To explore the mechanism of action of the yin nourishing and heat clearing prescription in treating cough variant asthma (CVA) based on network pharmacology (NP).  The active ingredients and targets of the yin nourishing and heat clearing prescription were screened using the Traditional Chinese Medicine System Pharmacology Analysis Platform (TCMSP); CVA targets were screened by the GeneCards, NCBI gene, and OMIM databases to construct the component-target network and the protein-protein interaction (PPI) network. GO functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the target genes were performed to construct the component-disease-pathway-target biological network. Moreover, CVA-related core target structures with high values were subjected to molecular docking (MD) with the active components.  We found 265 eligible targets in the prescription and 1115 CVA-related genes. The medicine targets were intersected with disease targets, which yielded 148 common targets. After topology analysis, 66 key targets were screened. Upon GO functional annotation, 2408 biological processes, 153 molecular functions, and 162 KEGG pathways were enriched. Molecular docking results suggested that the major active ingredients of the prescription showed high affinity to the key targets, among which AKT1 might be the most important target.  Active ingredients might act on AKT1, IL-6, VEGFA, IL-1B, and JUN to suppress eosinophil accumulation, decrease histamine release, suppress airway inflammation, regulate the airway immune microenvironment, increase autophagy in lung tissue, inhibit mucus production, and reduce airway resistance and hyperresponsiveness, thus treating CVA. Our findings provide a reference for further research and clinical applications of the prescription. Cough variant asthma (CVA) is a special type of asthma with repeated chronic persistent dry cough as the sole or major clinical manifestation. The symptom usually lasts for 8 weeks or longer, and it is closely related to classic asthma (CV). Generally, CVA is the precursor of CV, and about 35.7% of CVA cases will develop into CV within 5 years , severelThe active ingredients (compounds) and targets of medicines contained in the yin nourishing and heat clearing prescription , the targets of CVA, and the molecular mechanism underlying the effects of the yin nourishing and heat clearing prescription in treating CVA were studied.The components of the yin nourishing and heat clearing prescription were searched against the TCMSP database to predict the targets. In addition, the GeneCards, NCBI gene, and OMIM databases were searched to screen CVA targets. A Venn diagram was generated to obtain the targets of the yin nourishing and heat clearing prescription in treating CVA. Thereafter, the protein-protein interaction (PPI) network of common targets between the prescription and CVA was constructed based on the String database, and the constructed PPI network was analyzed with related parameters. Afterward, topology analysis was conducted with the NetworkAnalyzer tool to screen the core targets of the yin nourishing and heat clearing prescription in treating CVA. A compound-disease-target regulatory network was constructed using Cytoscape 3.8.0. The core targets were selected to conduct Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses to construct the component-disease-pathway-target network .https://tcmspw.com/tcmsp.php) using the terms “Beishashen,” “Lugen,” “Huangqin,” “Lianqiao,” “Qianhu,” and “Xingren,” with oral bioavailability ≥ 30% and drug likeness ≥ 0.18 as the criteria. Then, the targets were corrected based on the UniProt database (https://www.uniprot.org/) [Homo sapiens,” and the targets were converted to corresponding genes.Eligible candidate compounds and corresponding targets were screened against the TCMSP database  (https:/ot.org/) , where thttps://www.genecards.org/), the NCBI gene database [https://www.ncbi.nlm.nih.gov/), and the OMIM database [https://www.omim.org/), using the keyword “cough variant asthma.” Targets obtained from the GeneCards database were screened by the median score, so as to obtain the more relevant targets.Human genes were retrieved from the GeneCards database  , where the research species was restricted to “Homo sapiens,” the minimum interaction score was set to the median confidence (0.400), and the remaining parameters were set at default values for the construction of the PPI network.The common drug-disease targets were imported into the String database  , molecular function (MF), and cell component (CC) categories. The terms with The component-disease-pathway-target network file was imported into Cytoscape 3.8.0 to plot the pathway network diagram, so as to more intuitively exhibit the “multicomponent and multitarget” characteristics of the TCM active ingredients in treating CVA.http://pubchem.ncbi.nlm.nih.gov/). Later, the corresponding 3D structures of active ingredients were downloaded from the RCSB PDB database (http://www.rcsb.org/). Next, the ligands and proteins needed for MD were prepared using AutoDock Vina software (http://vina.scripps.edu/). For target proteins, their crystal structures were preprocessed to satisfy the low-energy conformation of the ligand structure. Finally, these five key target structures were molecularly docked with the five active ingredient structures. The affinity  value represents the binding capacity between the two, with a lower value indicating more stable binding. The top five docking results with the lowest binding energy were selected for plotting. At last, Pymol software was utilized to analyze the docking results.Five key targets were screened, and then, the compound names, molecular weights, and 2D structures of five active ingredients were determined based on the PubChem database , 153 MFs, and 82 CCs were enriched. These GO terms were sorted according to the P value. The top 10 terms from each category were screened as key functional annotations, and the bubble chart was plotted, as shown in P value . The main enriched BPs included response to molecule of bacterial origin, response to metal ion, cellular response to chemical stress, response to oxidative stress, response to drug, cellular response to oxidative stress, reactive oxygen species (ROS) metabolic process, response to ROS, and epithelial cell proliferation. The main enriched CCs were membrane raft, membrane microdomain, membrane region, caveola, plasma membrane raft, vesicle lumen, cytoplasmic vesicle lumen, secretory granule lumen, and apical part of cells. The main enriched MFs were cytokine receptor binding, signaling receptor activator activity, nuclear receptor activity, ligand-activated, transcription factor activity, receptor ligand activity, and DNA-binding transcription factor binding.The targets were subject to GO functional analysis based on the DAVID database. It was found that among the 148 common targets between the yin nourishing and heat clearing prescription and CVA, 2408 BPs (P < 0.05). The top 20 pathways were selected, as shown in P value. Pathways not related to CVA such as the AGE-RAGE signaling pathway in diabetic complications were excluded. Finally, three pathways were identified, including the PI3K-AKT signaling pathway, the IL-17 signaling pathway, and the TNF signaling pathway. This suggests that the effects of the yin nourishing and heat clearing prescription on CVA are mediated by the above pathways, among which the PI3K-AKT signaling pathway has the most significant effect.The drug-disease common targets were subjected to KEGG pathway enrichment analysis. It was found that 148 intersected target genes were significantly enriched in 162 signaling pathways , inhibit excessive production of mucus by goblet cells in lung tissues, improve airway stenosis, and alleviate airway resistance [κB translocation [In this study, the TCMSP database was utilized to screen the major active ingredients of the yin nourishing and heat clearing prescription with high degree values, including quercetin, luteolin, kaempferol, and tanshinone IIa. Of these, the flavonoid compound quercetin has anti-inflammation and antiallergy effects, which can prevent allergen- and platelet activation factor- (PAF-) induced airway obstruction and hyperresponsiveness . In addidiseases . Luteolidiseases , 30. Lutsistance . Moreovesistance . In addisistance . Tanshinlocation . Furtherlocation . To sum κB and promote the Th2 cell predominant response to aggravate the inflammatory response and stimulate airway smooth muscle cell proliferation as well as excessive mucus secretion [δ, can promote airway remodeling via the PI3K-AKT signaling pathway [κB and mTOR [Many previous studies have suggested that the PI3K-AKT signaling pathway participates in multiple key steps regulating airway inflammation, excessive mucus secretion, airway epithelial autophagy, and airway remodeling, leading to CVA. For instance, blocking the PI3K-AKT signaling pathway decreases the infiltration of eosinophils, neutrophils, and lymphocytes in lung tissues, thus suppressing airway inflammation and excessive mucus secretion , 37. ROSecretion . The Lynecretion . mTOR, aecretion , which cecretion . AKT kinecretion . Besidesecretion . One stu pathway . In thisand mTOR , which cand mTOR . Therefo


The results noted that three components could inhibit proinflammatory related hub genes but had no effect on survival-related hub genes. Thus, the three effective hub components and corresponding hub genes may play essential roles in the treatment of YHPGKL on pneumonia.Yinhua pinggan granule (YHPGKL), a traditional Chinese medical compound, could treat pneumonia. Although previous studies demonstrated the protective and therapeutic effects of YHPGKL on pneumonia, its potential molecular mechanisms and its effective components are still elusive. Herein, we performed a network pharmacology analysis to determine the possible signaling pathways involved in the protective effects of components of YHPGKL. A total of 119 components and 257 target proteins of YHPGKL were identified, among which 117 effective components interacted with 113 proteins related to pneumonia. Then, a compound-effective component-target protein network was established to screen the effective hub components. The top three effective components, namely luteolin, kaempferol, and quercetin, were selected. Moreover, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of 113 proteins revealed a significant enrichment term associated with host immune and anti-infectious responses. Furthermore, by constructing a protein-protein interaction network between common proteins, ten hub proteins were identified, among which three hub components hit eight proteins. A further molecular docking analysis confirmed that the three effective hub components had a good affinity with six hub proteins. Eventually, the interactions were further visualized and screened on account of an infectious macrophage model  According to the Global Burden of Disease report, respiratory infections are second threatened to human death. Pneumonia, the most common respiratory disorder, causes extremely high morbidity and mortality, particularly in young children (<5 years old) and older people (>65 years old) , 2. PathSo far, antibacterial, antiviral, antipyretic, antihistamine, and supportive therapies are beneficial to pneumonia treatments . HoweverκB), in vivo and in vitro [Traditional Chinese Medicine (TCM) has been used for thousands of years thanks to its good efficacy, few side effects, and special characteristics . TCM comin vitro , 21, 22.in vitro . Althougin vitro and in vivo due to the high cost and work overload. Therefore, this study investigates the relationships between effective components of YHPGKL and target proteins related to pneumonia through network pharmacology analysis. By means of database collection, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, protein-protein interaction network (PPI) establishment, molecular docking experiment, and in vitro study, we extracted some hub components from YHPGKL. We found some critical proteins related to pneumonia, which may be potential targets for the treatment of YHPGKL.The network pharmacology provides a practical approach that can transfer one target, one drug analysis of TCM to the multitargets, multicomponents analysis, accelerating the scientific application of TCM . Since tSince both oral bioavailability (OB) and drug-likeness (DL) are the critical factors in regulating drugs absorption in the body, we screened out all components of YHPGKL using the Traditional Chinese Medicine System Pharmacology  by imputing the keywords “jinyinhua,” “gegen,” “huzhang,” “mahuang,” “xingren,” and “gancao,” separately . The TCMSince the potential therapeutic symptoms of YHPGKL focus on various pathological factors induced inflammation of lung, we thought pneumonia was able to cover up the most of above-mentioned symptoms and related pathomechanisms to help us find out more universal therapeutic targets. Proteins related to pneumonia were collected from the Gene Cards database  and OMIMHomo sapiens” [After screening out cotarget proteins between active components and pneumonia, we analyzed their relationships using the STRING database. The STRING is a popular database of known and predicted protein-protein interactions. The interaction contains direct  and indirect  associations; they come from computational prediction, knowledge transfer amid organisms, and interactions aggregated from other databases. In this study, the STRING database analyzed the potential targeted proteins, with settings of a confidence score ≥ of 0.4 and the Organism of “sapiens” .Based on PPI analysis, we made an MCODE analysis, clustering a given network based on the topology to find densely connected regions, to extract similar nodes and protein complexes to perform clusters using the Metascape database with settings of physical core , Min Network Size:3, Max Network Size:500 . The MetWe kicked out active components that did not target pneumonia-related proteins according to previous prediction and screening results. Then, the data were imputed into the Cytoscape 3.7.1 software (Cytoscape) for network construction . The CytTo screen out hub protein, based on the PPI analysis, we imputed PPI results into Cytoscape and rebuilt a new PPI network which visualized in line with degrees (the size and brightness of protein) and edges (the size and brightness of rope). Then, we picked up hub proteins according to the degrees of betweenness centrality and closeness centrality.P < 0.05).GO annotation is used to define the functions of genes based on biological process (BP), cell components (CC), and molecular functions (MF). KEGG is a database that integrates genome, chemistry, and system function information. Therefore, the acquired target proteins for pneumonia were imputed into Metascape to get GO and KEGG functional enrichment analysis  in the presence or absence of 1 μg/mL Phosphate polysaccharide  for 24 h, respectively. Then, the THP-1 cells were challenged with 100 ng/mL phorbol 12-myristate 13-acetate  for 48 h to differentiate into macrophages.THP-1 cells, after stimulation into THP-1-derived macrophages (referred to as macrophages), were selected for assay due to their similarity to human primary macrophages . Cells wμl CCK-8 solution  was supplemented and incubated for another 2 h, followed by a microplate reader measurement  at a wavelength of 450 nm.To assess the cytotoxicity of luteolin, kaempferol, or quercetin, macrophages were seeded into 96-well plates along with luteolin, kaempferol, or quercetin at different concentrations for 24 h, respectively. Then, 10 Total RNA was isolated using the TRIzol reagent , and cDNA was synthesized with ReverTra Ace qPCR RT kit  according to the manufacturer's instructions, respectively. The RT-qPCR assay was performed with SYBR Green Real-Time PCR Master Mix . The target primer sequences are as follows:IL6: 5′-CCACTCACCTCTTCAGAAC-3′, 3′-CTTTGCTGCTTTCACACAT-5′.TNF: 5′-GTGATCGGCCCCCAGAGGGA-3′, 3′-CACGCCATTGGCCAGGAGGG-5′. AKT1: 5′-CTCCTGAGGAGCGGGAGGAGTGG-3′,3′-GTCCACTCCTCCCGCTCCTC A GGA-5′.MMP9: 5′-TTCTCCAGAAGCAACTGTCC-3′, 3′-TAGGTG ATGTTGTGG T G GTG-5′. GAPDH: 5′-GGAGAAGGCTGGGGCTCAT-3′, 3′ TGATGGCATGGACT G TG GTC-5′. CAPASE3:5′-GCAGCAAACCTCAGGGAAAC-3′, 3′-TGTCGGCATA CTGT T TCAG C A-5′.t-test or one-way analysis of variance (ANOVA) by SPSS software. P value <0.05 was seen as significant differences.Data are visualized as the mean ± standard deviation (SD), and statistical analysis was performed using the student's According to the standard of OB >30% and DL >0.18, which has been performed by other studies , 37, 119Due to pneumonia's complex mechanisms and bioprocesses, we screened GenCards (score> 3) and the OMIN database on account of similar studies and obtained 1423 pneumonia-related targets , 38. TheBased on the above results, we set up a network to visualize the interactions of 6 herbs, effective components, and target proteins by Cytoscape . The degP value. In addition, the biological process (BP), cellular components (CC), and Molecular function (MF) were analyzed, and the top 20 terms were performed, respectively  6, tumor necrosis factor (TNF) -α, etc., expression [in vitro experiment suggested interacting with IL6, MMP-9, Caspase-3, and TNF, consistent with the previous report. Of note, the docking analysis demonstrated that a structural core interaction between compound and critical protein, which deserve to further study with such as increase binding activity by chemical modification, etc.The OB value and DL were set as a standard in the TCMSP database to ensure that those components functioned in vivo . We screpression . In addipression . Our stuin vivo and in vitro [κB pathway activity and inhibited the expression of proinflammatory cytokines in the lung tissue of LPS induced ALI mice model [Growing evidence has proved that kaempferol has an excellent protective ability against inflammation and apoptosis in vitro , 45. Mecce model . Du et ace model . Followice model . Our resKEGG and GO analysis reveal these common targets distribution in all signaling pathways, biological processes, cellular components, and molecular function. In our studies, the top ranks of signaling pathway are involved in immune-related signaling pathways, such as the TNF pathway, IL-17pathway, Toll-like pathway, and MAPK pathway. Besides, the top ranks of biological process are response to exogenous invasion, oxidative stress, and cell injury, like molecular of bacterial origin, oxidative stress and wounding, etc. Furthermore, the top ranks of molecular function focus on inflammatory response . Also, the top ranks of cellular component revealed cell mobilization and stress such as membrane raft, early endosome and focal adhesion, etc. In terms of KEGG and GO results, these effective components of YHPGKL are obviously interacted with pneumonia through regulating inflammation and wounding.Further study, the top three effective components from YHPGKL were picked up and also tightly related with inflammatory genes Figures –6. AccorIn fact, it has been reported that TNF signaling pathway serves a vital role in a broad spectrum of diseases . TNF is in vivo, resulting in variable active components, hardly predicting actual effective components and contents. Therefore, we performed in vitro experiment to confirm the above results. The discrepancy between network pharmacology and in vitro was acceptable due to virtual and real-world research. In addition, although the top three compounds we screened out play important roles in the treatment of pneumonia, according to our studies, they either interacted with common targets or different targets, suggesting a possible combination  and is worth to finding an appropriate matching in the future.In a nut word, the network pharmacology help us analyze possible effective components of YHPGKL, illuminate the potential mechanisms of compounds, improve compounds, and extract valuable components from YHPGKL, all of which could promote experimental processes in real-world experiments. However, it is worth noting that the herb compound showed extremely complex metabolism in vitro. We screened out three hub-effective components and six critical proteins, possibly playing pivotal roles in protecting against lung injury. Importantly, our results implied that the TNF signaling pathway might be a potential mechanism by which YHPGKL treats pneumonia, which will be confirmed.In this research, we systemically analyzed the potential effective components and target proteins of YHPGKL in the treatment of pneumonia through network pharmacology, molecular docking analysis, and


Tripterygium wilfordii (TW), as a traditional Chinese medicine (TCM), has been widely used in anti-inflammation, anticancer, and other fields. However, the potential of TW in treating PAH is currently unclear.  Pulmonary artery hypertension (PAH) is a rare, life-limiting cardiopulmonary disorder characterized by the progressive and remodeling of pulmonary vasculature. Although the development of the technology brings us many approaches for the treatment of PAH, the effect of treatment is unsatisfactory. via molecular docking technology and surface plasmon resonance (SPR) experiments.  Active ingredients and their corresponding genes were harvested from the Traditional Chinese Medicine Database and Analysis Platform (TCMSP), CTD, and STITCH. Meanwhile, genes associated with PAH were adopted from OMIM and GeneCards databases. Through Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analyses, potential targeting KEGG pathways and functions were further collected. Then, STRING was used to generate the protein-protein interaction (PPI) network. The “ingredients-targets-pathway” network was built by Cystoscope. Finally, the binding between active ingredients of TW and corresponding targets of PAH was identified  The network pharmacology analysis revealed 36 active ingredients in TW and 150 potential targets related to the treatment of PAH with TW. Moreover, GO enrichment analysis showed that the key function in molecular function (MF) was related to enzyme binding, the key function in biological process (BP) was related to cellular response to organic substance, and the key function in cellular component (CC) was related to KEGG enrichment analysis and found that it was closely related to the IL-17 signaling pathway, TNF signaling pathway, Toll-like receptor signaling pathway, and apoptosis. At last, molecular docking results revealed that the main active ingredients of TW had a strong binding ability with the PAH target protein. In addition, the SPR experiment revealed that kaempferol was combined with the CASP3 protein rather than PARP1, while triptolide was combined with PARP1 rather than the CASP3 protein. Tripterygium wilfordii in the treatment of PAH. TW may have therapeutic effects on PAH through multitargets and multimethods, which provide a scientific basis for further elaborating the mechanism of  Pulmonary artery hypertension (PAH) is a common chronic disease in clinical practice, which is the main category of pH classification in the Second World Symposium , 2. AlthTripterygium wilfordii, a traditional Chinese herbal medicine, has been widely used in various diseases, such as rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), and psoriasis [soriasis . Its comNetwork pharmacology, a novel concept proposed by British pharmacologist Hopkins, systematically revealed the mechanisms by which drugs act on a disease . By consTripterygium w ilfordii  experiment verification methods to provide new ideas for the treatment of PAH by ilfordii .https://tcmspw.com/tcmsp.php), which is an analysis platform that represents ideal information convergence of pharmacochemistry, absorption, distribution, metabolism, and excretion (ADME) properties, drug-likeness, drug targets, associated diseases, and interaction networks [Homo sapiens.” The bioactive components were obtained by the metrics of oral bioavailability (OB) > 30%, drug-likeness (DL) > 0.18, and Caco-2 > 0.The bioactive ingredients of TW are filtered from Traditional Chinese Medicine Systems Pharmacology (TCMSP) (networks . The spehttps://ctdbase.org/) and STITCH (https://stitch.embl.de/) are widely used to collect the corresponding genes of TW. CTD is a public database, which provides relations of gene products, diseases, and chemical and environmental exposures [Homo sapiens were limited. We used the screened genes to conduct further analysis.CTD (xposures . STITCH xposures . Organishttps://www.genecards.org/) and the OMIM database (https://www.omim.org/). OMIM is a sophisticated, authoritative, and timely research resource that provides an elaborate description of human genes, phenotypes, and their relationships [Homo sapiens”. The keyword “pulmonary artery hypertension” was inputted into the search for the target genes of PAH from the two databases.Potential targets of PAH were obtained from GeneCards . Overlapping genes between TW and PAH were identified as candidate genes.p value <0.05 were regarded as enriched. Only those GO categories or KEGG pathways contained ≥5 DEGs were kept for further analysis.The Gene Ontology (GO) category database and the KEGG database are used for functional annotation of candidate genes. Enrichment analysis of GO categories, composed of cellular components (CC), biological process (BP), and molecular function (MF), was performed by the R cluster Profiler (v3.14.3) package, and KEGG enrichment analysis of pathways was tested upon hypergeometric distribution by R “phyper” function. Those GO categories with a false discovery rate (FDR) <0.05 were considered as significantly enriched. However, KEGG pathways with a https://string-db.org) with the species limited to Homo sapiens and the highest confidence >0.9. The STRING database is to collect and merge bioinformation by integrating known and predicted the relations of protein-protein for organisms [The hub proteins were inputted into STRING . The chemical structures of kaempferol and triptolide were retrieved from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/). The molecular docking studies between proteins and compounds were based on these obtained structures and carried out with the AutoDock Package (version 4.2). The AutoDock suite provides a comprehensive toolset for computational ligand docking and drug design and development, including empirical free energy force fields, docking engines, methods for site prediction, and interactive tools for visualization and analysis [via the AutoGrid program. Conformation searching and energy evaluation were completed with the AutoDock program. AMBER Tools (version 14) was performed to dock the active ingredients with protein receptor molecules, and AMBER Tools MM/PBSA was used to visualize the affinities of active ingredients and targets. Briefly, the optimal complex was placed in a cubic water box with a minimum distance of 10 Å between protein surface and the box edges. Proper sodium was added to achieve physiological salt conditions with overall neutrality. Energy minimization was performed under the force field. The constraint of all bonds involving hydrogen atoms was achieved with the SHAKE method. Average structures were extracted for interaction mode analysis.The crystal structures of CASP3 (PBD ID: ICP3) and PARP1 (PBD ID: IUKO) were obtained from the RCSB PDB database . Imidazole and NiCl2 solutions were injected into the activated chip to complete the surface functionalization of the chip. Then, Casp3 and PARP1 proteins were injected at a flow rate of 20 μL/min, and the capture levels were respectively reached at 1000 RU and 1200 RU. Micromolecules were diluted with Running Buffer  and injected into the flow cell of the channel at a flow rate of 20 μL/min for an association of 240 s, followed by 300 s dissociation. Both the association and dissociation processes were handled with the Running Buffer. Repeat 5 cycles of analyte according to analyte concentrations in ascending order. After each cycle of interaction analysis, the sensor chip surface should be regenerated completely with PBS as the injection buffer at a flow rate of 100 μL/min for 30 s to remove the ligand and any bound analyte. The analysis software used in this experiment was TraceDrawer (Ridgeview Instruments ab Sweden) and was analyzed by the one-to-one analysis model.The Sensor Chip NTA  should be prepared before the experiment, which was performed with an OpenSPRTM surface plasmon resonance instrument (Nicoya). The Casp3  and PARP1  proteins were diluted to 30 The TCMSP database was used to collect the active ingredients in TW. It is shown in In the present study, 2755 genes of PAH were screened out by GeneCards and the OMIM database. The R Venn package was used to draw the Venn diagram after filtering the obtained genes of TW and PAH. A total of 150 overlapping genes were filtered as candidate targets. Venn diagram data are shown in GO enrichment was obtained in our study, which expressed the functions of collected genes in Biological Process (BP) , cytologp value, the three clusters with the best scores in the PPI network were selected to describe their biological functions  network by Cytoscape software . The netunctions . In summunctions .Tripterygium wilfordii  corresponding to the top 2 active ingredients (kaempferol and triptolide) of ilfordii . The morilfordii . The expμM as determined in the SPR (A surface plasmon resonance (SPR) experiment was a kind of ligand with membrane protein interaction technology that could be used to verify the drug's main molecular targets. The experiment was unlabeled and was able to measure the real-time quantitative binding affinity and kinetics of the interaction of membrane proteins with ligand molecules using a relatively small amount of material . The rel the SPR .Tripterygium wilfordii were obtained, which together constituted a network diagram of the disease-active ingredient-predicted targets. The pathogenesis and development of pulmonary artery hypertension is a complex process involving various risk factors in multiple systems. Similarly, herbal medicines also play an important role in diseases by acting on different active components and targets. This study attempted to better explain the mechanism of action of Tripterygium wilfordii on pulmonary artery hypertension using network pharmacology and further verified its results by molecular docking, and the SPR experiment was further used to validate the binding relationship between ingredients and targets of this herbal medicine.As a method for the analysis of multicomponent, multitarget, and multimechanism herbal medicines, network pharmacology has been increasingly used in clinical practice. It has systematically revealed the mechanism by which herbal medicines act on the disease . And it Tripterygium wilfordii in pulmonary artery hypertension is not clear.As a common pulmonary vascular disease in clinical practice, pulmonary artery hypertension was characterized by a progressive increase in pulmonary vascular resistance, which could lead to various clinical complications, ultimately lead to right heart failure or even death , 4. Its Tripterygium wilfordii was kaempferol, followed by triptolide, sichenesin, and Tripterygium wilfordii lactone. Kaempferol has many pharmacological activities such as antioxidant damage, immune regulation, and estrogen-like effect, and has preventive and therapeutic effects on RA, diabetes, osteoporosis, and cardiovascular diseases. Kaempferol could be used in the treatment of cancer. Relevant studies have found that kaempferol can affect autophagy in cancer cells, thereby exerting antitumor activity [β, IL-6, and TNF-α in mice macrophages. In addition, it has been found that nobiletin acts by increasing antioxidant activity and characteristics [In this study, we concluded by network pharmacology and molecular docking that the compounds with the highest comprehensive score of activity . Many stactivity . Relevaneristics .Tripterygium wilfordii treating PAH, including the IL-17 signaling pathway, TNF signaling pathway, Toll-like receptor signaling pathway, and apoptosis. Studies have found that the IL-17 function of interleukin (IL)-17, as one member of the new family members of inflammatory cytokines, is much more subtle than that it simply triggers inflammation. Increasing evidence suggests that IL-17 has important environmental and tissue-dependent roles in maintaining health in response to injury, physiological stress, and infection [α can cause the abnormality of nitric oxide lyase (NOS) in vascular endothelial cells, reduce the synthesis of prostaglandin (PG) by pulmonary artery smooth muscle cells, and eventually lead to impaired vascular endothelial function and pulmonary vasoconstriction. Studies have shown that kaempferol might be involved in NF-κB signaling pathway to inhibit the expression of the major proinflammatory cytokines, including IL-17A and TNF-α, and decrease the percentage of IL17A+CD4+ T cells in the imiquimod (IMQ)-induced psoriatic mouse model [Tripterygium wilfordii treatment of PAH may be related to these KEGG pathways, and further validation is required.The Gene Ontology project classifies functions based on three aspects: biological processes, cellular components, and molecular functions. It involves cellular response to organismal substances, membrane rafts, signaling receptor binding, etc. The KEGG enrichment analysis results showed that the targets were regulated by 243 KEGG pathways. It was related to multiple biological processes and signaling pathways associated with nfection , 28. Relse model . In addise model . Relevanse model . It is cTripterygium wilfordii and their corresponding active targets. kaempferol and CASP3 obtained the highest docking total score, which was higher than the docking total score for the binding of triptolide and PARP1. For further validation, we performed SPR experiments. It showed that kaempferol and triptolide were selected as extracellular validation molecular models to perform small-molecule and macromolecule interaction experiments with CASP3 and PARP1, respectively. According to the results, it can be speculated that kaempferol and triptolide can bind to CASP3 and PARP1 and inactivate them so as to prevent other proteins from binding to cell surface receptors. In summary, these KEGG pathways acted synergistically in the treatment of PAH, providing a strong basis for multitarget therapy. In addition, molecular docking has been widely used in the prediction of clinical targets. Molecular docking results showed that kaempferol and triptolide had a high score when docking with CASP3 and PARP1, and this result suggested that further attempts could be made to develop their leading compounds, which was consistent with the results of network pharmacology analysis.To further verify the mechanism of action, we used molecular docking to predict and analyze the binding energy of the active components of Tripterygium wilfordii in the treatment of PAH.TW may have therapeutic effects on PAH through multitargets and multimethods, which provided a scientific basis for further elaborating the mechanism of TW, as a traditional Chinese medicine, has been increasingly valued in the treatment of various diseases, and many mechanistic studies on TW and diseases are under way. To our knowledge, there is no study performed on TW and PAH mechanisms. In this study, the mechanisms between TW and PAH were investigated by network pharmacology, molecular docking, and SPR trials. However, the specific pathways in the treatment of PAH are unclear. The efficacy of TW in treating PAH through multiple pathways and multiple targets also needs further experimental verification. It may provide new perspectives on the treatment of PAH and contribute to the development of Chinese herbal medicine in the treatment of diseases.


Thin endometrium is considered as a leading cause of infertility, recurrent pregnancy loss, and repeated implantation failure. The seed of Cuscutae Semen (CS) has been used to prevent aging and improve sexual function in Traditional Chinese Medicine. However, the pharmacological mechanism of CS in preventing and treating thin endometrium remains to be elucidated.  Three public databases, TCMSP, GeneCards, and OMIM, were searched to collect the main active compounds and putative molecules of CS, as well as the targets of thin endometrium, respectively. The CS and thin endometrium common targets were subject to protein-protein interaction (PPI) analysis followed by functional enrichment analysis. The best binding mode of CS compounds and common target proteins was evaluated by molecular docking and analysis in the AutoDockTools.  In total, 11 main active compounds, 102 drug target proteins, and 70 CS and thin endometrium common targets were identified. There were 68 nodes with 722 edges in the PPI network; HIF1A, MYC, ESR1, and EGFR were the top 4 targets. After functional enrichment analysis, it was revealed that the therapeutic effects of active compounds of CS on thin endometrium were achieved through cellular response to chemical stress, transcription regulator, DNA-binding transcription factor binding, chemical carcinogenesis-receptor activation, lipid, and atherosclerosis. The molecular docking analysis revealed that the 3 active compounds of CS, quercetin, matrine, and isorhamnetin, have good binding ability with their targets, HIF1A, MYC, ESR1, and EGFR.  Our study uncovers the main active compounds in CS and their corresponding targets related to thin endometrium which explains the pharmacological mechanism underlying therapeutic effects of CS on thin endometrium. The human endometrium is the inner lining of the uterus that is a highly regenerative tissue at each cycle under estrogen stimulation in the menstrual cycle . Its solCuscutae Semen (CS), originated from the dry and mature seeds of Cuscuta australis R. Br. or Cuscuta chinensis Lam., has been widely used as Chinese medicine since ancient . CS can The dominant paradigm in drug discovery refers to the concept of designing ligands with maximum selectivity to act on individual drug targets . HoweverThe Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) is a public pharmacology platform covering Chinese herbal medicines that captures the relationships between drugs, targets, and diseases . We usedhttps://www.genecards.org/) and Online Mendelian Inheritance in Man database . Duplicate values were removed. The Venn diagram of the thin endometrium-associated targets and the targets related to the active components of CS was made using the R software to obtain disease-drug common targets. The disease-target-compound network was visualized using the Cytoscape software to visualize.The target genes related to thin endometrium were acquired from two public databases: the GeneCards database (https://www.string-db.org/) to obtain the PPI network which was visualized by importing the tsv-based file to the Cytoscape software (3.8.1). The species must be “Homo sapiens,” and high confidence for interaction score must not less than 0.4. In the PPI network, nodes reflect proteins, and connecting lines represent PPIs. The core genes ranked according to degree value obtained using cytoHubba plug-in of Cytoscape.The disease-drug common targets were mapped into the STRING 11.0 database (Gene Ontology (GO) functional analysis and KEGG-based pathway analysis were implemented to harvest the potential functions of the disease-drug common targets by using the “clusterProfiler” in the R software. The results of GO analysis were presented at three levels: biological processes, molecular functions, and cellular components. KEGG stores the items linking metabolic pathways or signal transduction pathways. The GO terms at three levels and significant KEGG pathways enrichments were ranked by the value of GeneRatio, and the top 20 pathways and top 10 GO functions were presented as bubble plots using the “pathview” package in the R software.https://www.rcsb.org/. Then, we converted the pdb-based files containing curcuma and the proteins encoded by core targets into pdbqt-based files and search for active pockets. The AutoDockTools was employed to determine the binding ability of ligands and receptors. The binding energy less than 0 indicates spontaneous binding of ligand and receptor, and smaller values reflect higher binding activity.Molecular docking technology is a well-recognized method to examine receptor-ligand interactions along with binding patterns and affinities. Therefore, we performed molecular docking analysis between curcuma and the top core target genes in the PPI network. The pdb format of the 3D structure of the proteins encoded by the top core target genes was downloaded from the RCSB Protein Data Bank (PDB) database, accessed at First, we searched the active compound components of CS in the TCMSP database and collected active ones using an OB at least 30% and DL at least 0.18 as cutoff values; a total of 11 active compounds of CS were identified . We remoβ-ol, and β-sitosterol. Next, we searched the GeneCards and OMIM databases and sorted out 2342 targets of thin endometrium, respectively. Accordingly, we mapped 2342 thin endometrium-related disease targets to 102 target genes of the active compounds of CS by using Venny 2.1 drawing software. We finally identified 70 CS and thin endometrium common targets . We thenWe introduced 70 CS and thin endometrium common targets into the STRING database for PPI analysis. As presented by p < 0.05). The active ingredients of CS were associated with 1146 terms at the level of BP, 15 terms at the level of CC, and 82 terms at the level of MF. p < 0.05). Next, we further analyzed 70 CS and thin endometrium common targets by GO annotation and KEGG pathway analyses. After GO analysis, a total of 1243 GO terms were identified to be significantly enriched by these thin endometrium-CS common targets , matrine and MYC , quercetin and MYC , isorhamnetin and ESR1 , and quercetin and EGFR  suggests that the 3 active compounds of CS, quercetin, matrine, and isorhamnetin, have good binding ability with their targets, HIF1A, MYC, ESR1, and EGFR .It is reported that adequate uterine receptivity and good quality of endometrium are necessary factors for successful pregnancy. Thin endometrium  may be a contributing factor to the increased risk of infertility . TCM appβ-ol, and β-sitosterol were obtained. Lastly, the top 4 key targets including HIF1A, MYC, ESR1, and EGFR were identified according to the PPI network. Hypoxia plays an important role in in the pathology of human diseases represented by cancers [κB inhibition and protein kinase B phosphorylation [α and IL-1β and attenuated the uterus injury in the lipoteichoic acid-induced mouse endometritis model [κB, and MAPK to display antitumor, anti-inflammatory, and antioxidation prosperity [Network pharmacology-based approach combined with molecular docking has gained popularity in exploring active compounds of TCM, key targets acting on diseases, and potential pharmacological mechanism of TCM against diseases –33. On t cancers , inflamm cancers , and neu cancers . Hypoxia cancers . Endomet cancers . The tra cancers . Females cancers . MYC gen cancers . Althoug cancers . In addi cancers . Estroge cancers . Studies cancers . In a ba cancers . EGFR is cancers . Suh et  cancers . In our rylation , 50. Matrylation . Matrineis model . Isorhamosperity .Several limitations should be noticed when our results were interpreted. First, experimental validation in vivo and in vitro focusing on the suppressive effects of main 3 active compounds of CS, quercetin, matrine, and isorhamnetin, cells as well as the expressions of HIF1A, MYC, ESR1, and EGFR in the setting of thin endometrium is warranted to improve the preliminary nature of the study. Second, the molecular mechanism by which CS against thin endometrium is not completely characterized as these public databases we used in the study have been updated continuously.In summary, the study demonstrates that CS, especially its main 3 active compounds of CS, quercetin, matrine, and isorhamnetin, may exert therapeutic effects on thin endometrium through the modulation of multiple targets, HIF1A, MYC, ESR1, and EGFR. The present work not only investigates the complex mechanism of CS in the treatment of thin endometrium with multicomponent, multitarget, and multisignal but also supports that network pharmacology prediction method with molecular docking verification may provide a preliminary but systemic exploration focusing on the pharmacokinetic properties and mechanism of TCM in human diseases, offering opportunities to develop micelles for targeted delivery of TCM to thin endometrium.


The current geneset, network, and pathway analysis (GNPA) web servers, e.g., DAVID, EnrichR, WebGestaltR, or PAGER, do not allow automated integrative functional genomic downstream analysis. In this study, we developed a new web-based interactive application, “PAGER Web APP”, which supports online R scripting of integrative GNPA. In a case study of melanoma drug resistance, we showed that the new PAGER Web APP enabled us to discover highly relevant pathways and network modules, leading to novel biological insights. We also compared PAGER Web APP’s pathway analysis results retrieved among PAGER, EnrichR, and WebGestaltR to show its advantages in integrative GNPA. The interactive online web APP is publicly accessible from the link,  Functional genomics analysis is widely performed to characterize genes and intergenic regulatory regions in the genome that contribute to different biological processes . EssentiDuring the last decade, several GNPA web servers have been developed , includiin vitro experiment. Hence, PAGER enables gene prioritization using the network topology in each PAG  in default. Users can add or remove the source name in the source multiple-choice field. PAGER Web APP also allows users to change the minimum number of overlapped genes, similarity score, and “-log2p-value” cutoff. The similarity score is based on the combination of overlap coefficient and Jaccard index using the methods described previously . We clean up the terms or names by removing irrelevant content, such as species, identifier, etc., and making all the terms lower case. We also remove the redundant terms enriched from different data sources, such as “MAPK signaling pathway” may come from KEGG and wikiPathway at the same time. Then we apply the string similarity using optimal string alignment (OSA) distance  and take the highest score with the term as the most similar term. Therefore, we generate a list of pairwise term-to-term similarities. Finally, we use the default or customized similarity cutoff to filter low similar term-to-term pairs.https://cran.r-project.org/web/packages/igraph/index.html) to find the community structure in m-type PAG-to-PAG networks. The Louvain clustering is based on the modularity in a scale between -0.5 (non-modular clustering) to 1 (fully modular clustering) described in the paper (We apply the Louvain clustering function in the igraph library in R (he paper .https://cran.r-project.org/web/packages/wordcloud2/index.html) for the visualization.We create bag-of-words from the space-separated PAG names to present the frequently appearing words in each PAG for any enriched PAG set. We create word corpus, remove the potential punctuation such as comma, colon, etc., make all the words lower case, remove both irrelevant words and common words, “pathway,” “signaling,” “human,” “homo,” “sapiens,” “has,” “or,” and “and”. Finally, we apply wordcloud2 function in the wordcloud2 library in R (https://cran.r-project.org/web/packages/bs4Dash/index.html) package in R. The application is supported by R Shiny (https://shiny.rstudio.com/) framework. In addition to data processing and statistical analysis, GNPA Analysis are implemented using PAGER API, EnrichR API and WebGestaltR API. Graphing libraries like Plotly (https://plotly.com/r/), igraph in R (https://igraph.org/r/), ggplot2, wordcloud2, and VennDiagram have been used.The PAGER Web Application user interface is designed using bs4Dash (https://bioconductor.org/packages/release/bioc/html/DESeq2.html) to generate the differentially expressed genes that compared drug-resistant patients to drug-sensitive patients. The output file is stored in the PAGER Web APP as a demo.We downloaded the melanoma dataset of 64 patient samples from cBioPortal, and it was initially published in a paper in the New England Journal of Medicine . We idenp-value ≤ 0.01  and saved their fold changes as input of ROntoTools. We set the adjusted p-value ≤ 0.01 and the absolute logFC >0.5 to get the 1,470 candidate genes as the input of PAGER, EnrichR and WebGestaltR.We loaded the differentially expressed gene table, “extdata/E-GEOD-21942.topTable.RData”, preprocessed in the ROntoTools library . This dahttps://bioconductor.org/packages/release/bioc/html/limma.html). We set the cutoffs of adjusted p-value ≤ 0.05 and the absolute logFC >0.5 to get the 518 candidate genes in Crohn’s disease and the 528 candidate genes in the ulcerative colitis study.We downloaded the transcription profiling by array of RNA from inflamed and non-inflamed colonic mucosa (E-MTAB-2967). In Crohn’s disease, there are 15 inflamed colonic mucosa and 15 controls. In ulcerative colitis, there are 14 inflamed colonic mucosa and 14 controls. We performed the normalization and linear regression using the limma library in R  that implements semantic searches of PubMed abstracts to report biomedical literature citations . We implhttps://www.ncbi.nlm.nih.gov/research/pubtator-api/publications/export/pubtator?pmids=[PMID]. We took a sample list of PubMed IDs from each retrieved entry. To remove biases and further confirm the mentioned keywords, we applied the analysis described in the previously developed tool called biomedical entity expansion ranking and exploration (BEERE)   to extrap-value cutoff 0.05 and the absolute gene’s log fold-changes larger than or equal to 0.5. Secondly, we performed pathway enrichment analysis using the ROntoTools. Thirdly, we defined the “true” data set as the significantly enriched pathways with adjusted combined p-values ≤ 0.05  curve and the area-under-the-curve (AUC) value. The hybrid technique also includes performing a literature co-citation-based assessment. We constructed the ground truth using ROntoTools, the best performing method reported in the review paper , in threpv.func”  in ROntop-value ranked pathways can be supported by the PubMed scores. Particularly, we ranked the PAGs based on adjusted p-values, and compared the top n% PAGs’ PubMed scores to the bottom (100-n)% PAGs’ PubMed scores for each method, where n ranges from 10 to 90 with a step increment of 10. And then, we reported their average p-values, respectively. The smaller p-values are, the better performance the methods have.In the literature co-citation validation, we developed a t-test based statistical model on evaluating how significant the Compared to EnrichR and WebGestalt, PAGER progresses the network interpretation of functional genomics results. Although there are 35 unique geneset libraries reported in most updated PAGER, which are less than EnrichR, each of PAG in PAGER contains metadata other than EnrichR and WebGestalt, including PAG-type , PAG descriptions, source link, publication reference, curator, and nCoCo score (described in PAGER 2.0). In addition, PAGER provides geneset intra-network views, including the protein-protein interaction network and gene-gene regulation network members in each geneset, while WebGestalt reports pathway maps in wikiPathway source only. For the geneset’s inter-network, WebGestalt inherits the Gene Ontology (GO) hieratical structure from the GO consortium. We extent the relationship concepts by introducing m-type (co-membership) PAG-to-PAG relationships and r-type (regulatory) PAG-to-PAG relationships described in PAGER. The m-type PAG-to-PAG relationships represent co-memberships between two PAGs, which reveals signaling cross-talk between PAGs that share signaling components within signal transduction pathways in response to external stimuli. The r-type PAG-to-PAG relationships represent the PAG causal ordering inferred from gene-to-gene regulations by adapting our method previously described in PAGER . The PAGTo better identify the cohorts in melanoma cancer to improve the treatment, functional genomics has been applied to the next-generation sequencing data for an in-depth understanding of the molecular mechanisms in the drug resistance cases. We collected the transcriptomes from the cBioPortal database in this study. In the result, we found 164 P-type PAGs (pathways) to be significantly enriched.In the 164 P-type PAGs, they are two PAGs that are derived from more than one data source, i.e., “PI3K-Akt signaling pathway” and “Bladder cancer”, each of which is simultaneously recorded in both “WikiPathway_2021” and “KEGG_2021_HUMAN” data sources. Compared to the results from EnrichR and WebGestaltR, PAGER had the greatest number of enriched pathways, which is 164, EnrichR has 98, and WebGestaltR has 52 . PAGER aIn the 164 P-type PAGs reported by PAGER, there were 4 major sources and 1 minor source . 50 (30.Cluster 1 consists of 3 pathways with represented terms “FAM20C” protein (Golgi-associated secretory pathway kinase), “IGF” protein (insulin-like growth factor). Cluster 2 has 7 pathways related to the Gi-activating and ligand-receptor bindings. Cluster 3 is formed by 43 pathways related to collagen formation and binding events. Cluster 4 has 37 pathways related to inflammasome responses in cancer or infection. Cluster 5 contains 66 pathways with the regulation of several inflammatory and cytokine responses through the receptor interactions. Hence, PAGER Web APP enables screening for the critical terms and quickly identifying the specific molecular mechanism communities in the m-type PAG-to-PAG network.The 164 P-type PAGs form a densely connected m-type PAG-to-PAG network  with an average degree of 18. After the community detection using Louvain clustering, we found 5 PAG clusters in the m-type PAG-to-PAG network . The extWe found all of them relevant to melanoma cancer for the 33 consensus pathways among PAGER, EnrichR, and WebGestaltR results. We listed the results using pathway name, the pairwise term similarities, keywords used for co-citation retrieval, number of co-citations, odds ratio, PubMed score, one of PubMed IDs, and BEERE validation in . All theWe ranked the pathways based on the d score . As repod score . We obsed score   signaling pathway, reported in PAGER also shows how literature supports its involvement in melanoma. IL-10’s role in immune system biology is that it acts as an immunomodulator, which means that it regulates how the immune system behaves . Terai eWe applied precision to measure the performance among the three tools using different cutoffs . To evalp-value (0.318) compared with ROntoTools (0.319), EnrichR (0.319) and WebgestaltR (0.319). In the inflamed colonic mucosa vs. non-inflamed colonic mucosa in Crohn’s disease study  compared with ROntoTools (0.317), PAGER (0.322) and WebgestaltR (0.322). In the inflamed colonic mucosa vs. non-inflamed colonic mucosa in the ulcerative colitis study  compared with ROntoTools (0.321) and WebgestaltR (0.322). Overall, PAGER was among the best.In the sclerosis study, we found 20 pathways in the true set and 203 pathways in the false set using ground truth discovered by the topology-based method, ROntoTools . The PAGse study , we founis study , we founTo summarize, we developed an interactive online functional genomics analysis tool, PAGER Web APP. The tool can provide new and significant insights into functional genomics studies and may support precision medicine in delivering the candidate targets. In the melanoma drug-resistant-sensitive case study, we observed that the P-type PAGs (pathways) reported in PAGER lead to insights into molecular mechanisms validated in literature support. PAGER web server supports the feature of r-type PAG-to-PAG network generation.p-value using p-value, p-value’s multiple tests from the PAGs under the constraints of PAG source, overlaps, PAG size, and similarity score, and the p-values in the multiple test that has less than or equal to the original p-value. EnrichR uses fuzzy enrichment analysis, and applies Benjamini–Hochberg for FDR, according to the documentation online. The WebgestaltR uses hypergeometric test to evaluate the significance of enrichment and uses Bonferroni for p-value adjustment. To construct the ground truth in assessing the performance of functional genomics analysis tools, many data-driven approaches can be applied, such as target pathway , TopoGSA  to improve the use. In the current version, we observed that the user interface, especially, in the enriched results, the enriched PAGs’ result is not that interactive enough for users to select a certain number of PAGs or arbitrarily remove some of the records to generate PAG-to-PAG networks. We will implement the interactive panels in the future release. PAGER Web APP calls the PAGER API, which implements an over-representation analysis (ORA) technique by default. In general, advanced functional class scoring (FCS) techniques, e.g., Gene Set Enrichment Analysis (GSEA) , Gene Se TopoGSA , Bayesia TopoGSA , and Pat TopoGSA , etc. We TopoGSA  to guide


Purpose: Dapansutrile is an orally active β-sulfonyl nitrile compound that selectively inhibits the NLRP3 inflammasome. Clinical studies have shown that dapansutrile is active in vivo and limits the severity of endotoxin-induced inflammation and joint arthritis. However, there is currently a lack of more in-depth research on the effect of dapansutrile on protein targets such as NLRP3 in gouty arthritis. Therefore, we used molecular docking and molecular dynamics to explore the mechanism of dapansutrile on NLRP3 and other related protein targets.Methods: We use bioinformatics to screen active pharmaceutical ingredients and potential disease targets. The disease-core gene target-drug network was established and molecular docking was used for verification. Molecular dynamics simulations were utilized to verify and analyze the binding stability of small molecule drugs to target proteins. The supercomputer platform was used to measure and analyze the binding free energy, the number of hydrogen bonds, the stability of the protein target at the residue level, the radius of gyration and the solvent accessible surface area.Results: The protein interaction network screened out the core protein targets  of gouty arthritis. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that gouty arthritis mainly played a vital role by the signaling pathways of inflammation and immune response. Molecular docking showed that dapansutrile play a role in treating gouty arthritis by acting on the related protein targets such as NLRP3, IL1B, IL6, etc. Molecular dynamics was used to prove and analyze the binding stability of active ingredients and protein targets, the simulation results found that dapansutrile forms a very stable complex with IL1B.Conclusion: We used bioinformatics analysis and computer simulation system to comprehensively explore the mechanism of dapansutrile acting on NLRP3 and other protein targets in gouty arthritis. This study found that dapansutrile may not only directly inhibit NLRP3 to reduce the inflammatory response and pyroptosis, but also hinder the chemotaxis and activation of inflammatory cells by regulating IL1B, IL6, IL17A, IL18, MMP3, CXCL8, and TNF. Therefore, dapansutrile treats gouty arthritis by attenuating inflammatory response, inflammatory cell chemotaxis and extracellular matrix degradation by acting on multiple targets. The mechanisms analysis of dapansutrile in the treatment of gouty arthritis. Gouty arthritis is considered one of the most common forms of inflammatory arthritis, it is a metabolic rheumatic disease . Gouty aDapansutrile (OLT1177) is a beta-sulfonitrile compound. It can inhibit the NLRP3 inflammasome and reverses the metabolic cost of inflammation . The druHowever, there is currently a lack of more in-depth and systematic research on dapansutrile in the treatment of gouty arthritis. Molecular dynamics can comprehensively and systematically simulate the interaction and binding stability between small molecule monomers and protein targets with the help of powerful computing power.Molecular dynamics (MD) use large computer clusters as the carrier to obtain data such as the microstructure, physicochemical properties, and performance characterization parameters of small molecule drugs and proteins through calculation . It is aSince the mechanism of action of dapansutrile in the treatment of gouty arthritis is still unclear, this study used bioinformatics to screen core targets between dapansutrile and gouty arthritis, and we used gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and protein-protein interaction (PPI) to analyze target genes and explore their mechanisms of action and potential pathways. We used molecular system motions to simulate the results of computing interactions from the cellular level to the chemical group level. Molecular docking was used to determine the affinity of monomeric compounds to protein targets, and molecular dynamics were used to model the stability of bound complexes. Research on the mechanism of action of dapansulide in the treatment of gouty arthritis will promote the related research and clinical application of the drug.Homo sapiens,” and obtained relevant information on protein interactions by STRING database. Finally, the network topology parameters were analyzed by Cytoscape 3.7.1, and the core protein targets were screened out according to the criterion that the node degree value and the betweenness center value were greater than the average value.“Gouty arthritis” was used to be the key word to obtain the disease gene targets through GeneCards database. The STRING database was used to analyze the protein-protein interaction (PPI) of dapansutrile in the treatment of gouty arthritis . In ordeHomo sapiens”  functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. We obtained molecular function (MF), cellular component (CC) and biological process (BP) of the gene targets through GO enrichment. The disease related targets obtained from screening were input into the DAVID database by entering the list of target gene names and selecting the species as “sapiens” . In thisp < 0.05 .This study used the Cytoscape 3.7.1 network map software to construct a disease-core target gene-drug network and conduct topological analysis. The core gene targets can be screened based on the node degree value greater than 2 times the median .Molecular docking was used to study the molecular affinity of dapansutrile with gouty arthritis protein targets. In this study, AutoDock Vina 1.1.2 software was used for molecular docking work. Before docking, PyMol 2.5 was used to process all receptor proteins, including removal of water molecules, salt ions and small molecules . ADFRsuiIn this study, the stability of the conformational complex of the dapansutrile and gouty arthritis proteins was further verified by molecular dynamics simulations. Molecular dynamics (MD) simulation is a comprehensive set of molecular simulation methods combining physics, mathematics and chemistry. This method mainly relies on Newtonian mechanics to simulate the motion of molecular systems, we calculate macroscopic properties such as thermodynamic quantities of a system by taking samples from an ensemble of different states of a molecular system . In thisThe proteins were all energy minimized using the steepest descent method and the conjugate gradient method. Subsequently, combined NVT and NPT  and MD tests  were performed at 298 K temperature and 1 bar pressure using a jump-integration algorithm. The coordinates and energy of the system are saved every 10 ps. Finally, 50 ns production simulations were carried out for each system under periodic boundary conditions. For all simulations, the van der Waals force (vdw) cutoff and short-range electrostatic interactions were set to 10 Å. The Particle-Mesh-Ewald (PME) method was used to evaluate long-range electrostatic interactions. Molecular dynamics simulation trajectories include protein-ligand complex root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration and solvent accessible surface area (SASA).In this study, the binding free energy of the compound was investigated by MM-PBSA method, and its conformational stability was studied in detail. We calculated the binding free energies between proteins and ligands in all systems using the MM/GBSA method . The molEbond), angular energy (Eangle), torsion energy (Etorsion), ΔGGA and ΔGGB are collectively called solvation free energy. The non-polar solvation free energy (ΔGGA) was calculated based on the product of surface tension (γ) and solvent accessible surface area (SA), ΔGGA = 0.0072 × SASA . The RMSF can reflect the flexibility of the protein during molecular dynamics simulations. The binding of small molecule drugs to proteins reduces the flexibility of the proteins, which results in stabilization of the proteins and thus their efficacy. The results showed that most of the proteins had low RMSF except for the two ends, indicating that the protein core structure has good rigidity. Notably, the overall RMSF of IL1B, NLRP3 and TNF bound to small molecules was less than 2.5 Å, indicating that these proteins are more rigid when bound to small molecules. The results are shown in The radius of gyration (RoG) can reflect the degree of compactness of the complex. The results reflected the variation of RoG over time for the six complexes during the molecular dynamics simulation. The experimental results showed the degree of denseness of the complexes from largest to smallest: Dapansutrile/NLRP3, Dapansutrile/IL1B, Dapansutrile/IL18, Dapansutrile/MMP3, Dapansutrile/TNF, Dapansutrile/IL6, Dapansutrile/IL17A, and Dapansutrile/CXCL8. The simulation results indicated that dapansutrile/NLRP3, dapansutrile/IL1B, dapansutrile/IL18, and dapansutrile/MMP3 have strong binding potential. The results of RoG experiments were consistent with those of RMSD. The results are shown in The solvent accessible surface area (SASA) indicates the area where the complex can come into contact with the aqueous solution. The contact area of the complex indicates the size of the interaction between the complex and the aqueous solution. In addition, the fluctuation of SASA responds to the exposure of the protein surface and the changes occurring in the buried area. The fluctuation analysis of SASA suggests that the fluctuations of Dapansutrile/NLRP3, Dapansutrile/TNF, Dapansutrile/IL1B, Dapansutrile/IL18, and Dapansutrile/MMP3 were small. This result implied the close interaction within the complex, which was the basis for the formation of stable binding of the complex. The results are shown in This study explored the pharmacological mechanism of dapansutrile in the treatment of gouty arthritis by molecular docking and molecular dynamics simulation based on molecular system movement. This study found that dapansutrile may not only directly inhibit NLRP3 to reduce the inflammatory response and pyroptosis, but also hinder the chemotaxis and activation of inflammatory cells by regulating IL1B, IL6, IL17A, IL18, MMP3, CXCL8, and TNF. Firstly, dapansutrile may attenuate inflammatory responses and reduce pyroptosis by directly inhibiting the NLRP3 inflammasome and hindering the activation of downstream inflammatory inflammation. Secondly, dapansutrile may impede the activation of IL1B, CXCL8, and TNF reducing the chemotaxis and activation of inflammatory cells. Finally, dapansutrile may reduce the expression of MMP3 by regulating IL6, IL18, and IL17A, thereby degrading the extracellular matrix to treat gouty arthritis. Therefore, these results demonstrate that dapansutrile treats gouty arthritis by inhibiting the inflammatory response from multiple targets.in vivo, and predict their interaction and binding mode and affinity. Therefore, the results of molecular docking can be used to explore the mechanism of action of dapansutrile on gouty arthritis.Molecular docking can recognize each other through the spatial matching of drug small molecule dapansutrile and protein macromolecules Firstly, molecular docking experiments indicated that dapansutrile had strong affinity for the protein targets NLRP3 and MMP3. The binding of dapansutrile in IL1B, CXCL8 and TNF were relatively stable, molecular docking showed that the binding of Dapansutrile/IL1B and Dapansutrile/IL18 is mainly maintained by hydrogen bonding and hydrophobic interaction. Dapansutrile/CXCL8 and Dapansutrile/MMP3 were mainly through hydrophobic interaction. Dapansutrile combined with IL6, IL18, and IL17A can form stable complexes, but there were some abnormal fluctuations, which may be due to the influence of the number and angle of binding bonds.Secondly, based on the trajectory of the molecular dynamics simulation, we calculated the binding energy using the MMGBSA method, which could more accurately reflect the binding mode of small molecules and target proteins. In the molecular dynamics simulation, the RMSDs of Dapansutrile/NLRP3 converged gradually in the first 5 ns of the simulation and preserved stable fluctuations in subsequent simulation. The RMSF results suggested that the overall RMSF of IL1B and TNF was less than 2.5 Å when they were bound to small molecules. These proteins are more rigid when bound to small molecules. The radius of gyration suggested that Dapansutrile/IL18 and Dapansutrile/MMP3 have stable fluctuations in size, which means they have high binding potential. Hydrogen bonding is also an important basis for the formation of stable binding between small molecule drugs and protein targets. The results of this study showed that the number of hydrogen bonds in Dapansutrile/IL18 and Dapansutrile/MMP3 were the best in terms of size and density. The number of their hydrogen bonds was stable throughout at about three. And all eight complexes can form stable hydrogen bonds. Therefore, the results of hydrogen bonding analysis showed that all the eight complexes had the basis for forming stable bonds.Finally, the binding free energy consists mainly of non-bonding interactions . Because only non-bonding interactions are generally present in the actual drug small molecule (ligand) and protein (receptor) complex systems. The drug molecule binds reversibly to the proteins through non-bonding interactions, and this binding is more favorable for its own metabolism and excretion. Therefore, the results of free energy of binding were the comprehensive evaluation of the binding stability of drug and protein targets in this study. We analyzed our binding free energy consequences and other experimental results to derive a comprehensive ranking of the complex binding stability from strong to weak Dapansutrile/MMP3, Dapansutrile/NLRP3, Dapansutrile/IL1B, Dapansutrile/IL17A, Dapansutrile/IL6, Dapansutrile/TNF, Dapansutrile/IL18, Dapansutrile/CXCL8.Dapansutrile may inhibit the activation of downstream inflammatory signaling pathways and reduce cell death by directly inhibiting the NLRP3 inflammasome.Bioinformatics analysis suggested that dapansutrile can attenuate inflammatory responses and reduce pyroptosis by directly inhibiting the NLRP3 inflammasome and hindering the activation of downstream inflammatory inflammation. As a key component of inflammatory activation, NLRP3 plays a crucial role in innate immunity and inflammation. NLRP3 has a regulatory role in inflammation, immune response and cellular scorching as an upstream activator of NF-kappaB signaling. Analysis of protein interaction network PPI suggested that NLRP3 was closely related to inflammatory responses targets. KEGG signaling pathway analysis showed that NLRP3 was involved in protein metabolism and NOD-like receptor signaling pathway. GO analysis suggested that NLRP3 was involved in peptidoglycan binding.in vitro at 1 μM or less. Interestingly, in LPS-stimulated human blood-derived macrophages, dapansutrile reduced IL1B levels by 60% and IL18 by 70%, in vitro at concentrations 100-fold lower than plasma concentrations safely achieved in humans  and procaspase-1 . The intn humans . Alba SáBertinaria discussed whether the bond between dapansutrile and NLRP3 was covalent or non-covalent . In factTherefore, dapansutrile may attenuate inflammation and reduces pyroptosis by inhibiting the NLRP3 inflammasome to treat gouty arthritis.Dapansutrile may reduce the inflammatory response and the chemotaxis of inflammatory cells by blocking the activation of IL1B, CXCL8, and TNF for the treatment of gouty arthritis.Dapansutrile may impede the activation of IL1B, CXCL8, and TNF reducing the chemotaxis and activation of inflammatory cells. IL1B is an important mediator of inflammatory response, and it is involved in various cellular activities such as cell proliferation, differentiation and apoptosis. IL1B is also involved in the pathogenesis of osteoarthritis. KEGG signaling pathway analysis suggested that IL1B regulated rheumatoid arthritis and glucocorticoids. GO analysis indicated that IL1B was associated with protein domain-specific binding. CXCL8  is a chemokine that attracts neutrophils, basophils and T cells. It is not only involved in neutrophil activation and chemotaxis, but also has a role in systemic inflammatory response syndrome (SIRS). KEGG signaling pathway analysis included cellular senescence and MIF-mediated glucocorticoid regulation. GO analysis included chemokine activity and interleukin 8 receptor binding. Protein interaction network analysis indicated that IL1B, CXCL8, and TNF were jointly engaged in the chemotaxis and activation of inflammatory cells. TNF is a multifunctional pro-inflammatory cytokine. This cytokine is mainly secreted by macrophages, it causes fever by direct action or through IL1B secretion, and has been implicated in the induction of cachexia. KEGG signaling pathway analysis suggested that TNF regulated inflammatory response and inflammatory bowel disease. GO analysis indicated that TNF affected cytokine activity.Therefore, dapansutrile may reduce the chemotaxis and activation of inflammatory cells for the treatment of gouty arthritis by blocking the activation of IL1B, CXCL8, and TNF.Dapansutrile may regulate extracellular matrix degradation by reducing MMP3 expression through IL6, IL18, and IL17A in the treatment of gouty arthritis.Dapansutrile may reduce the expression of MMP3 by regulating IL6, IL18, and IL17A, thereby degrading the extracellular matrix to deal with gouty arthritis. IL6 is mainly produced at sites of acute and chronic inflammation, and it has been implicated in various inflammation-related disease states, including diabetes and systemic rheumatoid arthritis. Protein interaction network analysis showed that IL6, IL18, IL17, and MMP3 were closely connected with each other. KEGG signaling pathway analysis showed that IL6 was involved in dendritic cell developmental lineage pathways and cellular senescence. GO analysis included signaling receptor binding. IL17A is involved in inducing the production of inflammatory molecules, chemokines, antimicrobial peptides and remodeling proteins. IL17A plays a key role in inducing innate immune defenses, and IL17A stimulates non-hematopoietic cells and promotes the production of chemokines, which attract bone marrow cells to sites of inflammation. KEGG signaling pathway analysis included MIF-mediated glucocorticoid regulation and IL17 family signaling pathways. GO analysis included cytokine activity. IL18 is associated with tissue and organ damage and plays an important role in potentially fatal diseases characterized by cytokine storm. KEGG signaling pathway included MIF-mediated glucocorticoid regulation and IL-1 family signaling pathway. MMP3 is involved in the breakdown of extracellular matrix in arthritis and metastasis. MMP3 is regarded as involved in wound repair, atherosclerosis progression and tumor initiation. KEGG analysis included Gastrin-CREB signaling through PKC and MAPK. GO analysis included calcium binding and metallopeptidase activity.Studies have shown that dapansutrile can inhibit the IL6/STAT3 axis to inhibit breast cancer metastasis . TantileTherefore, Dapansutrile may decrease the expression of MMP3 by regulating IL6, IL18, and IL17A, thereby degrading the extracellular matrix for the treatment of gouty arthritis.Gouty arthritis is a metabolic rheumatic disease caused by disorders of purine metabolism and reduced synthesis or excretion of uric acid. Therefore, the treatment of gouty arthritis mainly revolves around correcting the metabolic abnormalities and reducing the inflammatory response of the body. Current studies have shown that dapansutrile alleviates the clinical symptoms of gouty arthritis by suppressing the inflammatory response, and that dapansutrile has good therapeutic effects and few side effects.The results of our study further validated the important role of dapansutrile in reducing the inflammatory response. And we believed that dapansutrile could reduce the inflammatory response and body damage not only through NLRP3 but also through other protein targets . Moreover, the further development of related drugs should focus on and learn from some of the characteristics of dapansutrile. Firstly, dapansutrile has a very simple structure, and its molecular weight is around one hundred. The simple molecular structure allows dapansutrile to have satisfactory transmembrane ability, the excellent transmembrane ability provides the basis for dapansutrile to inhibit the intracellular inflammatory response. Secondly, dapansutrile has good absorption, which can effectively improve drug utilization and reduce drug dosage, thus reducing drug side effects. Based on the good absorption properties, dapansutrile is currently being developed for oral administration. Finally, the clear and reliable biosafety proof is the biggest advantage of dapansutrile. The development and improvement of any related drug must be based on the principle that there is no or minimal biological toxicity.The summary of the mechanisms analysis of dapansutrile in the treatment of gouty arthritis is shown in Graphical Abstract.This study explored the pharmacological mechanism of dapansutrile in the treatment of gouty arthritis by molecular docking and molecular dynamics simulation based on molecular system movement. This study found that Dapansutrile may not only directly inhibit NLRP3 to reduce the inflammatory response and pyroptosis, but also hinder the chemotaxis and activation of inflammatory cells by regulating IL1B, IL6, IL17A, IL18, MMP3, CXCL8, and TNF.Therefore, Dapansutrile treats gouty arthritis by attenuating inflammatory response, inflammatory cell chemotaxis and extracellular matrix degradation by acting on multiple targets.


Multiple system and organ damage occurs with the continuous progression of primary Sjögren's syndrome (pSS), and the lack of specific drugs against this disease is a huge challenge. White peony (WP), a widely used traditional Chinese herb, has been confirmed to have a therapeutic value in pSS. However, the specific mechanisms of WP in the treatment of pSS are unknown.  The active ingredients and their targets in WP were searched on the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and disease-related targets were collected from GeneCards, Online Mendelian Inheritance in Man (OMIM), and the Therapeutic Target Database (TTD). The overlapping targets were acquired by taking the intersection. A protein-protein interaction (PPI) network was structured using the STRING database. A disease-drug-ingredient-target (D-D-I-T) network was built using Cytoscape software. By filtering twice, core targets were acquired. Gene Ontology (GO) and Kyoto Encyclopedia Gene and Genome (KEGG) pathway enrichment analysis were accompanied by R packages. Finally, molecular docking was used to verify the abovementioned results. γ, AKT1, CASP3, NOS3, and JUN. GO and KEGG analysis were used to elucidate pharmacological mechanisms, mainly acting in the AGE-RAGE signaling pathway. Molecular docking proved that paeoniflorin bound well with core targets.  In total, we screened 88 WP-related targets, 1480 pSS-related targets, and 32 overlapping targets. D-D-I-T Network analysis displayed six main active ingredients of WP, which played a significant therapeutic role in pSS. Further topological analysis selected seven core target genes, including IL-6, TNF, PPARγ may be a protective target gene. The main active ingredients of WP mainly played a therapeutic role via the AGE-RAGE signaling pathway. These findings provide a fundamental and theoretical basis for the clinical application of WP. Our study revealed that IL-6, TNF, AKT1, CASP3, NOS3, and JUN may be pathogenic target genes, and PPAR Primary Sjögren's syndrome (pSS) is a systemic autoimmune disease, and the majority of patients are female, aged approximately 50 years. The global incidence of pSS is 6.92 per 100,000 person-years, with a prevalence of 60.82 cases per 100,000 people . To dateRanunculaceae. Total glucosides of peony (TGP), extracted from RPA, consist of paeoniflorin (Pae), albiflorin, hydroxyl-paeoniflorin, benzoylpaeoniflorin, benzoyloxypeoniflorin, and others [Radix Paeoniae Alba (RPA), is also called white peony (WP) in China. As a traditional Chinese medicine, it is derived from the radix of Paeonia of d others . Pae is d others , 8. TGP d others . In addid others . Other rd others , 12, andd others , which md others , 12, 14.d others , which wNetwork pharmacology is a novel paradigm in drug discovery based on the rapid progress of interdisciplinary fields such as bioinformatics and systems biology . Moleculhttps://tcmspw.com/tcmsp.php). To obtain the main active ingredients with superior pharmacological properties based on ADME , two parameters were required: (1) oral bioavailability (OB) ≥ 30% and (2) drug-likeness (DL) ≥ 0.18 [https://www.uniprot.org/) under the condition of “Homo sapiens”. Disease-related target genes were downloaded and merged from the GeneCards database (https://www.genecards.org/), Online Mendelian Inheritance in Man (OMIM) (https://omim.org/search/advanced/geneMap) and the Therapeutic Target Database (TTD) using the keyword “Sjögren's Syndrome” [https://bioinfogp.cnb.csic.es/tools/venny/index.html).In order to verify that the intrinsic ingredients in TGP are valuable and to identify other new compounds, we searched the ingredients of WP on the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database  ≥ 0.18 . In addiyndrome” , 18. Thehttps://cnstring-db.org/cgi/input.pl) to predict interactions between the genes by setting the organism to “Homo sapiens”. Therefore, a PPI network graphic could be constructed, where nodes represented genes and edges represented gene-gene associations [The overlapping target genes were transferred into the STRING database  and converted into 3D structures using Chem3D software (version 20.0). Through energy minimization calculations, these structures were saved in the mol2 format [https://www.rcsb.org/). The AutoDockTools software (version 1.5.7) completed file format conversion to pdbqt format, and active pocket coordinates determination. The affinities between ligands and receptors were evaluated as docking energies by AutoDock Vina software (version 1.2.0). They were considered to bind well with each other when the docking energy was less than −5 kcal/mol [The 2D structures of the main active ingredients were downloaded from the PubChem database . They were 11alpha,12alpha-epoxy-3beta-23-dihydroxy-30-norolean-20-en-28,12beta-olide, paeoniflorgenone, -3, 17-dihydroxy-4, 4, 8, 10, 14-pentamethyl-2, 3, 5, 6, 7, 9-hexahydro-1H-cyclopenta(a)phenanthrene-15, 16-dione (DPHCD), lactiflorin, paeoniflorin, paeoniflorin_qt, albiflorin_qt, benzoyl paeoniflorin, mairin, beta-sitosterol, sitosterol, kaempferol, and (+)-catechin . Throughγ), RAC-alpha serine/threonine-protein kinase (AKT1), caspase-3 (CASP3), nitric-oxide synthase, endothelial (NOS3), and transcription factor AP-1 (JUN) are listed in The 32 overlapping target genes were imported into the STRING database and a PPI Network graphic was demonstrated . There wP value < 0.05). The top 20 GO items and top 20 KEGG pathways are shown in The biological functions and potential therapeutic mechanisms of the target genes were acquired via GO and KEGG enrichment analysis , cellular component (CC), and molecular function (MF). In total, 1089 items in BP, the targets mainly enriched in response to lipopolysaccharide, response to molecules of bacterial origin, regulation of smooth muscle cell proliferation, and others. Five items in CC mainly included membrane raft and membrane microdomain. Sixty items in MF mainly included cytokine receptor binding, R-SMAD binding, TNF receptor superfamily binding, and others. A total of 96 pathways were found, and many were closely related to pSS, such as the Advanced Glycation End Product-Receptor for AGE (AGE-RAGE) signaling pathway, TNF signaling pathway, IL-17 signaling pathway, apoptosis, etc. Furthermore, the associated target genes of the AGE-RAGE signaling pathway are presented in detail in The top three key compounds  were selected to dock to seven core target genes in turn and their docking energies were calculated . Lower dYin deficiency, dryness, and heat in the body are viewed as pathological mechanisms of pSS, while body fluid deficiency, qi-stagnation, blood stasis, and phlegmatic hygrosis are viewed as manifestations of pSS in traditional Chinese medicine . WP is tκB activation, and leads to the generation of proinflammatory cytokines, the presence of oxidative stress and the maintenance of a sustained inflammatory state [κB, resulting in a vicious cycle of dysregulated inflammatory responses.We attempted to preliminarily investigate the possible pharmacological mechanisms of WP in treating pSS using network pharmacology and molecular docking. As shown by KEGG pathway analysis, the therapeutic targets are mainly enriched in AGE-RAGE, TNF, IL-17, Toll-like receptor, the c-type lectin-like receptor signaling pathway, and apoptosis, of which the most important is the AGE-RAGE signaling pathway. Advanced glycation end (AGE) products are the final products of nonenzymatic glycation and protein oxidation, and the level of these products has been found to increase in many autoimmune diseases, including SLE, severe psoriasis, and RA. In the AGE-RAGE signaling pathway, AGE, by binding with the multiligand receptor RAGE, transduces signals via several pathways: JAK2-STAT1, PI3K-AKT, MAPK-ERK, and NADPH oxidase-ROS, consequently resulting in NF-ry state , 27. A pry state . Aota etry state . Similarry state . In addiκB, PI3K-Akt-TOR, and JAK2-STAT3 signaling pathways [2+ concentration through endogenous release in salivary gland cells, which may promote salivation [κB pathway was inhibited, leading to a decrease in the release of inflammatory cytokines [κB pathways, which has been verified by in vitro experiments [Based on the D-D-I-P network, we eventually found that six key active ingredients, including Pae, (+)-catechin, kaempferol, sitosterol, beta-sitosterol, and DPHCD had therapeutic efficacy against pSS. The main ingredients interacting with core targets were Pae, kaempferol, and beta-sitosterol. Pae, considered a principal component of TGP, has been extensively studied. There is no uniform preparation process for TGP capsules in pharmaceutical companies, which leads to the production of specific compounds which are different; however, Pae accounts for at least 40% of TGP . It inflpathways , 31. Thepathways . Thus, Plivation . The stuytokines . In a raytokines . Furtherγ, AKT1, CASP3, NOS3, and JUN were viewed as core targets. IL-6 takes part in the progression of inflammation and immunity. Previously named cell stimulatory factor 2 (BSF-2), IL-6 performs an important function by inducing B-cell differentiation into plasma cells, leading to autoantibody production and hypergammaglobulinemia. In addition, IL-6 promotes the differentiation of naïve CD4+ T cells, linking the innate immune response to the acquired immune response [α signaling can contribute to autoimmune diseases. The serum level of TNF-α is elevated in SS patients [α blocker had an antiapoptotic effect on human salivary gland epithelial cells which is a significant pathological environment for SS [κB and MAPK pathway [γ has anti-inflammatory effects by degrading intrinsic NF-κB. Other aspects of PPARγ in immunity are that PPARγ can inhibit the expression of Th1 and Th2 cytokines to control the progression of SS in NOD mice and suppress the proliferation and differentiation of Th17 cells, which mainly release IL-17 [γ was strongly relevant to lacrimal gland dysfunction in dry eyes [According to the series of filters for overlapping targets, IL-6, TNF, PPARresponse . Moreno-response . Other sresponse . Furtherresponse . The inapatients . Other st for SS , and supt for SS . Akt, fut for SS , 49. Thet for SS , which i pathway . As a cy pathway . In expe pathway . CASP3 o pathway . NOS3 (a pathway . With re pathway , 57. Difse IL-17 . Existindry eyes .α [γ and displayed an antiapoptotic effect by downregulating CASP3 and Bax. Kaempferol treatment reduced the expression of NOS3 and TNF-α, which mainly modulated the NF-κB and MAPK pathways in a rat model [Experimental evidence suggests that Pae can suppress the release of inflammatory cytokines, such as IL-6 and TNF-α . Furtherα . Lu et aα  revealedat model . Beta-siAs a result, molecular docking reflected a strong affinity between three key ingredients of WP and seven core target genes. Our results describe the synergistic effects between ingredients and targets and emphasize the multicomponent, multipathway, and multitarget therapeutic mode of traditional Chinese medicine. However, our research also has certain limitations. What we predicted in theory, with the exception of DPHCD, can be supported more or less by existing research, but it is hoped that more in vivo or in vitro experiments can further strengthen our conclusions. In terms of DPHCD, which has been rarely studied, this compound may provide potential for the development of new drugs.γ seems to be a protective target gene during the process of pSS. These findings provide further evidence towards revealing the potential mechanism of WP in the treatment of pSS. Furthermore, they provide a reference for the development of new drugs directly and describe the pathological mechanism of pSS indirectly.In summary, WP has a significant advantage in the treatment of pSS, which is consistent with previous studies. Kaempferol, beta-sitosterol, and paeoniflorin in WP have therapeutic effects against pSS by inhibiting six targets, including IL-6, TNF, AKT1, CASP3, NOS3, and JUN through the AGE-RAGE, TNF, IL-17, and Toll-like receptor signaling pathways. PPAR