Network Pharmacology-based Strategy Research Articles

Exploring the Potential Mechanism of Shufeng Jiedu Capsule for Treating COVID-19 by Comprehensive Network Pharmacological Approaches and Molecular Docking Validation

Shufeng Jiedu capsule (SFJDC) is a well-known Chinese patent drug that is recommended as a basic prescription and applied widely in the clinical treatment of COVID-19. However, the exact molecular mechanism of SFJDC remains unclear. The present study aims to determine the potential pharmacological mechanisms of SFJDC in the treatment of COVID-19 based on network pharmacology. The network pharmacology-based strategy includes collection and analysis of active compounds and target genes, network construction, identification of key compounds and hub target genes, KEGG and GO enrichment, recognition and analysis of main modules, as well as molecule docking. A total of 214 active chemical compounds and 339 target genes of SFJDC were collected. Of note, 5 key compounds (β -sitosterol, luteolin, kaempferol, quercetin, and stigmasterol) and 10 hub target genes (TP53, AKT1, NCOA1, EGFR, PRKCA, ANXA1, CTNNB1, NCOA2, RELA and FOS) were identified based on network analysis. The hub target genes mainly enriched in pathways including MAPK signaling pathway, PI3K-Akt signaling pathway and cAMP signaling pathway, which could be the underlying pharmacological mechanisms of SFJDC for treating COVID-19. Moreover, the key compounds had high binding activity with three typical target proteins including ACE2, 2OFZ, and 1SSK. By network pharmacology analysis, SFJDC was found to effectively improve immune function and reduce inflammatory responses based on its key compounds, hub target genes, and the relevant pathways. These findings may provide valuable evidence for explaining how SFJDC exerting the therapeutic effects on COVID-19, providing a holistic view for further clinical application.

Elucidation of the Mechanisms and Molecular Targets of Qishen Yiqi Formula for the Treatment of Pulmonary Arterial Hypertension using a Bioinformatics/Network Topology-based Strategy.

Qishen Yiqi formula (QSYQ) is used to treat cardiovascular disease in the clinical practice of traditional Chinese medicine. However, few studies have explored whether QSYQ affects pulmonary arterial hypertension (PAH), and the mechanisms of action and molecular targets of QSYQ for the treatment of PAH are unclear. A bioinformatics/network topology-based strategy was used to identify the bioactive ingredients, putative targets, and molecular mechanisms of QSYQ in PAH. A network pharmacology-based strategy was employed by integrating active component gathering, target prediction, PAH gene collection, network topology, and gene enrichment analysis to systematically explore the multicomponent synergistic mechanisms. In total, 107 bioactive ingredients of QSYQ and 228 ingredient targets were identified. Moreover, 234 PAH-related differentially expressed genes with a |fold change| >2 and an adjusted P value < 0.005 were identified between the PAH patient and control groups, and 266 therapeutic targets were identified. The pathway enrichment analysis indicated that 85 pathways, including the PI3K-Akt, MAPK, and HIF-1 signaling pathways, were significantly enriched. TP53 was the core target gene, and 7 other top genes (MAPK1, RELA, NFKB1, CDKN1A, AKT1, MYC, and MDM2) were the key genes in the gene-pathway network based on the effects of QSYQ on PAH. An integrative investigation based on network pharmacology may elucidate the multicomponent synergistic mechanisms of QSYQ in PAH and lay a foundation for further animal experiments, human clinical trials and rational clinical applications of QSYQ.

Network Pharmacology-Based Strategy Reveals the Effects of Hedysarum multijugum Maxim.-Radix Salviae Compound on Oxidative Capacity and Cardiomyocyte Apoptosis in Rats with Diabetic Cardiomyopathy.

Objective To explore the effects of the Hedysarum multijugum Maxim.-Radix Salviae compound (Huangqi-Danshen Compound (HDC)) on oxidative capacity and cardiomyocyte apoptosis in rats with diabetic cardiomyopathy by a network pharmacology-based strategy. Methods Traditional Chinese Medicine (TCM)@Taiwan, TCM Systems Pharmacology Database and Analysis Platform (TCMSP), TCM Integrated Database (TCMID), and High-Performance Liquid Chromatography (HPLC) technology were used to obtain and screen HDC's active components, and the PharmMapper database was used to predict HDC human target protein targets. The DCM genes were collected from the GeneCards and OMIM databases, and the network was constructed and analyzed by Cytoscape 3.7.1 and the Database for Annotation, Visualization, and Integrated Discovery (DAVID). Finally, HDC was used to intervene in diabetic cardiomyopathy (DCM) model rats, and important biological processes and signaling pathways were verified using techniques such as immunohistochemistry. Results A total of 176 of HDC's active components and 442 potential targets were obtained. The results of network analysis show that HDC can regulate DCM-related biological processes (such as negative regulation of the apoptotic process, response to hypoxia, the steroid hormone-mediated signaling pathway, cellular iron ion homeostasis, and positive regulation of phosphatidylinositol 3-kinase signaling) and signaling pathways (such as the HIF-1 signaling pathway, the estrogen signaling pathway, insulin resistance, the PPAR signaling pathway, the VEGF signaling pathway, and the PI3K-Akt signaling pathway). Animal experiments show that HDC can reduce fasting plasma glucose (FPG), HbA1c, and malondialdehyde (MDA) and increase superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) (P < 0.05). The results of immunohistochemistry showed that HDC can regulate the protein expression of apoptosis-related signaling pathways in DCM rats (P < 0.05). Conclusion It was initially revealed that HDC improves DCM through its antiapoptotic and anti-inflammatory effects. HDC may play a therapeutic role by improving cardiomyocyte apoptosis in DCM rats.

A network-based pharmacology study of active compounds and targets of Fritillaria thunbergii against influenza

Seasonal and pandemic influenza infections are serious threats to public health and the global economy. Since antigenic drift reduces the effectiveness of conventional therapies against the virus, herbal medicine has been proposed as an alternative. Fritillaria thunbergii (FT) have been traditionally used to treat airway inflammatory diseases such as coughs, bronchitis, pneumonia, and fever-based illnesses. Herein, we used a network pharmacology-based strategy to predict potential compounds from Fritillaria thunbergii (FT), target genes, and cellular pathways to better combat influenza and influenza-associated diseases. We identified five compounds, and 47 target genes using a compound-target network (C-T). Two compounds (beta-sitosterol and pelargonidin) and nine target genes (BCL2, CASP3, HSP90AA1, ICAM1, JUN, NOS2, PPARG, PTGS1, PTGS2) were identified using a compound-influenza disease target network (C-D). Protein-protein interaction (PPI) network was constructed and we identified eight proteins from nine target genes formed a network. The compound-disease-pathway network (C-D-P) revealed three classes of pathways linked to influenza: cancer, viral diseases, and inflammation. Taken together, our systems biology data from C-T, C-D, PPI and C-D-P networks predicted potent compounds from FT and new therapeutic targets and pathways involved in influenza.

Theoretical Study of the Molecular Mechanism of Maxingyigan Decoction Against COVID-19: Network Pharmacology-based Strategy.

Maxingyigan (MXYG) decoction is a traditional Chinese medicine (TCM) prescription. However, how MXYG acts against coronavirus disease 2019 (COVID-19) is not known. We investigated the active ingredients and the therapeutic targets of MXYG decoction against COVID-19. A network pharmacology strategy involving drug-likeness evaluation, prediction of oral bioavailability, network analyses, and virtual molecular docking was used to predict the mechanism of action of MXYG against COVID-19. Thirty-three core COVID-19-related targets were identified from 1023 gene targets through analyses of protein-protein interactions. Eighty-six active ingredients of MXYG decoction hit by 19 therapeutic targets were screened out by analyses of a compound-compound target network. Via network topology, three "hub" gene targets (interleukin (IL-6), caspase-3, IL-4) and three key components (quercetin, formononetin, luteolin) were recognized and verified by molecular docking. Compared with control compounds (ribavirin, arbidol), the docking score of quercetin to the IL-6 receptor was highest, with a score of 5. Furthermore, the scores of three key components to SARS-CoV-2 are large as 4, 5, and 5, respectively, which are even better than those of ribavirin at 3. Bioinformatics analyses revealed that MXYG could prevent and treat COVID-19 through anti-inflammatory and immunity-based actions involving activation of T cells, lymphocytes, and leukocytes, as well as cytokine-cytokine-receptor interaction, and chemokine signaling pathways. The hub genes of COVID-19 helped to reveal the underlying pathogenesis and therapeutic targets of COVID-19. This study represents the first report on the molecular mechanism of MXYG decoction against COVID-19.

Network Pharmacology-Based Prediction and Verification of the Active Ingredients and Potential Targets of Zuojinwan for Treating Colorectal Cancer.

BackgroundZuojinwan (ZJW), a famous Chinese medicine formula, has been widely used to treat colorectal cancer (CRC). However, its bioactive compounds, potential targets, and molecular mechanism remain largely elusive.AimA network pharmacology-based strategy combined with molecular docking studies and in vitro validation were employed to investigate bioactive compounds, potential targets, and molecular mechanism of ZJW against CRC.Materials and MethodsBioactive compounds and potential targets of ZJW, as well as related genes of CRC, were acquired from public databases. Important ingredients, potential targets, and signaling pathways were determined through bioinformatics analysis, including protein–protein interaction (PPI), the Gene Ontology (GO), and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Subsequently, molecular docking and cell experiments were performed to further verify the findings.ResultsA total of 36 bioactive ingredients of ZJW and 163 gene targets of ZJW were identified. The network analysis revealed that quercetin, baicalein, wogonin, beta-sitosterol, and isorhamnetin may be candidate agents. The AKT1, JUN, CDKN1A, BCL2L1, and NCOA1 could become potential drug targets. The KEGG indicated that PI3K-AKT signaling pathway may play an important role in the effect of ZJW against CRC. Molecular docking suggested that quercetin, baicalein, and wogonin combined well with AKT1 and JUN. The in vitro experiment showed that quercetin, the most important ingredient of ZJW, could induce apoptosis of HCT116 cells through PI3K-Akt signaling pathway. This finding was congruent with the prediction obtained through the network pharmacology approach.ConclusionThis study comprehensively illuminated the active ingredients, potential targets, and molecular mechanism of ZJW against CRC. It also provided a promising approach to uncover the scientific basis and therapeutic mechanism of traditional Chinese medicine (TCM) formula treating for disease.

Mechanism of YuPingFeng in the Treatment of COPD Based on Network Pharmacology.

YuPingFeng (YPF) granules are a classic herbal formula extensively used in clinical practice in China for the treatment of COPD. However, the pathological mechanisms of YPF in COPD remain undefined. In the present research, a network pharmacology-based strategy was implemented to elucidate the underlying multicomponent, multitarget, and multipathway modes of action of YPF against COPD. First, we identified putative YPF targets based on TCMSP databases and constructed a network containing interactions between putative YPF targets and known therapeutic targets of COPD. Next, two topological parameters, “degree” and “closeness,” were calculated to identify target genes in the network. The major hubs were imported to the MetaCore database for pathway enrichment analysis. In total, 23 YPF active ingredients and 83 target genes associated with COPD were identified. Through protein interaction network analysis, 26 genes were identified as major hubs due to their topological importance. GO and KEGG enrichment analysis results revealed YPF to be mainly associated with the response to glucocorticoids and steroid hormones, with apoptotic and HIF-1 signalling pathways being dominant and correlative pathways. The promising utility of YPF in the treatment of COPD has been demonstrated by a network pharmacology approach.

Can network pharmacology identify the anti-virus and anti- inflammatory activities of Shuanghuanglian oral liquid used in Chinese medicine for respiratory tract infection?

IntroductionShuanghuanglian (SHL) oral liquid is a well-known traditional Chinese medicine preparation administered for respiratory tract infections in China. However, the underlying pharmacological mechanisms remain unclear. The present study aims to determine the potential pharmacological mechanisms of SHL oral liquid based on network pharmacology. MethodsA network pharmacology-based strategy including collection and analysis of putative compounds and target genes, network construction, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and Gene Ontology (GO) enrichment, identification of key compounds and target genes, and molecule docking was performed in this study. ResultsA total of 82 bioactive compounds and 226 putative target genes of SHL oral liquid were collected. Of note, 28 hub target genes including 4 major hub target genes: estrogen receptor 1 (ESR1), nuclear receptor coactivator 2 (NCOA2), nuclear receptor coactivator 1 (NCOA1), androgen receptor (AR) and 5 key compounds (quercetin, luteolin, baicalein, kaempferol and wogonin) were identified based on network analysis. The hub target genes mainly enriched in pathways including PI3K-Akt signaling pathway, human cytomegalovirus infection, and human papillomavirus infection, which could be the underlying pharmacological mechanisms of SHL oral liquid for treating diseases. Moreover, the key compounds had great molecule docking binding affinity with the major hub target genes. ConclusionUsing network pharmacology analysis, SHL oral liquid was found to contain anti-virus, anti-inflammatory, and “multi-compounds and multi-targets” with therapeutic actions. These findings may provide a valuable direction for further clinical application and research.

A network pharmacology-based strategy deciphers the multitarget pharmacological mechanism of Reduning injection in the treatment of influenza

IntroductionInfluenza remains a major public health concern. With the increasing resistance to existing anti-influenza drugs, the development of new drugs is urgently needed. Reduning injection is a commonly used drug in the clinical treatment of influenza. This preliminary work explored the molecular mechanisms underlying the action of Reduning injection in the treatment of influenza. MethodsNetwork pharmacology and molecular docking simulation were adopted to explore the mechanisms. ResultsThirty-four compounds and 668 compound targets were included in this study. Eight common targets, namely, CXCL10, CCL2, IL6, STAT1, PTPN11, TNF, BRAF and MMP9, were considered to be the key targets. Sixteen compounds were closely related to influenza, among which quercetin and luteolin showed the highest degrees. Two GO terms were obtained: “positive regulation of ERK1 and ERK2 cascade” and “cellular response to lipopolysaccharide”. Three KEGG entries containing “influenza A” and “TNF signaling pathway” were obtained. All compounds docked well with the key targets. ConclusionReduning injection may have an effect on cytokine storms and protect patients from lung damage. The compounds of Reduning injection can inhibit viral-cell fusion and stop viral replication through NF-kappa B signaling, the MAPK cascade and TNF signaling pathways. Reduning injection may treat influenza by regulating viral infection pathways, signal transduction pathways and immune systems.

Network pharmacology-based strategy to investigate pharmacological mechanisms of Tinospora sinensis for treatment of Alzheimer's disease

Ethnopharmacological relevanceTinospora sinensis (Lour.) Merr. belongs to the family Menispermaceae. It is called LeZhe and is widely used as a kind of folk medicine especially in the Tibetan Plateau of China. T. sinensis has the functions of clearing away heat and detoxification, dispelling wind and dredging collaterals, calming and soothing the nerves. T. sinensis is an effective medicine for the prevention and treatment of aging diseases such as Alzheimer's disease (AD) in the Tibetan Plateau of China, whereas its material basis and underlying mechanisms are not clear. The aim of this study was to investigate the material basis and potential mechanisms of T. sinensis in the treatment of AD by using network pharmacology and molecular docking. Materials and methodsIn this study, targets were collected from DrugBank database, Therapeutic Target Database (TTD) and literatures reports for the treatment of AD. Compounds were searched by literatures and systematic separation from T. sinensis. The molecular docking experiment was carried out by using Autodock Vina software to screen the bioactive compounds in T. sinensis and target proteins for AD. Then, the “compound-target network” was constructed by Cytoscape software. The drug-like properties of the active compounds were analyzed by pKCSM performs, and the protein-protein interaction (PPI) network was constructed by Search Tool for the Retrieval of Interacting Genes/Proteins (STRING). The Kyoto Encyclopedia of Genes and Genomes (KEGG) target pathway enrichment analysis was carried out by Database for Annotation, Visualization and Integrated Discovery (DAVID). Furthermore, the protective effect of neurons of two active compounds were verified with the injury cell model of PC12 and primary hippocampus neurons induced by Aβ25-35. Finally, the key proteins of related pathways were quantitatively analyzed with Western blot method. ResultsIn total, 105 compounds and 38 targets have been screened. The main active compounds contained berberine, which belongs to alkaloids, Aurantiamide acetate, N–P-coumaroyltyramine, which belongs to amides, Trans-syringin and 3-demethyl-phillyrin, which belongs to phenylpropanoids. The targets covered inflammation-related proteins, including Protein kinase B (AKT), Phosphoinositide 3-kinase (PI3K), Tyrosine-protein kinase JAK1 (JAK1), mammalian target of rapamycin (mTOR), tumor necrosis factor alpha (TNF-α), Neuronal NOS (NOS1), and cholinergic function-related proteins, including α4-Nicotinic acetylcholine receptor (α4 nAChR), Muscarinic acetylcholine receptor M1 (Muscarnic M1). Inflammation and cholinergic dysfunction were the center of the network and occupy a dominant position. And the results of enrichment analysis shown the pathways mainly contained phosphoinositide-3-kinase/Akt (PI3K/Akt) signal pathway, neurotrophic factors (NTFs) signal pathway, Hypoxia-inducible factor 1 (HIF-1) signal pathway, mechanistic Target of Rapamycin (mTOR) signal pathway, Tumor necrosis factor (TNF) signal pathway, insulin resistance (IR). The results of in vitro assays showed that the tested compounds could significantly improve the survival rate and inhibit the apoptosis of PC12 cells and primary hippocampal neurons injured by Aβ25-35. Western blot results showed that T. sinensis had a significant effect on the expression of protein PI3K and Akt. Conclusion: Our results revealed that T. sinensis could prevent and treat AD through a multi-compound-multi-target-multi-pathway regulatory network. Our work also expected to provide new ideas and theoretical bases for searching for the active compounds in T. sinensis and potential mechanism in the prevention and treatment of AD by the network pharmacology and molecular docking. The results of in vitro assay and in vivo assay supported the results of molecular docking.

Uncovering the mechanism of the effects of Paeoniae Radix Alba on iron-deficiency anaemia through a network pharmacology-based strategy

BackgroundPaeoniae Radix Alba, the root of the plant Paeonia lactiflora Pall, is a common blood-enriching drug in traditional Chinese medicine. Its effectiveness in the clinical treatment of anaemia is remarkable, but its potential pharmacologic mechanism has not been clarified.MethodsIn this study, the potential pharmacologic mechanism of Paeoniae Radix Alba in the treatment of iron-deficiency anaemia was preliminarily elucidated through systematic and comprehensive network pharmacology.ResultsSpecifically, we obtained 15 candidate active ingredients from among 146 chemical components in Paeoniae Radix Alba. The ingredients were predicted to target 77 genes associated with iron-deficiency anaemia. In-depth analyses of these targets revealed that they were mostly associated with energy metabolism, cell proliferation, and stress responses, suggesting that Paeoniae Radix Alba helps alleviate iron-deficiency anaemia by affecting these processes. In addition, we conducted a core target analysis and a cluster analysis of protein-protein interaction (PPI) networks. The results showed that four pathways, the p53 signalling pathway, the IL-17 signalling pathway, the TNF signalling pathway and the AGE-RAGE signalling pathway in diabetic complications, may be major pathways associated with the ameliorative effects of Paeoniae Radix Alba on iron-deficiency anaemia. Moreover, molecular docking verified the credibility of the network for molecular target prediction.ConclusionsOverall, this study predicted the functional ingredients in Paeoniae Radix Alba and their targets and uncovered the mechanism of action of this drug, providing new insights for advanced research on Paeoniae Radix Alba and other traditional Chinese medicines.

A network pharmacology-based strategy for predicting anti-inflammatory targets of ephedra in treating asthma

Asthma, the most common chronic respiratory disease in the world, is involved in a sustained inflammatory response caused by a variety of immune cells. Ephedra with multi-target, multi-pathway functions is an effective treatment for asthma. However, the ingredients and anti-inflammatory targets of ephedra in treating asthma are unclear. Therefore, there is a need for further research. Ephedra-related and anti-inflammatory targets were found and then combined to get intersection, which represented potential anti-inflammatory targets of ephedra. Moreover, compound-anti-inflammatory target and asthma-target protein-protein interaction network were merged to get the protein-protein interaction network intersection and core genes in asthma-target protein-protein interaction network. For the anti-inflammatory targets of ephedra in treating asthma, Gene Ontology and pathway analysis were executed to confirm gene functions of ephedra in antagonizing inflammation of asthma. Finally, molecular docking, qRT-PCR, WB and ELISA were performed to assess the binding activities between the compounds and anti-inflammatory targets of ephedra in treating asthma. Critical compounds and anti-inflammatory targets of ephedra in treating asthma were identified, including quercetin, luteolin, kempferol, naringenin, beta-sitosterol, SELE, IL-2 and CXCL10. The biological processes of anti-inflammatory targets of ephedra in treating asthma were involved in immune response, inflammatory response, cell-cell signaling and response to lipopolysaccharide. Moreover, 22 pathways were obtained and we proved that critical compounds inhabited the expression of SELE, IL-2 and CXCL10 at mRNA and protein levels.

Erratum: A Network Pharmacology-Based Strategy for Predicting Active Ingredients and Potential Targets of LiuWei DiHuang Pill in Treating Type 2 Diabetes Mellitus [Corrigendum

[This corrects the article DOI: 10.2147/DDDT.S216644.].

Network Pharmacology-Based Strategy to Investigate the Pharmacologic Mechanisms of Atractylodes macrocephala Koidz. for the Treatment of Chronic Gastritis.

Chronic gastritis (CG) is an inflammatory disease. Atractylodes macrocephala Koidz (AMK) is employed in traditional Chinese medicine (TCM) to treat various disorders. AMK can be efficacious against CG, but the active ingredients, drug targets, and its exact molecular mechanism are not known. We employed network pharmacology to analyze the active ingredients, drug targets, and key pathways of AMK in CG treatment. Seventy-seven AMK candidate ingredients were selected from four databases, and 27 active ingredients were selected for CG treatment. Twenty-five overlapping gene symbols related to CG and drugs were obtained from GeneCards and OMIM databases. A protein–protein interaction (PPI) network and TCM comprehensive network (Drug–Ingredients–Gene symbols–Disease network) were constructed, and 528 Gene Ontology (GO) terms and 26 pathways were obtained by analyses of enrichment of GO pathways and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. We suggest that the interleukin-17 signaling pathway, C-type lectin receptor signaling pathway, tumor necrosis factor signaling pathway, and AGE-RAGE signaling pathway in diabetic complications might serve as the key points and principal pathways for CG treatment. We also evaluated the reliability of some important active ingredients and targets by in vitro experiments. We showed that AMK probably influences the inflammatory response, amino acid synthesis, and energy metabolism when treating CG. This study provides novel insights for researchers to explore the mechanism of action of TCM systematically.

Uncovering the Pharmacological Mechanism of Stemazole in the Treatment of Neurodegenerative Diseases Based on a Network Pharmacology Approach.

Stemazole exerts potent pharmacological effects against neurodegenerative diseases and protective effects in stem cells. However, on the basis of the current understanding, the molecular mechanisms underlying the effects of stemazole in the treatment of Alzheimer’s disease and Parkinson’s disease have not been fully elucidated. In this study, a network pharmacology-based strategy integrating target prediction, network construction, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, and molecular docking was adopted to predict the targets of stemazole relevant to the treatment of neurodegenerative diseases and to further explore the involved pharmacological mechanisms. The majority of the predicted targets were highly involved in the mitogen-activated protein kinase (MAPK) signaling pathway. RAC-alpha serine/threonine-protein kinase (AKT1), caspase-3 (CASP3), caspase-8 (CASP8), mitogen-activated protein kinase 8 (MAPK8), and mitogen-activated protein kinase 14 (MAPK14) are the core targets regulated by stemazole and play a central role in its anti-apoptosis effects. This work provides a scientific basis for further elucidating the mechanism underlying the effects of stemazole in the treatment of neurodegenerative diseases.

Network Pharmacology-Based Strategy to Investigate Pharmacological Mechanisms of Qiaoshao Formula for Treatment of Premature Ejaculation.

Background Qiaoshao (QS) formula, a traditional Chinese medicine (TCM) comprising seven herbs, has been clinically proven to have a favorable treatment effect on premature ejaculation (PE). However, its underlying pharmacological mechanisms in the treatment of PE need to be further clarified. Methods In the present study, a network pharmacology-based strategy was adopted. The active compounds of QS formula were obtained from the Chinese medicine database, and the potential targets of these compounds were collected from the DrugBank database to construct compound-compound targets network. PE-related targets were identified from human disease databases and used to construct the protein-protein interaction (PPI) networks. Compound-disease target PPI network was constructed by merging the PPI network of disease-targets and compound-targets. Cluster and enrichment analyses were performed on the PPI network of disease targets and compound-disease targets. The influence of QS formula on serum 5-HT, NO, oxytocin, and thyroid hormones of PE patients was verified. Results Four primary pharmacological networks of QS formula were constructed, including the compound-compound targets network, PPI network of PE-related targets and compound-disease targets, and the QS-PE mechanism network. The module and pathway enrichment analyses revealed that the QS formula had the potential to affect varieties of biological process and pathways, such as nitric oxide biosynthetic process, oxytocin, thyroid hormone, TNF, PI3K-Akt, and the HIF-1 signaling pathway, that play an important role in the pathogenesis of PE. Meanwhile, the QS formula has been clinically confirmed to regulate the serum level of 5-HT, NO, oxytocin, and TT in PE patients. Conclusion This study preliminarily discovered the potential targets and pathways of QS formula in the treatment of PE, which laid a good foundation for further experimental research.

Deciphering the Key Pharmacological Pathways and Targets of Yisui Qinghuang Powder That Acts on Myelodysplastic Syndromes Using a Network Pharmacology-Based Strategy.

Background Yisui Qinghuang powder (YSQHP) is an effective traditional Chinese medicinal formulation used for the treatment of myelodysplastic syndromes (MDS). However, its pharmacological mechanism of action is unclear. Materials and Methods In this study, the active compounds of YSQHP were screened using the traditional Chinese medicine systems pharmacology (TCMSP) and HerDing databases, and the putative target genes of YSQHP were predicted using the STITCH and DrugBank databases. Then, we further screened the correlative biotargets of YSQHP and MDS. Finally, the compound-target-disease (C-T-D) network was conducted using Cytoscape, while GO and KEGG analyses were conducted using R software. Furthermore, DDI-CPI, a web molecular docking analysis tool, was used to verify potential targets and pathways. Finally, binding site analysis was performed to identify core targets using MOE software. Results Our results identified 19 active compounds and 273 putative target genes of YSQHP. The findings of the C-T-D network revealed that Rb1, CASP3, BCL2, and MAPK3 showed the most number of interactions, whereas indirubin, tryptanthrin, G-Rg1, G-Rb1, and G-Rh2 showed the most number of potential targets. The GO analysis showed that 17 proteins were related with STPK activity, PUP ligase binding, and kinase regulator activity. The KEGG analysis showed that PI3K/AKT, apoptosis, and the p53 pathways were the main pathways involved. DDI-CPI identified the top 25 proteins related with PI3K/AKT, apoptosis, and the p53 pathways. CASP8, GSK3B, PRKCA, and VEGFR2 were identified as the correlative biotargets of DDI-CPI and PPI, and their binding sites were found to be indirubin, G-Rh2, and G-Rf. Conclusion Taken together, our results revealed that YSQHP likely exerts its antitumor effects by binding to CASP8, GSK3B, PRKCA, and VEGFR2 and by regulating the apoptosis, p53, and PI3K/AKT pathways.

Network Pharmacology‐Based Strategy for Predicting Active Ingredients and Potential Targets of Gegen Qinlian Decoction for Rotavirus Enteritis

Materials and Methods In this study, a network pharmacology-based strategy was used to elucidate the mechanism of GGQLD for the treatment of RVE. Oral bioavailability and drug-likeness were taken as the judgment criteria to search the active ingredients of GGQLD in traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP). The affinity between protein and ingredients was further determined using the similarity ensemble approach to find the corresponding targets. According to the genes related to enteritis in GeneCards database, the key targets were screened by intersections between drug and disease targets. And the therapeutic mechanism was predicted using the protein-protein interactions (PPIs), the Gene Ontology (GO), and the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, which was verified by detecting calcium ion concentration with the fluorescent probe. Result 130 active ingredients were screened from GGQLD, including (R)-canadine, moupinamide, formononetin, and other flavonoids. They act on a total of 366 targets, which is mainly distributed in the biological process of hormone binding or signaling pathways of neuroactive ligand receptor interaction, serotonergic synapse, and calcium signaling pathway. Furthermore, serotonin receptors, adrenergic receptors, cholinergic receptors, and dopamine receptors in the enteric nervous system may be the key targets of RVE treatment by GGQLD. Conclusion This study demonstrated that the potential mechanism that GGQLD can effectively improve the symptoms of RVE may depend on the regulation of calcium ions, serotonin, and gastrointestinal hormone ion that could mutually affect the intestinal nervous system.

Network Pharmacology-Based Strategy for Predicting Therapy Targets of Traditional Chinese Medicine Xihuang Pill on Liver Cancer.

Objective To investigate the potential therapy targets and pharmacological mechanism of traditional Chinese medicine (TCM) Xihuang pill in liver cancer based on network pharmacology. Methods Drug ingredients-target network was constructed based on the target sets of Xihuang pill and liver cancer. The overlapping genes between Xihuang pill targets and liver cancer-related molecular targets were investigated using comparative analysis. Moreover, the PPI network and module was constructed based on overlapping genes and hub nodes, respectively, followed by the pathway enrichment analysis. Results A drug ingredients-target network was established with 1184 nodes and 11035 interactions. Moreover, a total of 106 overlapping genes were revealed between drug targets and liver cancer molecular targets. Furthermore, a PPI network and 4 modules were further investigated based on overlapping genes, respectively. These hub nodes such as VEGFA and EGFR were mainly enriched in GO functions including positive regulation of MAP kinase activity, activation of protein kinase activity, regulation of MAP kinase activity, and pathways like proteoglycans in cancer, bladder cancer, and estrogen signaling. Conclusion VEGFA and EGFR might be potential therapy targets of Xihuang pill in liver cancer. Furthermore, the effect of Xihuang pill on liver cancer might be realized by targeting VEGFA and EGFR in pathways like proteoglycans in cancer and estrogen signaling.

A Comprehensive Network Pharmacology-Based Strategy to Investigate Multiple Mechanisms of HeChan Tablet on Lung Cancer.

Background HeChan tablet (HCT) is a traditional Chinese medicine preparation extensively prescribed to treat lung cancer in China. However, the pharmacological mechanisms of HCT on lung cancer remain to be elucidated. Methods A comprehensive network pharmacology-based strategy was conducted to explore underlying mechanisms of HCT on lung cancer. Putative targets and compounds of HCT were retrieved from TCMSP and BATMAN-TCM databases; related genes of lung cancer were retrieved from OMIM and DisGeNET databases; known therapeutic target genes of lung cancer were retrieved from TTD and DrugBank databases; PPI networks among target genes were constructed to filter hub genes by STRING. Furthermore, the pathway and GO enrichment analysis of hub genes was performed by clusterProfiler, and the clinical significance of hub genes was identified by The Cancer Genome Atlas. Result A total of 206 compounds and 2,433 target genes of HCT were obtained. 5,317 related genes of lung cancer and 77 known therapeutic target genes of lung cancer were identified. 507 unique target genes were identified among HCT-related genes of lung cancer and 34 unique target genes were identified among HCT-known therapeutic target genes of lung cancer. By PPI networks, 11 target genes AKT1, TP53, MAPK8, JUN, EGFR, TNF, INS, IL-6, MYC, VEGFA, and MAPK1 were identified as major hub genes. IL-6, JUN, EGFR, and MYC were shown to associate with the survival of lung cancer patients. Five compounds of HCT， quercetin, luteolin, kaempferol, beta-sitosterol, and baicalein were recognized as key compounds of HCT on lung cancer. The gene enrichment analysis implied that HCT probably benefitted patients with lung cancer by modulating the MAPK and PI3K-Akt pathways. Conclusion This study predicted pharmacological and molecular mechanisms of HCT against lung cancer and could pave the way for further experimental research and clinical application of HCT.