The aim of this study was to explore the potential biological mechanisms of coix seed in the treatment of colorectal cancer (CRC) based on network pharmacology analysis.  The active components of coix seed and their potential action targets were retrieved from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP). The disease targets related to CRC were obtained from the DisGeNET database. The intersection targets of the drug targets and disease targets were selected, and a component-target-disease network was built using Cytoscape 3.8.0 tool. A global network of the core target protein interactions was constructed using String database. Biological function analysis and pathway enrichment analysis of core targets were conducted to explore the potential.  A total of nine active components were obtained from the TCMSP database corresponding to 37 targets. Further analysis showed that 18 overlapping targets were associated with CRC. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was conducted based on the 18 targets and 11 significantly enriched signaling pathways implicated in CRC were identified.  The multicomponent and multitarget characteristics of coix seed are preliminarily verified, and the potential biological mechanisms of coix seed in the treatment of CRC are predicted, which provides a theoretical basis for the experimental research. Incidence of CRC has been increasing yearly, and the patients are increasingly younger. Previous studies report that CRC disease is associated with factors such as genetics, lifestyle, and diet . The clihttps://old.tcmsp-e.com/index.php) [Data on the phytochemical composition of coix seed were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform  . Search https://www.uniprot.org/). A drug-target network was the established using the UniProt ID.The targets for the active components obtained in Section 1.1 were retrieved from the TCMSP database (Select “Related Targets” in TCMSP to obtain the corresponding targets to the active compounds of coix seed). The targets were verified using the UniProt database  by screening the genes related to CRC disease. Diseases was used as the search field, CRC was used as the search term, and Summary of Gene-Disease Associations was used as the range selection [https://bioinfogp.cnb.csic.es/tools/venny/). The core targets where drug targets overlapped with disease targets were selected for subsequent analyses.The targets implicated in CRC were retrieved from the DisGeNet database  for protein-protein interaction analysis to explore the role of target proteins in CRC. The protein data were used for construction of a PPI based on the component target-disease target network. Protein-protein interactions with an interaction score ≥0.40 were visualized.The main targets obtained were imported into the String protein interaction database  enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were applied to the target proteins. GO functional analysis was performed to explore the function of genes based on the molecular function (MF), biological process (BP), and cellular components (CC) categories [Based on the tegories .A total of 38 active components isolated from coix seed were retrieved from the TCM-SP database. Further analysis was conducted and 9 compounds with oral bioavailability (OB) ≥30% and drug likeness (DL) ≥0.18, such as sitosterol-alpha1, sitosterol, and mandenol were selected .The targets corresponding to the 9 active compounds were obtained from the TCMSP database. A total of 48 related targets were retrieved, which were verified using the UniProt database to obtain 37 targets and their related information. The target gene information of each component is shown in A total of 5473 genes related to CRC were retrieved from the GeneCards database. The drug target database of coix seed was compared with the corresponding disease target database of CRC using the Venny 2.1.0 tool. A total of 18 overlapping core targets were selected: PGR, NR3C2, NCOA2, ADH1C, RXRA, NCOA1, PTGS1, SLC6A2, ADRB2, AKR1B1, PLAU, LTA4H, CHRM3, ADRA1A, ADRA1B, GABRA1, CHRNA7, and PTGS2.A drug-component-target-disease network was established based on the component targets and the disease targets using Cytoscape 3.8.0 tool. The network comprised 22 nodes with 6 drug components and 18 core targets of diseases .A PPI network was established which comprised a total of 18 common target proteins in coix seed-CRC, forming 3 network units . The nodP < 0.05. The top 20 BP, MF, and CC terms screened based on adjusted P values were identified , cellular component (CC), and biological process (BP) categories were screened with threshold of Figures 5.P < 0.05  of CRC cells induced by TNF-α. Yang et al. [CHRNA7 gene is implicated in the occurrence of CRC. CHRNA7 is an important protein in Ca2+-dependent signaling pathways . PI3K/AKT plays an essential role in various cell activities such as cell proliferation, apoptosis, metabolism, and survival, which can activate NFkβ. [2+-PI3K-PIP3-AKT- is a key target signaling pathway of the activity of active components in coix seed for treatment of CRC. Zhou et al. [Core target proteins corresponding the active compounds in coix seed for CRC treatment including PGR, PTGS2, NCOA2, NCOA1, and CHRNA7 were identified through PPI Network analysis. Previous studies reported a significant correlation between low expression of PGR and poor prognosis of CRC patients . PTGS2 eg et al.  reportedte NFkβ.  The curru et al.  reportedin vivo and in vitro studies. Studies should be conducted to explore the expression profiles of genes and key targets through reverse transcription-polymerase chain reaction and western blot to further elucidate the mechanism of action of the compounds in coix seed.Network pharmacology and bioinformatics analyses were used to explore the effect of active compounds in coix seed in treatment of CRC disease. The findings showed that the main mechanism of action of coix seed is the regulation of chemical carcinogenesis-receptor activation pathway, targeting calcium signaling pathway, lipolysis in adipocytes, and cGMP-PKG signaling pathway. The results showed that CHRNA7, PGR, PTGS2, NCOA2, and NCOA1 may be the main targets of the active components in coix seed implicated in CRC treatment. This study provides important information to further understand the interaction mechanisms of active compounds and related targets. In addition, the findings provide a basis for further elucidating the molecular mechanism of traditional Chinese medicine compounds in CRC treatment. Network pharmacology technology only qualitatively predicts drug components and targets, and clear pharmacological effects need to be verified through animal experiments and even clinical trials. Network pharmacological approach has certain limitations, thus the results reported in this study should be further verified through


Premenstrual syndrome (PMS) is a common disorder that affects women of reproductive age. It is characterized by periodic mental and somatic symptoms such as irritability, depression, and breast pain during the luteal phase. Premenstrual dysphoric disorder (PMDD) is the most severe form of PMS. In recent years, the incidence of PMS/PMDD has been increasing year after year. However, due to the complex symptoms and ambiguous classification of PMS/PMDD, the limitations of present treatments, such as their poor efficacy rate, have become increasingly apparent. With its unique benefits such as syndrome differentiation and high cure rate, traditional Chinese medicine (TCM) has sparked new diagnosing and treating of PMS/PMDD. This study uses data mining methods, and statistical analysis revealed that Xiaoyao San and Chaihu Shugan San were the commonly used TCM to treat PMS/PMDD. A detailed investigation of regularly used single herbs revealed that most TCM is used as cold herbs that penetrate the liver meridian, with predominant bitter, sweet, and pungent flavors. The network pharmacology method analyzes the interactions between diseases, targets, and herbs. Meanwhile, the deep action targets and molecular mechanisms of 10 commonly used herbs for the treatment of PMS/PMDD are studied, revealing that it involves several ingredients, many targets, and different pathways. This interaction provides insight into the mechanism of action of TCM in the synergistic treatment of PMS/PMDD. It is now clear that we can begin treating PMS/PMDD with TCM using the target and mechanism revealed by the abovementioned findings in the future. This serves as an essential reference for future research and clinical application of TCM in the treatment of PMS/PMDD. Premenstrual syndrome (PMS) is a common disorder with an incidence between 30 and 40% among women of childbearing age, in which mental, physical, and behavioral abnormalities occur regularly during the luteal phase and subside or disappear after menstruation, particularly mental symptoms such as mental tension, irritability or depression, breast pain, and other mental symptoms . PremensBupleurum Chinensis DC and Radix Paeoniae Alba. At the same time, experimental animal research into the antidepressant mechanism of single drugs is also increasing. On the other hand, the existing network of pharmacological studies on the depression mechanism of action of commonly used single drugs such as Bupleurum Chinensis DC and Radix Paeoniae Alba has revealed that they primarily contain active ingredients such as β-sitosterol, sitosterol, and flavonoids, with the primary targets being ADRA2A, ESR1, ADRA1B, and SLC6A4  Literature contains complete and precise clinical prescriptions for various syndrome types of premenstrual syndrome/premenstrual dysphoric disorder and reports on the pharmacological mechanism of herbs commonly used in the treatment. (2) For the summary literature, (1) is taken as the standard. The original data are explored based on the references, and qualified data are collected. Exclusion criteria (1) relevant individual clinical cases; (2)those having unclear herb composition and insufficient clinical treatment data; and (3) clinical western medicine treatment and those inconsistent with the keywords.Raw Radix Paeoniae Alba” is uniformly standardized as “Radix Paeoniae Alba” and “Concocted Rhizoma Cyperi " standardized as “Rhizoma Cyperi.” The Chinese name, used part, English name, and Latin name of herbs are shown in Prescription screening and single herb name standardization: A total of 63 prescriptions were selected based on the inclusion and exclusion criteria. The names of the herbs appearing in prescriptions are standardized in the People’s Republic of China Pharmacopoeia (2020 edition) and the textbook “Traditional Chinese Medicine” of the 13th five-year Plan of higher Education in the Traditional Chinese Medicine Industry. “Data entry and analysis: the selected and standardized prescriptions are inputted into the Excel form. The two authors were responsible for validating the input data one by one to assure data mining accuracy. Statistics were built on the frequency of use, syndromes, and treatment associated with commonly used TCM prescriptions and Chinese patent medicines, ranked based on the frequency of occurrence of TCM in all prescriptions, and sorted out based on the nature, taste, and meridian tropism of commonly used herbs.http://tcmspw.com/tcmsp.php) (http://www.megabionet.org/tcmid/) was used to supplement the search for information on TCM (http://www.swisstargetprediction.ch/) and the SEA data database (https://sea.bkslab.org/). The duplicate targets were excluded. The Uniprot database (https://www.uniprot.org/) was used to standardize the target proteins in preparation for the subsequent construction of the herb–herb combination–active ingredient–disease target network. We used the TTD database (http://bidd.nus.edu.sg/group/cjttd/), the DrugBank database (https://go.drugbank.com/), and the DisGeNET database (https://www.disgenet.org/) to screen the disease targets by searching the keyword “Premenstrual Dysphoric Disorder” and “Premenstrual Syndrome” (https://www.uniprot.org/) was also used to standardize the target proteins.To collect the chemical constituents of a single medicine, we logged on to the TCMSP platform (msp.php) . The TCMn on TCM , lackingn on TCM  was usedn on TCM  was idenyndrome” , and theThe standardized active ingredient targets were compared with disease targets to obtain intersection targets, and then the intersection targets were compared with the respective targets of ten single herbs. According to the intersection targets contained in every single herb, the herbs containing common intersection targets were grouped into a group (the number of herbs contained in every combination ≥3 was included in the study), and a total of 17 combinations of herbs were obtained, See https://string-db.org/) was used to predict the interaction between target proteins. The target of joint prediction between herbs and disease was imported into the String database, and the study species “Homo sapiens” was selected to obtain the target protein interaction relationship (The String database (tionship .https://www.omicshare.com/tools/) online platform for high-throughput GENE function analysis to clarify the biological characteristics of the herb–herb combination, the active ingredients, and the disease intersection target and obtain the analysis results of biological processes (BP), cellular components (CC), and molecular function (MF) belonging to GO enrichment, we performed Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis for intersection targets. Then, we selected the option of “GO enrichment analysis” and “KEGG pathway analysis” separately in the platform and imported the intersection targets into the platform according to the requirements of sample files. Select “Homo sapiens (GRCH38.p13)" for version/species/type and keep the default options for other items. After submitting the analysis, the corresponding GO enrichment and KEGG pathway analysis results were obtained. (Using the GENE DENOVO (btained. .http://bioinformatics.psb.ugent.be/webtools/Venn/) based on their taste: group 1 , group 2 , and group 3 . The three sets of intersection targets were combined to obtain the intersection. The intersection target formed by this junction is the target shared by the ten Chinese medicines. The target data were imported into the GENE DENOVO platform for the KEGG pathway and GO enrichment analyses. The method of analysis is identical to that described previously.Due to a large number of different types of herbs that could not be selected simultaneously, herbs were classified into three categories  using the Venn diagram software , Wanfang database, China Science and Technology Journal Database (VIP), and PubMed database. Seventy-six and 30 literature reports were retrieved from the Wanfang and Wei Pu databases. 886 articles and 433 articles were obtained from the PubMed database. The Note Express document management software retrieved a total of 244 valid documents. Bupleurum Chinensis DC and Paeoniae Radix Alba and dispersing and collecting. The treatment approach is primarily focused on relieving liver depression and nourishing liver blood. The use of Gardenia jasminoides Ellis, Scutellaria baicalensis Georgi, and other heat-clearing and detoxifying herbs enhances the power of heat-clearing and eliminating fire. The clinically representative prescriptions include Danzhi Xiaoyao San and Longdan Xiegan Decoction to treat liver stagnation and clear the fire. The qi stagnation and blood stasis syndrome treatment use Semen persicae and Carthamus tinctorius. The primary blood-activating medications are generally compatible with Platycodon grandiflorus, Fructus aurantii, and other qi-invigorating medications. Blood circulation to alleviate blood stasis is combined with the circulation of qi to dissipate qi stagnation and blood stasis. The typical prescription is Xuefu Zhuyu Decoction. Rehmanniae Radix, Cornus Officinalis Sieb, Rhizoma Dioscoreae, Lycii Fructus, and other yin nourishing medicines are frequently utilized for Yin deficiency syndrome. Pinellia ternata, Rhizoma atractylodis Macrocephalae, and GasTCMLIBodiaelata Bl for phlegm-fire disturbance syndrome are used as expectorants.There were 21 common prescriptions and 52 self-made prescriptions identified for the treatment of PMS/PMDD, and the common prescriptions used in the clinical treatment of PMS/PMDD with a frequency ≧5, and their related treatment syndromes and treatment methods were compiled. Overall, the study discovered that Xiaoyao San, Chaihu-Shugan-San, Xuefu Zhuyu Decoction, and Danzhi Xiaoyao San are used more frequently to treat PMS/PMDD, with the frequency of use being 48, 34, 24, and 19 times, respectively. The treatment syndromes included liver qi stagnation, qi stagnation, blood stasis, liver stagnation to transform fire, etc. As shown in Paeoniae radix Alba, Rhizoma atractylodis Macrocephalae, and Rhizoma cyperi for YueqianShu Jian, which can relieve the liver and depression, while regulating qi and invigorating the spleen, successfully treating PMS disorders.This study highlights the most often used Chinese patent medications for the clinical treatment of PMS/PMDD (use frequency ≧2), the corresponding syndromes, and treatment techniques, as shown in Statistical analysis was performed on the properties, taste, and meridian status of herbs comprising the prescriptions in Bupleurum Chinensis DC, Radix Paeoniae Rubra, Rhizoma Cyperi, Rhizoma Atractylodis Macrocephalae, and so on rotundus corresponding saikosaponins, total glucosides of paeony, flavonoids, and volatile oils having the main pharmacological effects. The most critical pharmacological effects include antidepressants, immune enhancement, antiaging, anti-inflammatory and analgesic, and prevention of thrombosis. These benefits are achieved through various pharmacological pathways.The frequency of use, properties, main ingredients, and pharmacological effects of several single medicines regularly used in the treatment of PMS/PMDD is summarized, and a single-medicine with a frequency of use ≧40 was selected for further investigation. The active ingredients of ten types of single medications typically used in the treatment of PMS/PMDD were obtained using the TCMSP and TCMID databases, yielding 9,782 active ingredients. After screening and deleting duplicates, 105 active ingredients of herbs, including (+)-anomalin, beta-sitosterol, and ferulic acid (FA), were found using bioavailability OB ≥ 30% and drug similarity DL ≥ 0.18), as shown in Fructus Aurantii) includes AR, CHRM2, and other seven intersection targets, with the most significant number of intervention intersection targets , kinase inserts domain receptor (KDR), sex hormone-binding globulin (SHBG), anaplastic lymphoma kinase (ALK), ESR1, ESR2, and acetylcholine. p-values and more significant target enrichment. In BP analysis, the cellular processes, the metabolic processes, response to stimulus, biological regulations, etc., were all involved. Among them, the highly enriched target proteins are involved in cellular metabolism and stress response. The target proteins involved in cell, organelle, membrane, protein-containing complex, synapse, and other cell compositions were enriched in the CC type. In the MFs, the target proteins involved in binding, catalytic activity, molecular transducer activity, molecular function regulator, transcription regulator activity, and other molecular functions were highly enriched. The KEGG pathway analysis results yielded 114 pathways, mainly related to endocrine resistance (5%), pathways in cancer (9%), adherens junction (4%), EGFR tyrosine kinase inhibitor resistance (4%), proteoglycans in cancer (5%), estrogen signaling pathway (4%), focal adhesion (4%), and other pathways, as shown in As seen in In recent years, the incidence of PMS/PMDD has been on the rise. This condition has a significant impact on the body, psychology, and life of women of childbearing age. This condition has attracted much research attention worldwide. It is mainly treated using serotonin reuptake inhibitors (SSRIs) such as fluoxetine and sertraline. However, these drugs are not sufficiently active due to poor clinical differentiation of the disease. In addition, they are associated with side effects . TraditiRhizoma Chuanxiong, Rhizoma Cyperi, and Citrus aurantium L are incorporated in Sini San to improve the spleen and qi. It is used to diagnose and treat chest tightness, irritability, and flank caused by liver qi stagnation. The herbs in the prescription can soothe the liver, regulate qi, and relieve depression  (C16H12O6), another glycosylated kaempferol derivative, improves the expression of the brain-derived neurotrophic factor (BDNF) responsible for the formation of the neural networks and neuronal plasticity (On the other hand, we found several intersecting targets for PMS/PMDD intervention in the active ingredients stigmasterol, kaempferol, hyndarin, and other active ingredients. In Nasiara Karim’s study, stigmasterol may be a new steroid for treating neurological disorders through the regulation of GABA receptors . It was asticity . The exiasticity , We reasComprehensively analyzing the results of GO enrichment, the intersection targets involved a wide range of molecular functions, diverse biological processes, and rich cell composition. The study found that G protein–coupled receptor, adrenergic receptor, and their corresponding signaling pathways are related to PMS/PMDD, which is consistent with the current research results on the mechanism of PMS/PMDD. A preliminary experimental study has proven that the occurrence and development of PMS/PMDD are closely related to the function of the ion channel coupled with GABAB receptor G protein and the conduction disorder of the signal pathway . Qiao de2+ concentration and Cav1.2 increase in current density induced by KCl. In addition, it showed beneficial effects against affective disorders by regulating Cav1.2 through the CaM/CaMKII pathway (According to the KEGG pathway analysis, we found that TCM can treat PMS/PMDD by regulating the neuroactive ligand–receptor interaction, calcium signaling pathway, and other signaling pathways. Previously, it was found that Baixiangdan capsules improved PMS/PMDD symptoms by regulating signal pathways such as neuroactive ligand–receptor interactions, mitogen-activated protein kinase, calcium, and gamma-aminobutyric acid signal transduction . Elsewhe pathway . The aboWe used the Venn diagram tool to analyze the ten herb targets for PMS/PMDD treatment. A total of 27 common targets such as PFKFB3, CES2, and KDR were obtained. Subsequently, the KEGG pathway analysis was performed on these targets, which identified 27 common targets . Among tIn summary, the pathogenesis of PMS/PMDD is complicated. TCM treatment can adjust the treatment focus through the compatibility of TCM or the changes in the taste and quantity of the herb to better treat different syndromes or concurrent syndromes of the same syndrome. TCM has shown to be flexible and accurate in application than Western medicine. In addition, TCM is safer, has fewer side effects, and has high clinical significance. However, it is worth noting that there is no unified approach to differentiate PMS/PMDD in TCM. Research on the antidepressant effects of TCM prescriptions and single herbs has not achieved much attention. Therefore, advanced methods based on systematic analysis should be adopted in future studies to improve the application of TCM in PMS/PMDD.


Panax ginseng C.A. Mey) is a kind of perennial herb of the Panax genus in the Araliaceae family. The secondary metabolites of mountain-cultivated ginseng (MCG) and garden ginseng (GG) vary greatly due to their different growth environments. To date, the differences in their pharmacological effects on cardiovascular diseases (CVDs) and their clinical applications remain unclear. To distinguish between the components of MCG and GG, ultra-high-performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry (UPLC-Q-TOF/MS) was performed. Next, the relationship between the expression of metabolites and the categories of the sample were analyzed using supervised partial least squares discriminant analysis and orthogonal partial least squares discriminant analysis. A network-based pharmacology approach was developed and applied to determine the underlying mechanism of different metabolites in CVD. In the present study, the role of MCG and GG in angiogenesis and their protective effects on damaged blood vessels in a vascular injury model of zebrafish were investigated. Using UPLC-Q-TOF/MS, 11 different metabolites between MCG and GG were identified. In addition, 149 common target genes associated with the metabolites and CVD were obtained; these targets were related to tumor protein P53, proto-oncogene tyrosine-protein kinase Src, human ubiquitin-52 amino acid fusion protein, ubiquitin-40S ribosomal protein S27a, polyubiquitin B, signal transducer and activator of transcription 3, isocitrate dehydrogenase 1, vascular endothelial growth factor A, glycose synthase kinase-3B, and coagulation factor II and were associated with the regulation of the phosphoinositide 3-kinase-Akt signaling pathway, the tumor necrosis factor signaling pathway, and the hypoxia-inducible factor-1 (HIF-1) signaling pathway, which play important roles in the curative effect in CVD treatment. Both types of ginseng can promote the growth of the subintestinal vessel plexus and protect injured intersegmental vessels through the HIF-1α/vascular endothelial growth factor signaling pathway in a dose-dependent manner. In addition, MCG has a stronger impact than GG. This is the first time metabolomics and network pharmacology methods were combined to study the difference between MCG and GG on CVDs, which provides a significant theoretical basis for the clinical treatment of CVD with two kinds of ginseng.Ginseng ( Panax ginseng C.A. Mey) has been used for the treatment of various ailments for the past 2000 years and is considered the “king of herbs”  and GG  were obtained from Huanren Liaoning, China. All samples were provided by Shanghai SPH Shen Xiang Health Medicine Co., Ltd. and were identified by Professor Yuexiong Li. After the addition of 50 mg of MCG and GG powder to 75% cold methanol solution and crushing at low temperature with a high flux crushing instrument, the mixtures were extracted using ultrasonics for 30 min at 4°C. The solution was then centrifuged at 13,000 × g for 15 min at 4°C to obtain the supernatant. At last, the supernatant was filtered using a 0.22-μm filter membrane and injected directly into the ultra-high-performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry (UPLC-Q-TOF/MS) system for analysis.The samples of MCG . Separation was achieved using the following gradient: 5% B—25% B—25% B—100% B—1.5–10.0 min, 100% B—100% B—10.0–13.0 min; 100% B—5% B—13.0–13.5 min and 13.5–14.5 min, holding at 5% B at a flow rate of 0.40 ml/min, where B was acetonitrile (0.1% (v/v) formic acid) and A was aqueous formic acid (0.1% (v/v) formic acid) in the positive ion mode and B was acetonitrile (containing 5 mM ammonium formate) and A was water (containing 5 mM ammonium formate) in the negative ion mode. The injection volume was 3 μL, and the column temperature was set at 45.0°C. The mass spectrometric data were collected using an LTQ Orbitrap mass spectrometer equipped with an electrospray ionization source operating in either positive or negative ion mode. The capillary and source temperatures were set at 350°C, with a desolvation gas flow of 45 L/h. Centroid data were collected from 50 to 1,000 m/z with a resolution of 30,000. The data were analyzed using QI software.http://lsp.nwu.edu.cn/tcmsp.php), SymMap database (http://www.symmap.org/), Encyclopedia of Traditional Chinese Medicine database (http://www.nrc.ac.cn:9090/ETCM/), and TCM-MESH database (http://mesh.tcm.microbioinformatics.org/). For the components that were not included in these databases, the Swiss Target Prediction (http://swisstargetprediction.ch/) and STITCH (http://stitch.embl.de/) databases were applied to predict the targets according to the chemical similarity. DrugBank (https://www.drugbank.ca/) and HGDB (http://www.hgdb.ir/Default1.aspx) databases were used to collect CVD targets. A Venn diagram of the overlapping relationship among the targets, the “components-targets” network, and the protein–protein interaction (PPI) network was established.The different ingredients between MCG and GG were imported into the Traditional Chinese Medicine Systems Pharmacology database  and strong binding activity (binding score < 9) were defined.The key proteins were placed in the database for annotation, visualization and integrated discovery (DAVID) 6.8 for Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. The KEGG database could identify functions at a higher level and the biological information resources that interact with them at the genomic and molecular levels. The results of the enrichment analysis of the study were selected at 2HPO4·12H2O, and KH2PO4 were purchased from Sinopharm . XueSaiTong (XST) was obtained from TeAnNa . Trizol was obtained from Invitrogen . Analytical-grade methanol, acetonitrile, and formic acid were purchased from Merck .The vatalanib dihydrochloride PTK787 was obtained from Selleck Chemicals . Methyl sulfoxide, HCl, glycerin, sodium dodecyl sulfate, NaCl, KCl, NaThe transgenic zebrafish line Tg (fli1a: EGFP) y1 was obtained from China Zebrafish Resource Center , and enhanced green fluorescent protein–expressed endothelial cells were used for angiogenesis observations. The zebrafish were maintained with a 14/10 h light–dark cycle and were fed brine shrimp twice a day. The zebrafish embryos were produced by natural pairing and were incubated in an embryo culture medium at 28.5°C.Panax notoginseng [(Burkill) F. H. Chen] was used as the positive control group. At least six embryos were analyzed in each group, and the experiments were replicated three times.Healthy embryos that developed 24 h after fertilization (hpf) were collected and treated with various concentrations of MCG and GG  for 48 h, and the number of sprouted and crossed vessels of the subintestinal vessel plexus (SIV) was counted in each zebrafish embryo. A stereoscopic fluorescence microscope  was used for observation of the growth of SIVs. The embryos at 21 hpf were pretreated with 0.2 μg/ml PTK787 (VEGF receptor inhibitor) for 3 h and then treated with various concentrations of MCG and GG  for 48 h. The elongation of intersegmental vessels (ISVs) from the dorsal aorta to the dorsal longitudinal anastomosis was observed, and the length of ISVs of each embryo was measured. XST, which mainly comprised saponins extracted from −ΔΔCt relative quantification method. The primer sequences that were used are presented in Each zebrafish embryo sample was collected in three replicates with 50 embryos per group. Total RNA was extracted using the Trizol extraction kit, and cDNA was synthesized from total RNA using the EVO M-MLV RT kit . The cDNA was diluted 10 times before RT-PCR analysis. Quantitative analysis of the mRNA of vascular endothelial growth factor receptor 2 (VEGFR2), hypoxia-inducible factor-1α (HIF-1α), interleukin-6 (IL-6), interleukin-1β (IL-1β), tumor necrosis factor-α (TNF-α), and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was performed using the Light Cycle 96 Real-Time PCR platform, and each gene was normalized to the internal control gene GAPDH. The results were analyzed using the 2p < 0.05 was considered statistically significant.All data were analyzed using GraphPad Prism 8.0 and are presented as the mean ± standard error of the mean. Two-sided unpaired Student’s t-test and one-way analysis of variance (ANOVA), followed by the Holm–Sidak test, were used to determine the difference between two independent samples and more than two independent samples, respectively. Comparisons between groups were analyzed using a two-way ANOVA, followed by Bonferroni’s post-hoc multiple comparison test. The correlations were calculated using Pearson correlation analysis. 2 > 0.5 proves that the model is reasonable and effective, and can be used for data analysis   . Based on the above analysis , 11 different metabolites were analyzed  . Orthogo= 0.927) . The impanalyzed .A total of 243 targets for different compounds were obtained; the DrugBank and HGDB databases were used to identify 4382 CVD-related targets, and the UniProt database was used to collect the gene names of all targets. In addition, the null and repetitive targets were removed. All compound targets were assigned to CVD target genes to obtain 149 common target genes .The “Components-targets” network was then constructed to determine the interaction between components and targets. This network contained 197 nodes and 291 edges; the more edges a component or target had, the more important they were in this network. The network showed that citric acid, ginsenoside Rg3, and ginsenoside Re might be the most important components between MCG and GG in CVD . The topp < 0.05, which served as a threshold, including the phosphoinositide 3-kinase (PI3K)-Akt signaling pathway, TNF signaling pathway, insulin resistance mechanism, and HIF-1 signaling pathway. The pathway with the most enriched genes was the PI3K-Akt signaling pathway, which interacted with 15 genes; VEGFA is an important protein factor in this signaling pathway.KEGG enrichment analysis results are shown in VEGFA is a homologous dimer vasoactive glycoprotein and a key mediator of angiogenesis and vessel permeability . ResearcThe active ingredients of ginsenosides Rg3, Re, B2, and C and the key genes of TP53, STAT3, NOS2, and TNF were selected. Molecular docking results showed that different compounds had a good binding ability to key genes, and the results from the network pharmacology screening were also directly verified by molecular docking. Part of the docking process is shown in The tolerance of zebrafish embryos to MCG and GG is depicted in The embryos were pretreated with PTK787 to establish the faulty angiogenesis model. PTK787 is a type of VEGF receptor inhibitor. The ISVs in zebrafish in the control group grew well without injury and were present in a uniform, longitudinal equidistant manner; however, the ISVs in the zebrafish in the PTK787 group eventually disappeared and were damaged . MCG andUsing network pharmacological analysis, the hypotheses of these potential targets and signaling pathways were confirmed and the molecular mechanism of the proangiogenesis effect of MCG and GG was predicted, which suggested the strong association between the proangiogenesis effect of MCG and GG and the PI3K/AKT and HIF-1α/VEGF signaling pathways and inflammatory factors. The RT-PCR results revealed that compared with the control group, PTK787 treatment significantly decreased the HIF-1α and VEGF levels and increased the TNF-α, IL-1β, and IL-6 levels, whereas compared with the PTK787-treated group, MCG and GG treatment significantly increased the HIF-1α and VEGF mRNA expression and decreased the TNF-α, IL-1β, and IL-6 expression . In addiMultiple studies have shown that ginseng has several pharmacological benefits, including the prevention and treatment of CVD, as well as a wide range of clinical applications. The secondary metabolites of MCG and GG differ due to the differences in the growth environment, resulting in differences in the pharmacological actions of the two types of ginseng. Therefore, it is of great clinical significance to explore the differences in the pharmacological effects of MCG and GG.In this study, the pharmacological effects of MCG and GG on vascular growth, which can increase angiogenesis, help minimize the extent of myocardial infarction, and protect the ischemic myocardium, were studied using zebrafish as a model animal. Both types of ginseng had no effect on the survival rate and heart rate of zebrafish embryos, indicating low toxicity and cardiotoxicity. MCG and GG improved the number of sprouting and crossing vessels in zebrafish SIVs, with MCG having a much greater effect than GG. Likewise, both types of ginseng could protect damaged ISVs, with MCG having a substantially greater effect than GG and MCG having a vascular growth rate of 73% at 100 g/ml. Taken together, our present study showed that MCG and GG have the bioactivity to promote angiogenesis in a pathophysiological state, and MCG has significant efficacy in the recovery of blood vessel loss.Several studies on the identification of ginseng and the determination of the ginsenoside content have recently been published; however, there have been few investigations on the differences in medicinal components between MCG and GG. Ginsenoside Rg3, ginsenoside Re, ginsenoside B2, ginsenoside C, L-phenylalanine, and ginsenoside M7cd expression levels were shown to be higher in MCG than in GG. Meanwhile, 1-palmitoyl lysophosphatidic acid, ginsenoside F5, citric acid, N2-acetyl-L-ornithine, and notoginsenoside Fa expression levels were lower in MCG than in GG, with 1-palmitoyl lysophosphatidic acid being the most significantly differentiated secondary metabolite, which was important for the identification of 1-palmitoyl lysophosphatidic acid as a quality marker of ginseng. The protective effects of ginsenoside Rg3  on the cMCG has been growing in the wild for over 15 years; its shape, color, fragrance, taste, and other characteristics are outstanding, and it has substantial medical significance in clinical applications. Ginseng has been used in the treatment of CVDs such as heart failure and coronary atherosclerotic heart disease in clinical trials. Some medicine has been widely used in the treatment of CVD, such as Rinchen Decoction and Shenfu Decoction; however, the differences in the pharmacological effects of MCG and GG in the treatment of CVD remain largely undetermined. VEGF is an important signal protein involved in angiogenesis and endothelial cell growth, thereby promoting the function of angiogenesis. VEGF can specifically bind to its corresponding receptor (VEGFR) and stimulate the proliferation of vascular endothelial cells, promoting the formation of collateral vessels. HIF-1  is a keyIn conclusion, we used plant metabolomics and network pharmacology to determine the angiogenic activity of MCG and GG. Based on the results of the zebrafish experiments, both MCG and GG can reduce inflammation and promote angiogenesis via the HIF-1α/VEGF pathway. Our findings showed that MCG has a higher metabolite content than GG and that these metabolites enhanced angiogenesis and had stronger pharmacological activity in CVD than those of GG. The accuracy of the predicted findings will be improved using our proposed method, which used experimentally determined constituents and their matching targets. The current work was the first to integrate metabolomics with zebrafish experiments to investigate the effects of MCG and GG on CVD, providing some theoretical support for clinical treatment.


The ‘glycoEnzymes’ include a set of proteins having related enzymatic, metabolic, transport, structural and cofactor functions. Currently, there is no established ontology to describe glycoEnzyme properties and to relate them to glycan biosynthesis pathways.We present GlycoEnzOnto, an ontology describing 403 human glycoEnzymes curated along 139 glycosylation pathways, 134 molecular functions and 22 cellular compartments. The pathways described regulate nucleotide-sugar metabolism, glycosyl-substrate/donor transport, glycan biosynthesis and degradation. The role of each enzyme in the glycosylation initiation, elongation/branching and capping/termination phases is described. IUPAC linear strings present systematic human/machine-readable descriptions of individual reaction steps and enable automated knowledge-based curation of biochemical networks. All GlycoEnzOnto knowledge is integrated with the Gene Ontology biological processes. GlycoEnzOnto enables improved transcript overrepresentation analyses and glycosylation pathway identification compared to other available schema, e.g. KEGG and Reactome. Overall, GlycoEnzOnto represents a holistic glycoinformatics resource for systems-level analyses.https://github.com/neel-lab/GlycoEnzOnto.Bioinformatics online. Glycosylation results in the biosynthesis of complex carbohydrates or glycans on the cell-surface and nuclear proteins, and lipids . During Systems-based bioinformatics analyses of glycosylation require formalized knowledge, including ontologies. Among these, GlycoRDF and Glycoconjugate Ontology (GlycoCo) help harmonize glycan structural data from various glycoscience databases  describeThis manuscript presents GlycoEnzOnto, a manually curated ontology that captures current biological knowledge regarding 403 human GlycoEnzymes and demonstrates its applications in bioinformatics data analyses. These glycoEnzymes are annotated into 139 glycosylation pathway classes, 134 molecular functions and 22 cellular compartments, similar to the organization of the Gene Ontology (GO)  based on existing biological knowledge . Such reFive ‘reaction types’ were described in the reaction rule strings, with curly braces used to enclose monosaccharides or substituents that are being transformed . Such trGlycoEnzymes exhibit group-specificity, necessitating the need to describe ‘substrate ambiguity’ to encode structurally similar/equivalent entities. To describe this, ‘?’ is used to depict uncertain substrate bond linkages. Angle brackets (‘<>’) enclose one or more sub-structures that may or may not be part of a given substrate. The continuation symbol (‘…’) indicates the presence of one monosaccharide or arbitrary glycan sub-structure. If present at the non-reducing terminal, this is used to indicate an internal reaction site. When included in the middle of the substrate, this is to shorten the structure presentation in order to reduce text and focus on more critical features. Examples of continuity operator usage are presented in ‘Substrate combination’ using logical operations enables more complex substrate definitions. For example, the logical ‘AND’ or ‘&’ symbol is used to indicate the presence of multiple, critical epitopes in a single substrate. The presence of multiple reactive substrates/epitopes is described using the logical ‘OR’ . Here, the presence of either groups would make the substrate reactive. Finally, ‘&&’ is used to facilitate the description of bimolecular reactions, as this enables embedding multiple reactants/products in a single biochemical reaction.‘Reaction constraints’ limit specific reaction types. Here, the logical ‘NOT’ or ‘!’ operator specifies glycan structure or sub-structures that prevent biochemical transformation. The number of allowed repeating structures/monosaccharides in a reactive substrate is defined using the symbol ‘n’. The ‘@’ operand is used to restrict the formation of specific products, and this is often used in conjunction with the logical NOT operator. For instance, β1-4 galactosyltransferases  can act on any terminal GlcNAc, except for bisecting GlcNAc of N-linked glycans. The constraint ‘!@GlcNAc(b1-4)[…]Man(b1-4)’ is used to describe this property. Overall, The ability of GlycoEnzOnto to distill differential expression in an overrepresentation analysis was compared to Reactome, GO and KEGG glycosylation pathway descriptions . To this+ breast cancer patients was compared to 113 normal tissue samples. The differential expression analysis was performed by fitting a linear mixed model in the DREAM package fucosyltransferase FUT4 as an example . Here, tGlycoEnzOnto presents the classification of 403 glycoEnzymes based on molecular function, pathway and compartment . Figure The glycan precursor formed during the ‘initiation’ step may be further modified during ‘elongation and branching’. This results in increased carbohydrate size. The subclasses in this group include the genes regulating the biosynthesis of (i) ‘Type-I/-II/-III LacNAc’ structures, (ii) ‘LacDiNAc’ chains, (iii) (β1-6)GclNAc branches and (iv) glycosaminoglycan polymerization . In the final ‘capping’ step, the glycoEnzymes generate modifications that preclude further chain extension, commonly using the sialyltransferases and fucosyltransferases. This often results in the biosynthesis of named carbohydrate epitopes, such as sialyl Lewis-X, blood group antigens and HNK-1.‘Compartments’ are curated for each of the GlycoEnzymes . Supportin silico glycosylation pathway generation for various glycoconjugate types Gal(β1-3)GalNAcα) and sialyl-Tn (Neu5Ac(α2-6)GalNAcα) type glycans that have been reported to be augmented during breast cancer  lactosylceramide synthesis, (ii) O-GalNAc glycosylation and (iii) glycan capping . KEGG anSeveral resources curate glycosylation-related protein functions and pathways including Reactome , GO Ash. AdditioGlycoEnzOnto curates reaction rules for 403 glycoEnzymes using linear strings that are derived from IUPAC-condensed nomenclature. This schema includes three critical components that describe: (i) enzyme-specific substrates and related substrate ambiguity; (ii) five types of biochemical reactions relevant to glycobiology; and (iii) reaction constraints that limits the nature of substrate transformation. The ability to parse the rules and constraints efficiently to generate a glycosylation reaction network was demonstrated for the case of N-linked glycosylation. The scope of this endeavor may be extended to other glycoconjugate types. The ability to automate the generation of glycosylation reaction networks allows the simulation of biochemical reaction networks and fitting with glycan structure experimental data (in vivo.The new ontology enables overexpression analysis by taking advantage of the classification of the glycoEnzymes into various molecular functions and biological processes. We illustrate this using a breast cancer example that helps discover a broad range of potential cancer-associated dysregulated pathways. During such analysis, the GlycoEnzOnto pathway hierarchy enabled more a nuanced identification of dysregulated pathways compared to GO, KEGG and Reactome. While a single test case is presented here for the purpose of illustration, a larger analysis of all 33 cancer types reported in TCGA and their relation to glycan dysregulation will follow shortly. Thus, the proposed method is designed to generate precise glycoscience hypotheses using gene expression data that may be tested in a wet-lab setting. It also aims to use mathematical analyses to uncover glycoEnzyme relationships within cells that cannot be readily measured The availability of GlycoEnzyme biochemical knowledge in OWL format using GlycoEnzOnto can allow the integration of glycoEnzyme knowledge into glycan structure databases, along with additional information, e.g. transcription factor binding sites and other gene regulatory properties (btac704_Supplementary_DataClick here for additional data file.


Mucosa associated lymphoid tissue (MALT) lymphoma of the orbit is rare, often indolent, but can recur, and spread to extra‐nodal sites. Pleural and retroperitoneum recurrences of MALT lymphoma are rare.A 65‐year‐old man was referred to our hospital due to right pleural effusion and difficulty in breathing. He had a medical history of having undergone surgery for MALT lymphoma of the left orbit. A chest computed tomography (CT) scan showed right pleural thickness, pleural effusion, and a retroperitoneal mass, spreading from the muscular layer to the subcutaneous layer. The thickened pleural lesion was surgically biopsied and diagnosed as a recurrence of MALT lymphoma.Pleural effusion should be carefully examined and monitored for the possibility of recurrence in MALT lymphoma patients. His right lung breath sounds were diminished. He had a medical history of surgery for MALT lymphoma of the left orbit at a previous hospital in 2009. Six years after the surgery, the patient experienced MALT lymphoma recurrence in the right orbit. Thus, he underwent surgical resection for recurrent lymphoma. He was given no other treatment than surgery in 2009 and 2015. Meanwhile, a retroperitoneal mass measuring 32 x 7 mm in size was detected on computed tomography (CT) in 2015. He discontinued his visits to the initial hospital and was not followed up. Eleven years after the initial diagnosis of MALT lymphoma, he visited our hospital because of dyspnea and massive pleural effusion Figure . Laborat3This was a case of MALT lymphoma with metachronous recurrence in the right pleura, retroperitoneum, and orbit. MALT lymphoma is a low‐grade lymphoma of the B‐cell type that originates from lymphoid tissue found in association with mucous membranes and glands and accounts for 7%–8% of non‐Hodgkin's lymphomas.d‐glucose. Though, chromosomal abnormalities of the lymphoma cells were not detectable in this case, the diagnosis of MALT lymphoma is generally aided not only by the clinical picture, histological examination, cytomorphological, and immunophenotypic features, but also by cytogenetic features.There are various reports on the usefulness of positron emission tomography (PET) in MALT lymphoma, and sensitivity and specificity vary from organ to organ.MALT lymphoma comprises 50%–78% of ocular adnexal lymphomas in Western countries, and 80%–90% in Japan and Korea.Approximately 16% of non‐Hodgkin's lymphoma patients have pleural lesions or develop pleural involvement during the course of their disease.pylori eradication, reportedly developed pleural recurrence 1 year later.Moreover, pleural recurrence resulting from MALT lymphoma is rare. Only one case of pleural recurrence of gastric MALT lymphoma has been reported. A gastric MALT lymphoma patient, who underwent Helicobacter In conclusion, the present case focused on the diagnostic challenges in evaluating pleural thickness and the occurrence of a metachronous recurrence from MALT lymphoma. Therefore, pleural effusion should be carefully examined and monitored for recurrence in MALT lymphoma patients. Physicians should be alert to the possibility of recurrence in patients with past history of MALT lymphoma.Conceptualization and methodology, A.S. and H.I.; Project administration, visualization, and writing—original draft preparation, A.S. and H.I.; Supervision, T.S., N.T., K.K., K.K., and H.K.; Investigation and resources, R.T., R.A., O.Y., K.H., E.N., H.I., Y.M., and A.M.; Writing —review and editing, All authors. All authors read and approved the final manuscript.The authors declare no conflict of interest.The article adhered to the principles outlined in the Declaration of Helsinki.


Hawthorn leaves, which is a traditional Chinese medicine (TCM), has been used for treating coronary heart disease (CHD) for a long time in China. But the limited understanding of the main active components and molecular mechanisms of this traditional medicine has restricted its application and further research. The active compounds of hawthorn leaves were obtained from TCMSP database and SymMap database. The targets of it were predicted based on TCMSP, PubChem, Swiss Target Prediction, and SymMap database. The putative targets of CHD were gathered from multi-sources databases including the Online Mendelian Inheritance in Man (OMIM) database, the DrugBank database, the GeneCards database and the DisGeNet database. Network topology analysis, GO and KEGG pathway enrichment analyses were performed to select the key targets and pathways. Molecular docking was performed to demonstrate the binding capacity of the key compounds to the predicted targets. Furthermore, RAW264.7 cells stimulated by lipopolysaccharides (LPS) were treated with three effective compounds of hawthorn leaves to assess reliability of prediction. Quercetin, isorhamnetin and kaempferol were main active compounds in hawthorn leaves. Forty four candidate therapeutic targets were identified to be involved in protection of hawthorn leaves against CHD. Additionally, the effective compounds of it had good binding affinities to PTGS2, EGFR, and MMP2. Enrichment analyses suggested that immune inflammation related biological processes and pathways were possibly the potential mechanism. Besides, we found that three predicted effective compounds of hawthorn leaves decreased protein expression of PTGS2, MMP2, MMP9, IL6, IL1B, TNFα and inhibited activation of macrophage. In summary, the present study demonstrates that quercetin, kaempferol and isorhamnetin are proved to be the main effective compounds of hawthorn leaves in treatment of CHD, possibly by suppressing expression of PTGS2, MMP2, MMP9, inflammatory cytokines and macrophages viability. This study provides a new understanding of the active components and mechanisms of hawthorn leaves treating CHD from the perspective of network pharmacology. Coronary heart disease (CHD), one of the leading causes of human death in the world, is characterized by atherosclerosis of the coronary arteries, narrowing or occluding the vascular lumen, leading to myocardial ischemia, hypoxia or necrosis . CoronarTraditional Chinese Medicine (TCM) has been used for ages to treat a variety of diseases including CHD and its related diseases. The diversity of components and mechanisms of action is an important feature of TCM . HawthorNetwork pharmacology is an important tool to explore the active components and action mechanism of TCM. It analyzes the mechanisms of action of drugs from a systematic and comprehensive perspective . So far,In this study, approaches based on network pharmacology were used to investigate underlying mechanism of action of hawthorn leaves in treatment of CHD. The purpose of this study was to explore main active components and possible mechanisms of hawthorn leaves in the treatment of CHD from the perspective of network biology.1 ] in hawthorn leaves were determined. All compounds with oral bioavailability (OB) ≥ 30 % and drug-likeness (DL) ≥ 0.18 were retrieved for subsequent research. OB is a pharmacokinetic parameter, representing the relative amount of a drug absorbed into the systemic circulation after oral administration. DL is a qualitative characteristic used to evaluate the possibility of converting a compound into a drug.The Traditional Chinese Medicine Systems Pharmacology Database (TCMSP)1  and SymM3 the Swiss Target Prediction database (4 and the SymMap Databases (see text footnote 2). Then, uniprot sites5 were used to process all the names of targets and normalize the gene information following the standards of human origin. Detailed information of supposed targets is showed in The supposed targets of effective compounds were picked up from the TCMSP database ,3 the Swdatabase 4 and theOMIM),6 the DrugBank database (7 the GeneCards database (8 and the DisGeNet database (9 Detailed information is showed in Related CHD targets were collected from multiple databases including the Online Mendelian Inheritance in Man database  (OMIM),6database ,7 the Gedatabase 8 and thedatabase .9 Detail10 were used to construct the PPI network of compound-CHD targets. The protein interactions were recognized as owning high confidence when the scoring value > 0.4 , biological process (BP) and cellular components (CC), were identified. The results of MF, BP, CC and KEGG were input into Hiplot database,12 which is a free and comprehensive scientific data analysis and visualization tool based on web technology and is supported by open source communities.The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted using the functional annotation tool of DAVID Bioinformatics Resources.We constructed networks using Cytoscape as follows: Firstly, the “hawthorn leaves bioactive compound target network” was established by connecting the compounds and targets of hawthorn leaves. Secondly, the “compound target signal pathway network” was constructed by connecting the targets of the ingredients and related signal pathways. Thirdly, the “PPI network” was built by connecting targets with other interactive human proteins.13 and included for analysis. Limma package was performed to identify differentially expressed genes (DEGs) between healthy controls and coronary artery disease (CAD) samples. P < 0.05 were selected as thresholds to indicate a statistically significant difference. Logistic regression was performed to identify association between target genes and CAD and the model’s accuracy was evaluated using the receiver operating characteristics (ROC) curve. Statistical analyses were performed with the use of R software, version 4.0.5 .The expression profiles of GSE12288 was downloaded from the Gene Expression Omnibus (GEO) database in the NCBI portalMolecular docking was performed to further demonstrate the relationship between the key compounds and major target genes. The key compounds of hawthorn leaves were downloaded from the Pubchem database (see text footnote 4) and were changed to PDB format by a software called PyMol (the PyMol Molecular Graphics System). PyMol, which is an open-source molecular visualization system, has the ability to render high-quality 3D images of small molecules and biological macromolecules, and to remove original ligand, water molecules and phosphates . High-qu2 incubator (5% CO2 at 37°C). RAW264.7 cells were stimulated with LPS (1 μg/ml) (Sigma-Aldrich) in the presence or absence of quercetin  , kaempferol  , and isohamnetin   for 24 h.RAW264.7 cells were cultured with Dulbecco’s modified Eagle medium  containing 10% fetal bovine serum (Gibco) and 1% penicillin/streptomycin (Gibco) in a CO3 cells/well. Following the treatments mentioned above, the Cell Counting Kit-8 solution  was added to the medium according to the operation manual, the plates were incubated for 2 h in the dark at 5% CO2, 37°C. The optical density (OD) was quantitated by microplate reader  at 450 nm wavelength.RAW264.7 cells were inoculated in 96-well plates at 2 × 10IP lysate including 1:100 phenylmethanesulfonyl was used to extract RAW264.7 cells. Protein concentration was measured with a BCA kit . 10–12% gradient gels and polyvinylidene fluoride membranes were used to separate and transfer the protein samples (20–40 μg) sequentially. After blocked with 5% bovine serum albumin for 1 h, the membranes were incubated with primary antibodies against PTGS2 , EGFR , MMP2 , MMP9 , ESR1 , IL6 , IL1B , TNFα  and GAPDH  at 4 °C overnight. After washed with TBST, the membranes were incubated with the corresponding secondary antibodies for 1 h at room temperature. Bands were detected by Electrochemiluminescence and protein levels were analyzed with Gel Pro analysis software.P values < 0.05 were considered statistically significant.All statistical analyses were performed on GraphPad Prism 8.0 . Significant differences were analyzed by one-way analysis of variance (ANOVA) followed by Tukey’s post-test among groups of three or more. The flow diagram of this study is summarized in This study got 1892, 294, 35, and 546 targets involved in CHD from Genecard, Disgenet, Drugbank, and OMIM gene database, respectively. To improve the accuracy of the selected disease targets, we selected targets that appeared simultaneously in two or more gene databases. 194 disease targets were selected in this study . MoreoveBased on the results mentioned above, the 328 putative targets of hawthorn leaves mapped to the 177 CHD related targets to get the overlapped targets. The detailed information of CHD related targets is showed in To clarify the mechanism of drug treatment ulteriorly, the enrichment analyses were performed. GO annotations including biological process (BP), cell composition (CC), and molecular function (MF) were analyzed. The results of enrichment included 115 BP terms, 12 CC terms and 39 MF terms. The top ten terms with a significant adjusted P-value were shown in Key compounds and proteins expressed by major hub target genes were used for molecular docking. We used Autodock Vina to calculate the docking affinity score, as shown in The PTGS2, MMP2, and MMP9 protein levels were significantly increased after exposure to LPS (1 μg/ml), while reversed by quercetin , kaempferol  and isorhamnetin  treatment, respectively, in RAW264.7 cells. However, the expression of ESR1 and EGFR did not change. Moreover, quercetin, kaempferol and isorhamnetin treatment also reduced protein level of IL6, IL1B and TNFα induced by LPS . Furtherin vitro.In recent years, increasing number of studies dedicated to discover new drugs and combined TCM to treat complex disease such as CHD, network pharmacology approach has been proved to play an important role in these researches. In this study, we built the following network to explore the potential targets and pathways of hawthorn leaves in the treatment of CHD: compound-target network, disease-target network, PPI network of compound-CHD targets and compound-target-pathway network. Furthermore, we verified the effects of three effective compounds on selected targets and possible mechanism After integrating information from different sources of available databases and formulating screening conditions, three main active compounds of hawthorn leaves acted on 44 different targets associated with CHD were screened out. Three compounds such as quercetin, kaempferol and isorhamnetin are highly connected with their supposed targets and can be thought as effective compounds in hawthorn leaves. As a naturally occurring polyphenol, quercetin was reported to possess antioxidant, anti-inflammatory, and antiallergic activity , 30. KaeActually, consistent with prior researches, the network of CHD targets in our study did reveal the underlying pathogenesis of CHD. Abundant data confirmed that inflammatory mechanisms play a vital role in the occurrence and development of atherosclerosis and CHD . Early aTo better elucidate the mechanism of hawthorn leaves in the treatment of CHD, the 44 targets were screened out in the compound-CHD targets. Coincidentally, 14 targets, namely IL6, VEGFA, IL1B, MMP9, CXCL8, CCL2, PTGS2, IL10, ESR1, EGFR, MMP2, CRP, SERPINE1, and ICAM1, have been identified as key pathogenic genes in the PPI network of CHD target proteins. These results reveal that hawthorn leaves might protect against CHD through a multi-targets synergistic way.As shown by the compound-target gene-pathway network, quercetin, kaempferol and isorhamnetin interacted with lots of targets, indicating their complex and comprehensive roles in the treatment of CHD. To further understand the binding ability between compounds and targets, molecular docking simulation was performed between 14 targets genes and three active compounds to find out major targets. Absolute value of the docking affinity are positively correlated with binding force between the compounds and the active site of targets. The data showed that some of the compound- target pairs had good docking affinity, such as, PTGS2, MMP2, EGFR, MMP9, and ESR1 , which mThe potential therapeutic mechanism was also validated by GO functional annotation and pathway enrichment analysis. First, main BP in GO pathway enrichment analysis of common-targets included signal transduction and the response to inflammatory response, which means most key targets participate in these two biological process; Second, main CC of common-targets included extracellular space, plasma membrane, which means those targets that we may be interested in mostly locate at extracellular space and plasma membrane; Third, main MF of these targets is protein banding, which means the function of these targets is mainly protein binding. Besides, the results of KEGG pathway enrichment analysis showed that effects of hawthorn leaves on CHD may be due to its ability to target varied pathways simultaneously, such as pathways in cancer, TNF signaling pathway, malaria, and so on . As for in vitro experiments. This study further proves that network pharmacology is an effective method to screen the active components and action targets of TCM, and provides methodological inspiration for other studies about TCM in the future.The results of our study are consistent with that of previous similar study which explored the effects of hawthorn leaves on different disease models. Fu et al. reported that hawthorn leaves flavonoids could decrease the degree and scope of myocardial ischemia by inhibiting inflammation in anesthetized dogs with acute myocardial ischemia/reperfusion . Min et In fact, besides anti-inflammatory action, non-anti-inflammatory effects have been considered by several studies to be involved in the beneficial effects of hawthorn leaves. Previous studies have shown that hawthorn leaves could improve non-alcoholic fatty liver disease and diabetic cardiomyopathy by inhibiting oxidative stress , 62. Anoin vitro and in vivo researches. Secondly, although three targets  and three inflammatory factors  were verified to be involved in mechanism of action, the potential upstream or downstream relationships between them still need to be further explored. Thirdly, we have only studied the anti-inflammatory effects and possible mechanisms of hawthorn leaves in macrophages, but lack of studies in endothelial cells and smooth muscle cells. Fourth, the results of enrichment analysis suggested that hawthorn leaves may also have non-anti-inflammatory effects, and it may be biased to focus only on its anti-inflammatory effects. Therefore, in order to better understand its potential mechanism of action, the non-anti-inflammatory effects of hawthorn leaves should be further studied in future.However, there are still some limitations in this research. Firstly, as a kind of complex disease, the underlying mechanisms behind the occurrence and progression of CHD are complicated, the mechanism of action of hawthorn leaves in treatment of CHD needs more comprehensive In conclusion, the effective components and key targets of hawthorn leaves for CHD treatment were explored using network pharmacology approach. Quercetin, kaempferol and isorhamnetin were proved to be the main effective compounds in treatment of CHD, possibly by suppressing expression of PTGS2, MMP2, MMP9, inflammatory cytokines and activation of macrophages . The preThe original contributions presented in the study are included in the article/in vitro experiments and helped to write and review the manuscript. YW organized the study. All authors read and approved the final manuscript.QF designed the experiments, wrote the manuscript, and conducted the pharmacology information analyses. JW helped to conduct the pharmacology information analyses. SL and MH participated in visualizing the data. HRW helped with the data analyses. JD completed the The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Liu Wei Di Huang Wan (LWDHW) is a well-known Chinese herbal compound, which has been prescribed for the treatment of gestational diabetes mellitus (GDM). We sought to clarify the potential therapeutic effects of LWDHW against GDM. Differentially expressed genes (DEGs) in GDM were firstly identified from the Gene Expression Omnibus (GEO) database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to reveal the biological functions of the DEGs. Subsequently, the LWDHW-compound–target network was constructed based on public databases to identify the relationship between the active components in LWDHW and the corresponding targets. Furthermore, gene functional analysis and protein–protein interaction (PPI) network construction were applied to investigate the function of potential targets and to evaluate hub genes. Finally, molecular docking was used to verify the binding activities between active ingredients and hub targets. Thirteen active components and 39 corresponding therapeutic target genes were obtained via network pharmacology analysis. The enrichment analysis demonstrated that the anti-GDM effect of LWDHW included oxidoreductase activity, involvement in renal system process, and regulation of blood pressure, which may be achieved through regulation of serotonergic synapses, vascular smooth muscle contraction, and neuroactive ligand–receptor interaction pathways. Additionally, molecular docking revealed that the main active component, Mu Dan Pi, exhibited the best affinity for proteins encoded by hub genes. This study applied network pharmacology analysis and molecular docking to display the multicomponent and multitarget characteristics of LWDHW in the treatment of GDM. Our findings provide novel insights into the pathogenesis of GDM and the therapeutic mechanisms of LWDHW against GDM. GDM is defined as diabetes diagnosed during pregnancy, with an approximately 2–10% morbidity in pregnant women . It was β cell function, and regulation of hepatic gluconeogenesis [Traditional Chinese medicine (TCM) has been used for centuries to prevent and treat disease in China. The active components of several types of TCMs show great potential as effective therapy for GDM through different mechanisms, including the inhibitory effect on inflammation, enhancement of ogenesis , 12.Liu Wei Di Huang Wan (LWDHW) is a popular Chinese herbal formula and is commonly prescribed for the treatment of diabetes , hyperteNetwork pharmacology, a methodology developed in recent years, can reveal the complex relational network of medicine, genes, and targets of diseases  and is ahttp://www.ncbi.nlm.nih.gov/) [Here, we sought to clarify the mechanism by which LWDHW exerted an affect against GDM. We first identified genes that are differentially expressed in GDM from a Gene Expression Omnibus (GEO) database (ih.gov/) . Then, tih.gov/) , 23. Thehttp://www.ncbi.nlm.nih.gov/) [Homo sapiens.” The GSE51546 dataset  was obtained, which included data from six women with GDM and six healthy pregnant controls. Then, we downloaded the platform annotation file and series matrix files. The data were normalized, and each corresponding gene probe was converted into a gene symbol by using the Bioconductor R package [P value and control the false discovery rate, the Benjamini–Hochberg method was applied for multiple comparisons. A |log2 fold change (FC)| >0.263 and a P value < 0.05 were regarded as the cut-off criteria for DEGs. Heatmap and volcano plots of significant DEGs were generated using the R software.The GDM gene expression dataset was downloaded from the GEO database (ih.gov/) . We syst package . If ther package . In ordeP value < 0.05 was considered to be statistically significant. The results of GO and KEGG enrichment analyses were displayed as bubble charts generated by the ggplot2 R package.Gene Ontology (GO) displays gene functions from three different aspects: molecular function (MF), cellular component (CC), and biological process (BP) . Kyoto Ehttps://tcmspw.com/tcmsp.php) [The constituents of LWDHW were entered into the TCMSP database (msp.php)  to obtaimsp.php) , 30, OB,http://string-db.org/) was used to establish a PPI network [https://cytoscape.org/) [The STRING database ( network . In the pe.org/) . Additiope.org/)  was usedhttp://bionet.ncpsb.org/batman-tcm/) database, which is the first online bioinformatics analysis tool specifically designed for research into the molecular mechanisms of TCMs [The corresponding protein targets of each active ingredient in LWDHW were predicted using the BATMAN-TCM  and converted into mol2 format by PyMoL. Then, the PDB format file of the proteins encoded by the hub genes were downloaded from PDB database. Finally, Autodock Vina software [To further elucidate the underlying mechanism of LWDHW in the treatment of GDM, molecular docking was applied to predict and verify the binding activity of the core active compounds of LWDHW to proteins encoded by the hub genes with the top three Matthews correlation coefficient (MCC) scores. These genes were considered potential GDM-related targets. First, the SDF format file of the active component was obtained from the PubChem database  and were presented as mean ± standard deviation. All statistical tests were two-tailed. Differences were considered significant at P < 0.05.All statistical analysis were performed with R . As shown in Figures The LWDHW-main active compound–GDM-target-signaling pathway network was established for better elucidation of the therapeutic effect. As shown in Molecular dynamics simulation offers novel insights into the stability and binding activities of protein–ligand complexes. Thus, to validate the potential GDM therapeutic targets, we performed molecular docking of LWDHW with the proteins encoded by the top three hub genes. Docking analysis predicted Vina scores successfully. Specific information is shown in In this study, we sought to clarify the potential therapeutic effects of LWDHW against GDM, by investigating the intersection of GDM DEGs and LWDHW targets, followed by virtual docking experiments for verification. Molecular docking analysis indicated that the active components of LWDHW bound well to the proteins encoded by the top three hub genes. Specifically, aristolone (an active compound of Shan Zhu Yu) targeted AGT and ADORA2A, mairin (a main ingredient of Mu Dan Pi) also targeted ADORA2A, while catechin targeted CNR1.GDM is the commonest medical complication during pregnancy and imposes a marked economic and health burden with the increasing prevalence of obesity . Since oWe identified 19 active compounds in LWDHW, 508 drug-related targets, and 1408 DEGs of GDM from public databases. Among these, there were 39 genes in common between the DEGs and the drug-corresponding targets, suggesting their potential role in anti-GDM action. In the PPI network of these 39 target genes, the proteins were not independent but were linked in a network. After evaluation of the compound and construction of the network, 13 active compounds, 39 targets, and 31 pathways were finally identified . These rLWDHW has displayed beneficial effects on alleviation of insulin resistance through regulating the PI3K/AKT signaling pathway, according to previous studies , 40. In β cell proliferation, which could strengthen the expansion of β cells pharmacologically [Additionally, molecular docking further verified the possible combinations of compounds and target hub genes . Accordiogically . Taken tOur study has yielded marked insights into the molecular mechanisms by which LWDHW exerts therapeutic effects in GDM. Nevertheless, the current study had some limitations. First, the one-sided results of single microarray analysis may lead to a high false positive rate; thus, it is necessary to improve the power of detection by integrating the results of analysis of multiple datasets. Second, although bioinformatics analysis is a powerful tool for the identification of potential targets in GDM and to improve mechanistic understanding, the therapeutic effect and potential mechanisms of active components still need to be validated in further experimental research. Third, to clarify whether LWDHW can be beneficial to maternal and neonatal outcomes, the safety of this drug should be evaluated.In summary, our research elucidated the potential active ingredients and multiple target mechanisms of LWDHW in the treatment of GDM, which have not been published previously and which provide scientific evidence for clinical practice and application of LWDHW for further research. Our results clarified the potential therapeutic mechanism of the compound and verified this with molecular docking. The key targets, pathways, and ingredients identified here form a basis for further research and facilitate herbal medicine use for the treatment of GDM in future. However, due to the limitations of network pharmacology analysis, it needs to be established whether the active components themselves could be used in GDM treatment in future. Additionally, more clinical research and molecular experiments are necessary to validate our current findings.


To explore the potential active compounds and molecular mechanism of Xuefu Zhuyu decoction (XFZYD) in the treatment of atherosclerosis (AS) based on network pharmacology and molecular docking.The effective components and action targets of XFZYD were screened by using TCMSP database. And then, the action targets of AS were collected by GeneCards database. The intersection targets between the effective components’ targets of XFZYD and AS-related action targets were used to construct PPI networks. GO and Kyoto Encyclopedia of Genes and Genomes enrichment analysis were performed on these intersection targets. Finally, molecular docking software was used to excavate the active compounds of the core targets VEGFA and AKT1.We detected 225 active components of XFZYD, and found that quercetin, kaempferol, luteolin, naringenin, β-sitosterol, isorhamnetin, stigmasterol, baicalein, nobiletin, and β-carotene are the potential active compounds of XFZYD; STAT3, IL6, JUN, VEGFA, MAPK14, and AKT1 are the core target proteins of the active compounds, among which VEGFA and AKT1 are the key target proteins. PPI network results showed that β-carotene, quercetin, kaempferol, luteolin, and naringenin had higher degree values and more corresponding targets than other 5 active compounds and had the stable binding ability to regulatory proteins VEGFA and AKT1. The core components β-carotene, quercetin, kaempferol, and luteolin exerted their therapeutic effects on AS by acting on the key target proteins VEGFA and AKT1 to regulate fluid shear stress and the AGE-RAGE signaling pathway and IL-17 signaling pathway of diabetic complications of AS. The molecular docking results showed that VEGFA and AKT1 had great docking ability with the targeted active compounds, and β-carotene is the best.The active components of XFZYD, including β -carotene, quercetin, kamanol, and luteolin, can act on VEGFA and AKT1. These active ingredients play a role in alleviating and treating AS by regulating fluid shear stress and participating in signaling pathways such AS AGE-RAGE of atherosclerosis and diabetes mellitus complicated with AS. β-carotene is a potential inhibitor of VEGFA and AKT1 and treats AS through antioxidant action. Statins are currently restricted in their use in the clinic due to liver and muscle damages, so it is of practical significance to find more safe and effective drugs to prevent AS. In Traditional Chinese Medicine (TCM ), AS belongs to the category of “pulse carbuncle” and “pulse paralysis,” which could affect the blood vessels. AS can result in cardiovascular disease such as strokes, myocardial infarction, and chest arthralgia. Blood stasis, according to ancient doctors, was astringent and stagnant, gathered heat and formed poison, and toxic evil was most likely to injure muscles and veins. A therapeutic treatment strategy involves improving circulation and reducing blood stasis.Atherosclerosis (AS) is a critical cause of many cardiovascular and neurological diseases. Clinical research reported that XFZYD can significantly improve microcirculation, expand microvessels, increase tissue perfusion, alleviates clinical symptoms, and so on.–7 Many diseases, including myocardial fibrosis, AS, hypertension, unstable angina pectoris, and myocardial ischemia-reperfusion injury, have been treated using XFZYD.,9 However, more research is needed into the material basis and molecular targets of multicomponent, multichannel, and multitarget XFZYD in the prevention and treatment of as to give an evidence-based foundation for clinical wide application and new drug development.The Xuefu Zhuyu decoction (XFZYD), created by Wang Qingren in the Qing Dynasty, is the therapy for blood stasis which including Persicae semen (Taoren), Carthami flos (Honghua), AngElicae sinensis radix (Danggui), Rehmanniae radix (Dihuang), Achyranthis bidentatae radix (Niuxi), Chuanxiong rhizome (Chuanxiong), Platycodonis radix (Jiegeng), Paeoniae radix rubra (Chishao), Aurantii fructus (Zhiqiao), and Bupleuri radix (Chaihu). It can improve blood flow, reduce blood congestion, boosts energy, and relieves pain.,11 In this study, the network pharmacology method was combined with molecular docking technology to predict the therapeutic mechanism of multitarget and multilevel synergistic application of pharmacodynamic active components in XFZYD for the treatment of AS, which helps to clarify the molecular mechanism of XFZYD in the treatment of AS and improve the effectiveness of the drug.Network pharmacology has become a brilliant way of studying traditional Chinese medicine’s multicomponent and multitarget action mechanism. This method employs bioinformatics, system biology, and multidrug biology to integrate network analysis, which breaks down the multilevel and all-encompassing drug mechanism into its constituent parts.GeneCards and PDH belong to public databases. The patients, animals, and protein structures involved in these databases have obtained ethical approval. These data have been maintained publicly available for any researchers to use. Thus, the relevant data could be downloaded gratuitously for users to do some research and publish relevant articles. Our study is based on the open-source data, so there are no ethical issues and other conflicts of interest.https://old.tcmsp-e.com/tcmsp.php), the compounds in XFZYD was obtained. The effective compounds were screened according to oral bioavailability ≥ 30% and drug-like ≥ 0.18. With the help of the UniProt database (https://www.uniprot.org), we converted the collected active components into gene names.Using TCM System Pharmacology database and analysis platform , search “AS.” We screened for AS disease targets to satisfy the Relevance score ≥ 3 of the disease set.AS disease targets were retrieved from the GeneCards database , choose Homo Sapiens as the race, and set the degree of confidence to 0.9 (the degree of confidence score represents the degree of protein interaction). We put the PPI network node data from the string database into Cytoscape 3.8.2 for network topology analysis and visualization, and the top 15 nodes are chosen as the core target of XFZYD for the treatment of AS, using degree as the screening criterion point.Import the intersection target into the String database , molecular function (MF), and cell composition (CC), then visually analyze the top 10 entries in each module. The intersection targets were analyzed using the KOBAS 3.0 database (http://kobas.cbi.pku.edu.cn/) for Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, and we chose the first 15 signal pathways as significant enrichment pathways.Set the threshold value to http://www.rcsb.org/). The 3D structure of effective compounds and the position control’s target core protein was obtained from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/). We download the 3D structure of active compounds in XFZYD targeting core protein and positive control in the PubChem database (https://pubchem.ncbi.nlm.nih.gov/). Utilize the Molecular Operating Environment (MOE v2019.0102 software) to optimize the target protein structure  and minimize the energy of the active compound, as well as perform molecular docking of the processed target protein and small molecule compounds. To verify the binding of the target protein and the target active chemical, RSMD is utilized as the accuracy parameter of the molecular docking model , and S  is used as the binding free energy parameter.The core target protein, whose species is human and the protein crystal resolution is <3A, was obtained in the PDH database  expression in human umbilical vein endothelial cells in vitro by decreasing STAT3 phosphorylation; hence, boosting VEGF-induced endothelial cell migration and proliferation and delaying the formation of atherosclerotic plaque. It is reported that STAT3 can bind to the promoter region of the VEGF gene and regulate its transcription.,22 When the inflammatory inducible factor IL6 binds to relevant receptors, it can facilitate signal transmission in cells, activate the JAK2/STAT3 signal pathway, and boost vascular smooth muscle cell proliferation. Inactivation of the c-Jun/AP-1 signaling pathway can effectively relieve AS in vivo and reduce the proliferation and migration of atherosclerotic vascular smooth muscle cells (VSMCs), according to Rongjing Ji. The findings show that the major active chemicals operate on a variety of target proteins to serve an overall regulatory effect.STAT3, IL6, Jun, VEGFA, Mapk14, and Akt are the primary target proteins in the PPI network (Fig.  Through oxidative stress, the AGE-RAGE signaling pathway can exacerbate vascular damage. Vascular damage is closely relative to plaque development in AS. Further investigation showed the pathways involved in the treatment of AS by XFZYD are related to the VEGFA signaling pathway, AKT1 signaling pathway, and MAPK14 signaling pathway. Meanwhile, the pathways involved in the treatment of diabetes complicated by AS by XFZYD are related to the VEGFA signaling pathway, AKT1 signaling pathway, and CCL2 signaling pathway. VEGFA is a critical angiogenesis growth factor, promoting macrophage infiltration, endothelial cell proliferation and differentiation, and foam cell formation. AKT1 is a serine/threonine-protein kinase that, among other things, helps regulate vascular endothelium and VSMCs and plays a role in protecting the cardiovascular system.,27The KEGG pathway enrichment analysis revealed that XFZYD inhibited AS via modulating the fluid shear stress, the AGE-RAGE signal pathway, the TNF signal pathway, and the IL-17 signal pathway Fig. . AS and The results of fluid shear stress and atherosclerosis enrichment pathway Fig. , AGE-RAGThe active compound—intersection target network, degree ranking of key active compounds, and molecular docking results of apple were comprehensively analyzed, we found that β-carotene, quercetin, kaempferol, luteolin, and naringenin not only have higher degree values and correspond to more targets, but also have good binding ability to key regulatory proteins VEGFA and AKT1, they may be active chemicals with the potential to treat AS. The above results reflected that XFZYD has the biological characteristics of multicomponents, multitargets, and multipathways. These components, targets, and pathways are woven into a network to treat atherosclerosis at a holistic level.In summary, we studied the enrichment analysis of action targets of XFZYD in treating atherosclerosis, then carried out the network topology analysis of the TCM component-action target network diagram and protein interaction network diagram. We found that β-carotene, quercetin, kaempferol, and luteolin in Safflower can act on VEGFA and AKT1 and other targets. By regulating the shear stress of vascular fluid and participating in the regulation of AGE-RAGE and other signaling pathways in atherosclerosis and diabetes mellitus complicated with AS, it can play a role in alleviating and treating AS. The active compounds that target VEGFA and AKT1 show strong docking ability and could be potential inhibitors of VEGFA and AKT1. β-carotene has the best docking ability of the bunch, and our study has shown that it can help prevent AS through antioxidants. In short, XFZYD treats AS with multiple components, multiple targets, and multiple pathways, providing ideas and references for AS and the theoretical basis for subsequent experimental studies. But there are also some limitations in our study, there are no further experiments to verify the results. Next, we will verify the results through animal or cells experiments.Jingshan Zhao, Lin Liu, Yingyun Li, Boyu Liu performed main analysis and drafted the article. Qing Xu, Quan Shen, Weikang Li helped in the introduction sections. All authors wrote, read, and approved the article.Conceptualization: Jingshan ZhaoData curation: Qing Xu, Quan Shen, Weikang LiFunding acquisition: Jingshan Zhao, Lin LiuInvestigation: Yingyun Li, Lin Liu, Jingshan Zhao, Boyu LiuProject administration: Jingshan Zhao, Lin LiuResources: Yingyun Li, Boyu Liu, Qing Xu, Quan Shen, Weikang LiSoftware: Yingyun Li, Quan Shen, Qing XuSupervision: Jingshan Zhao, Lin LiuValidation: Jingshan Zhao, Lin LiuWriting-original draft: Yingyun Li, Boyu Liu, Jingshan ZhaoWriting-review and editing: Yingyun Li, Lin Liu, Jingshan Zhao