovered that several core compounds of Zhishi Xiebai Guizhi Decoction have anti-inflammatory effects and are of great significance to treatment of cardiovascular diseases. The mechanism may be closely related to PPARγ, inflammation, TNF signaling pathway, AMPK signaling pathway, and PI3K-Akt signaling pathway. Clinical trials have also proved the key role of inflammation. Conclusions Zhishi Xiebai Guizhi Decoction may play a role in treating coronary heart disease by activating PPARγ. TNF signaling pathway, AMPK signaling pathway, and PI3K-Akt signaling pathway are potential mechanisms as well. The application of network pharmacology can provide a novel method for the research of Chinese herbal medicine. We hope that Zhishi Xiebai Guizhi Decoction will be recognized as a complementary or alternative treatment for coronary heart disease.

Active components and action mechanism of Shenmai Injection in treatment of atrial fibrillation based on network pharmacology and molecular docking

This study aims to explore the active components and molecular mechanism of Shenmai Injection in the treatment of atrial fibrillation(AF) based on the application of network pharmacology and molecular docking technology. The chemical components of single herbs of Shenmai Injection were collected from TCMSP and TCMID, with the standard chemical name and PubChem CID(referred to as CID) obtained from PubChem database. The active components were screened using SwissADME, and their targets were predicted using SwissTargetPrediction. Targets related to AF treatment were identified using GeneCards, OMIM, and other databases. Venn diagram was constructed using Venny 2.1 to obtain the intersection targets. The single herb-active component-potential target network was constructed using Cytoscape, and the clusterProfiler R function package was used to perform the gene ontology(GO) and Kyoto encyclopedia of genes and genomes(KEGG) pathway enrichment. The protein-protein interaction(PPI) network of intersection targets was generated based on the STRING database. The hub target protein was identified by visualization using Cytoscape, and then docked to its reverse-selected active components. The analysis showed that there were 65 active components with 681 corresponding targets in Shenmai Injection, 2 798 targets related to AF treatment, and 235 intersection targets involving 2 549 GO functions and 153 KEGG pathways. Finally, hub target proteins, including RAC-alpha serine/threonine-protein kinase(AKT1), phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha(PIK3 CA), and estrogen receptor 1(ESR1), were screened out by PPI network visualization. The molecular docking was performed for 39 active components screened out in reverse, among which 30 active components de-monstrated high affinity. Among them, homoisoflavanoids CID 10871974, CID 5319742, and CID 10361149 had stronger affinity docking with AKT1. This study preliminarily indicates that Shenmai Injection treats AF through multiple components, multiple targets, and multiple pathways. Homoisoflavonoids of Ophiopogon japonicus are its important active components, which target AKT1 to regulate metabolism, inflammation, and apoptosis in AF treatment.

Application of network pharmacology and molecular docking to elucidate the potential mechanism of Astragalus–Scorpion against prostate cancer

The present study aimed to investigate the molecular mechanism of the Astragalus-Scorpion drug pair in the treatment of prostate cancer (PCa). We employed network pharmacology and molecular docking technology to retrieving the active ingredients and corresponding targets of Astragalus-Scorpion by using TCMSP, BATMAN-TCM, TCMID and Swiss Target Prediction Databases. The targets related to PCa were retrieved through GeneCards. Cytoscape software was used to construct the 'active ingredient-target disease' network, and GO and KEGG enrichment analyses were performed on the common targets. Autodock software was used for molecular docking verification. In total, 26 active ingredients, 340 potential targets related to active ingredients and 122 common targets were screened from Astragalus-Scorpion drug pair. The core targets of the protein-protein interaction (PPI) network were JUN, AKT1, IL6, MAPK1 and RELA, whereas the core active ingredients were quercetin, kaempferol, formononetin, 7-o-methylisomucronulatol and calycosin. Nearly 762 GO entries and 154 pathways were obtained by using the pathway enrichment analysis. Molecular docking results revealed that quercetin and kaempferol bind to AKT1 and formononetin binds to RELA, all of which were found to be stable bounds.