Metabolomic is generally characterized as a comprehensive and the most copious analytical technique for the identification of targeted and untargeted metabolite diversity in a biological system. Recently, it has exponentially been used for phytochemical analysis and variability among plant metabolites, followed by chemometric analysis. Network pharmacology analysis is a computational technique used for the determination of multi-mechanistic and therapeutic evaluation of chemicals via interaction with the genomes involved in targeted or untargeted diseases. In considering the facts, the present review aims to explore the role of metabolomics and network pharmacology in the scientific validation of therapeutic claims as well as to evaluate the multi-targeted therapeutic approach of traditional Indian medicinal plants. The data was collected from different electronic scientific databases such as Google Scholar, Science Direct, ACS publication, PubMed, Springer, etc., using different keywords such as metabolomics, techniques used in metabolomics, chemometric analysis, a bioinformatic tool for drug discovery and development, network pharmacology, methodology and its role in biological evaluation of chemicals, etc. The screened articles were gathered and evaluated by different experts for their exclusion and inclusion in the final draft of the manuscript. The review findings suggest that metabolomics is one of the recent most precious and effective techniques for metabolite identification in the plant matrix. Various chemometric techniques are copiously used for metabolites discrimination analysis hence validating the unique characteristic of herbal medicines and their derived products concerning their authenticity. Network pharmacology remains the only option for the unique and effective analysis of hundreds of chemicals or metabolites via genomic interaction and thus validating the multi-mechanistic and therapeutic approach to explore the pharmacological aspects of herbal medicines for the management of the disease. Medicinal plants have been considered an essential source for drug discovery and development as they are enriched in verities of phytochemicals of different categories . Due to However, several modern analytical techniques, including chromatography, nuclear magnetic resonance (NMR), and mass spectrometry (MS), are used abundantly in the quantitative and qualitative assessment of plant metabolites. However, these techniques are much preferred with plant phytoconstituents profiling or metabolomics studies due to their high sensitivity and accuracy when coupled with effective chromatographic techniques that allow separation and characterization of the diversity of phytoconstituents present in medicinal plants . These tm/z values of metabolites are matched to reference data from mass banks, where the analysis is resumed under a defined tolerance of m/z value variability. MS data acquisition relies on the probability score between the analysis query and the reference data search. For non-targeted metabolites, the data acquisition tolerance can be in both the m/z value and the chromatographic retention time, and further, these implications are accustomed to measurements using alignment software. Advanced web-based platform analysis was established based on automated workflows ranging from processing to the extreme alignment of row data, annotation, and statistical analysis tools to enable easy access to a wide range of investigators or informatics experts [In mass spectrometric analysis,  experts ,8,9.With the advent of the gradual rise of interdisciplinary disciplines related to bioinformatics and computational biology, researchers are becoming more motivated or are shifting from single-mode to multidisciplinary and dimensional systematic research modes for traditional medical research. There are important changes from the perspective of biomolecular networks involving the role of genes in disease regulation to understand the mechanism of drug action. The purpose of using “network computational biology” is to bring about significant change or to address new challenges associated with the initial testing of drugs. Network targeting represents unique concepts that characterize the biological network of diseases underlying therapeutic targets and understand the systematic mechanism of action for one of the multi-targeted drugs primarily for conventional medicine. Thus, the principle of “network prediction of targets” has been accepted as a fundamental principle of network pharmacology ,11.Traditional Medicine (TM), characterized by individualized, multi-component, and holistic medicine, holds great potential in conceptualizing the various challenges in the system of modern health care . TraditiNetwork pharmacology (NP), a brand-new area of study, aims to explain the interactions and actions of drugs with a variety of targets. It uses technology to systematically catalog a drug molecule’s molecular interactions with a living cell . ResearcBased on the phytopharmacological evolution of metabolites, the present study is associated with exploring the mechanistic molecular role of metabolites in the treatment of various diseases, including its properties such as antimutagenic, antiulcer, antioxidant, antidiabetic, antifertility, anthelmintic, antilipolytic, etc. In the molecular-based pharmacological assessment of metabolites, the present study explores the multi-targeted therapeutic approach of traditional Indian medicinal plants in the treatment of various acute and chronic diseases .Studies were conducted according to preferred reported items/checklists from systematic reviews or statements of research articles published in national and international journals.The information was collected through a comprehensive literature search using more than five electronic databases such as Science Direct, Elsevier, Google Scholar, ACS Publications, PubMed, and Springer from databases published between 2000 and 2022 or more recently for the study. Influential information was selected for targeted and untargeted data. Modern systems of medicine and therapy for treatment, traditional systems of medicine and medicinal plants for the treatment of disease, phytochemistry, nephroprotective activity, antioxidant activity, oxidative and anti-inflammatory activity, and inflammatory stress associated with the pathophysiology of diseases, etc., were all included in the review, and the research papers checked for potentially relevant citations in the reference list. The study selection was restricted to articles in English due to the language barrier, time efficiency, and high cost of translation. For comprehensive detection of relevant studies and recapitulation of the journal’s publication history, a systematic review was conducted with the hyphenated keyword “Role of medicinal plants in the management of diseases; A systematic review”. Appropriate data were extracted and summarized as prospective information on metabolites to reach the selection process.Published reviews or research articles regarding the prevalence of diseases in national and international journals and metabolites represent a diverse group of low-molecular-weight structures, including lipids, amino acids, peptides, nucleic acids, and organic acids, that allow inclusive analysis to be combined into one.Studies such as duplicate publications, abstracts, and research published before 2000, unauthentic ethnobotanical/ethnomedicinal reports lacking study areas/localities, informant’s involvement, data of untargeted plant and disease, and non-open access journal articles or in part accessed articles were removed to avoid miscomprehension.All authors independently assessed the study through their inclusion criteria by examining the title and abstract of each record and obtaining its full text, if necessary. Study selection includes only well-indexed journal publications (research and review articles) related to diseases for trending input. The search results were screened based on the title and abstract of the identified journal articles/thesis. Furthermore, out of thousands of reports, only appropriate reports were downloaded and critically inspected to elaborate the discussion related to the preclinical and clinical evaluation of metabolomics and its exploration of multi-targeted therapeutic approaches of traditional Indian medicinal plants.We are aware of the multi-mechanistic and therapeutic action of medicinal plants and their derived products exhibited by the varieties of the metabolites present in the plant matrix, thus, alleviating several acute and chronic ailments. During this period, omics technology advancements were leveraged to create strategies for different aspects of drug research ,23. In oIt is known that medicinal plants deal with the diversity of metabolites even with different chemical or structural behavior. Furthermore, to reach perfection in exploring the phytochemistry of medicinal plants, a single analytical method does not put into their high throughput phytochemical screening . As eachBased on the above facts and assessment for metabolomic analysis helps us to unravel and even reach perfection in qualitative and quantitative phytochemical analysis of medicinal plants. Furthermore, in a single study, quantitative-based standardization of the medicinal plant needs at least four marker constituents to validate the authenticity aspects for their regulatory purpose . A systeComputational techniques have been growing and exotically contributing to drug discovery and development via assessing wide varieties of genes and their expression behavior to the chemical or bioactive principles which are involved in the pathophysiology of any ailments. Compounds and protein interaction and biomolecular accession provide a high throughput orientation to explore better pharmacological validation concerning the targeted or untargeted metabolites. Besides this approach, the one-drug/one-target/one-disease strategy for drug development is currently confronted with several difficulties in terms of sustainability, efficacy, and safety. Recently, strategies for network biology and pharmacology, respectively, have acquired recognition ,34.Network biology and polypharmacology are one of the most conventional approaches to exploring multi-mechanistic and therapeutic targets for integrating omics data and developing multitarget drugs. Hence, both approaches are combined and acknowledged as network pharmacology. This approach does not look only at the consequence of drugs in terms of the effect on both the interactome as well as the diseasome level and covers multiple interactions with multiple proteins/genes in a single time . By enabhttps://jensenlab.org/, 19 October 2022), while the type of interactors to the expanded network should remain to the Homo sapiens species only. The process is repeated till no interactors are further connected via expanding the network. No further expansion of the network represents no additional genomic information exists in the reported database. Thereafter, the statistical information of the generated network about the number of nods, edges, network density, heterogeneity, etc., is imported through a network analyzer. In one example, the constructed network with statistical summary has been depicted in In this analysis, the active molecule can be fixed or can not be fixed, which needs to be explored biologically based on the interaction of targets/genes targets that would be interacted with the molecule are completely unfixed. A random analysis is done using the software commands (Cytoscape) of the STRING app to expand the network. During this process, the number of interactors to expand the network depends on the information retrieval that exists in the database , which is a free online database that involves an n-number of genes involved in diseases. STITCH is an open-source platform for rapid analysis of the active components and the genes which are needed to be analyzed. Each component and selected gene are inserted into the STITCH platform of the Cytoscape software. It gives multiple possible matches at the fixed or optimum confidence score of 0.04 and maximum additional interactor ,36. DuriMomordica charantia in the alleviation of diabetic nephropathy. In this study, the author explored the therapeutic potential of several metabolites of Momordica charantia and reported that quercetin, ferulic acid, caffeic acid, and catechin are the potential metabolites that exhibit a significant interaction with the genes such as G6PD, MAPK1, MAPK3, NOS, PTGS2, PON1, ILs, etc. and alleviating diabetic nephropathy and its associated complications [Boerhaavia diffusa and Tinospora cordifolia against glomerulopathy, inflammation, oxidative stress, etc. The outcome of the study showed that Boerhaavia diffusa and Tinospora cordifolia contains several metabolites, such as polyphenols which poly a significant role in the alleviation of kidney disease and its associated complication via the regulation of several genomes such as CASP3, CASP7, CASP8, CASP9, MAPK1, MAPK3, TNF and TP53 involved in the several pathways AGE/RAGE pathway, signaling to interleukins, response to the inorganic substances, TNF signaling pathway, lipid localization, regulation of defense response, RAS and bradykinin pathway in COVID-19, circulatory system process, cellular response to nitrogen compounds, etc. [Previously, several studies have been reported based on the targeted and untargeted network pharmacology analysis, which revealed the multi-mechanistic and therapeutic role of various biologically active metabolites in the alleviation and treatment of diseases. In a study reported by Gautam evaluated multi-mechanistic and therapeutic potential of ications . Gaurav ds, etc. .https://www.networkanalyst.ca/, 19 October 2022), Metascape , STRING , DisGeNET , etc. outlined in Gene ontology analysis showed the multi-targeted and mechanistic approach of the targeted genes that are screened through the protein-protein network (PPI) and compound-protein interaction (CPI) network analysis. it gives information about that how genes play multi-targeted effect in pathophysiology involved in the disease via regulation of several positive and negative biological pathways. There are several platforms such as Cytoscape, network analyst  up to 24-methylene cholesterol, which is thought to be a precursor for the biosynthesis of withanolide, based on the annotation. Additionally, certain contigs associated with the enzymes used in these processes displayed differential expression [Gupta et al. evaluated functional annotation and comparative analysis of pression .Boerhaavia diffusa and Tinospora cordifolia, in the regulation of several pathways such as signaling to interleukins, response to the inorganic substances, TNF signaling pathway, lipid localization, regulation of defense response, RAS and bradykinin pathway in COVID-19, circulatory system process, cellular response to nitrogen compounds, etc. [Momordica charantia in alleviating diabetic nephropathy and its associated complications via regulation of several pathophysiological pathways such as metabolic regulation, increased uptake of glucose to the muscle, obviating insulin resistance, biochemical markers regulation, oxidative stress, and inflammation, etc. [Exploration of multi-mechanistic and therapeutic action of traditional medicines through network biology, polypharmacology and gene ontology analysis has been increased exponentially. Vadivu et al. reported that mapping genes involved in the diseases with standardized ontology analysis gives more improvement in analyzing the biological performance of the medicinal plants and their therapeutic options . Severalds, etc. . Gautam on, etc. .Physostigma venenosum potential targets were identified using a combination of network pharmacology and virtual reverse pharmacology techniques for the treatment of vascular dementia (VaD). This work used PASS prediction to find known VaD-related targets interacting with phytomolecules. More than 200 proteins connected to VaD were studied since its expression has increased. In order to broaden the scope of the search, an extra 34 genes were chosen. It was done because, from a pharmacological perspective, it is typically simpler to inhibit the function of proteins than to activate them. Thirty-four mechanisms of action (MOAs) predicted by the PASS program were found to exist. It was found that eseridine, physostigmine, physovenine, and eseramine can be predicted with a probability Pa of more than 0.5 for their dual MOAs (inhibition of acetylcholinesterase and butyrylcholinesterase) and pharmacological effects related to the treatment of VaD (cognition disorder treatment and nootropic). Acetylcholinesterase and butyrylcholinesterase are both inhibited by eseridine42. Physostigmine holds patents for treating dementia and Alzheimer’s disease as well as inhibiting butyrylcholinesterase, acetylcholinesterase inhibition, and memory enhancement. While eseramine has a less inhibitory effect against acetylcholinesterase than physostigmine, physovenine was patented as an inhibitor of acetylcholinesterase and butyrylcholinesterase as well as for the treatment of AD and dementia. The anti-acetylcholinesterase and anti-butyrylcholinesterase activity of several phytomolecules may have additive or synergistic effects on the therapeutic benefits of Physostigma venenosum in the treatment of VaD. It is now understood that this plant is utilized to cure atherosclerosis [clerosis .Duranta repens (D. repens) in diabetes mellitus. Through network pharmacology analysis between -amylase inhibitors, regulated proteins, and expression pathways, it was possible to determine the -amylase inhibitory action of substances from Duranta repens. In the compound-protein-pathway network, it was discovered that the PI3K-Akt signaling route and the p53 signaling pathway were anticipated to be substantially regulated. Scutellarein was also projected as the main hit based on its ability to inhibit -amylase, its affinity for binding, and its involvement in regulated pathways. Additionally, AGE-RAGE and the FoxO signaling pathways, which are implicated in diabetic complications, were projected to be modulated by -amylase inhibitors. It was shown that D. repens may not only block -amylase in the GI tract, but may also be absorbed into the systemic circulation and influence several pathways implicated in the etiology of diabetes mellitus to generate a synergistic or cumulative impact [Khanal et al. performed gene ontology enrichment analysis of α-amylase inhibitors from e impact .Traditional Indian medicinal plants and their therapeutic exploration through network pharmacology. Research techniques for developing novel drugs are increasingly using network-based methodologies. By using natural products as the primary molecule responsible for medication synergism and cumulative action, they aid in understanding novel therapies. These methods have been demonstrated to be effective in several herbal preparations used in conventional medicine ,41,42,43Quality, efficacy, and safety issues about herbal medicines often concern researchers or the healthcare system due to their complex phytochemical matrix responsible for exhibiting the pharmacological effect. In a plant matrix, it is challenging to justify which type of phytochemicals is responsible for exhibiting the pharmacological effect and to what extent. Besides that, herbal medicines and their derived products still represent the need for their comprehensive safety concern. Studying the phytochemicals of medicinal plants using modern analytical techniques such as LC-MS, GC-MS, and NMR, etc., are the most precise, accurate, and robust techniques for the qualitative and quantitative-based standardization of medicinal plants. These techniques have been exponentially used to explore the metabolomics pattern of medicinal plants. Furthermore, bioassay-based exploration of metabolomics patterns of medicinal plants brings to reach several facts concerning efficacy and safety. Qualitative and quantitative phytochemicals-based exploration of medicinal plants leads to unfolding their authentication concerns and provides accuracy in the regulatory-based exploration of medicinal plants. In recent times, several types of research have been conducted to explore the metabolomic pattern of medicinal plants using single technology such as LC-MS, GC-MS, NMR, etc. As we are aware of the complexity of the phytochemicals and their different chemical nature, single analytical methods cannot be accurate and precise enough to explore the complete phytochemical profile of the compounds. Plant metabolomics is well explored using different analytical methods based on the targeted phytochemical’s nature.With the expansion of research and development in medical technologies, more animals are being employed in the study. All throughout the world, millions of experimental animals are utilized each year. Animals’ suffering, mortality, and misery during scientific studies have long been a topic of controversy. Animal research has several critical and concerning drawbacks outside the main ethical issue, such as the need for trained labor, lengthy protocols, and high expense. In order to address the problems with animal testing and prevent unethical practices, several alternatives have been presented. For the use of animals in laboratories, the three Rs  are being used as a strategy .The different fundamental principles of biology can be better understood by computational methods. In order to create novel drugs, specialized computer models and software are used. Without dissecting animals, computer-generated simulations are used to estimate the numerous potential biological and toxic consequences of a chemical or prospective medication candidate. For in vivo testing, only the most promising compounds discovered via initial screening are employed. For instance, in vivo testing is required to determine a drug’s receptor binding location. The receptor binding site for a prospective therapeutic molecule is predicted using computer software called Computer Aided Drug Design (CADD) . By idenIn considering the 3Rs strategy, computational or in-silico approaches remain an exponential contribution to drug discovery and development, as well as drug repurposing via approaching biomolecular targets for potential therapeutic effects. Network pharmacology is one of the most efficient and conventional approaches to exploring the multi-targeted and therapeutic effects of chemicals. It is well-defined in the exploration of polypharmacology of medicinal plants or their derived products, even exponentially used to validate their traditional therapeutic claim via approaching different biological targets. However, the traditional drug research approaches are not suitable enough to study the biomolecular therapeutic application of complex components with many targets. Network biology or network polypharmacology provides a novel research technique for studying several active ingredients with their and predicting effector targets and effector mechanisms involved in the treatment of certain diseases.Different methods and alternatives to organisms provide a contributing hand concerning the computational approach, especially network biology, and polypharmacology is well enough for drug discovery and development via approaching their biomolecular and multi-targeted effects. Moreover, in the establishment or validation of the therapeutic effect of traditional medicinal plants or any herbal formulae, metabolomics and network pharmacology provides a contribution to validate them based on multi-targeted and therapeutic effect. The findings provided by the network pharmacology for predicting effector targets and effector mechanisms are based on reported databases. It would be an effective and alternative tool for the biological or therapeutic exploration of active constituents, thus contributing to scientific validation of medicinal plants concerning their safety and efficacy.This review enlightens the systematic approach of metabolomics and network pharmacology for multi-mechanistic and therapeutic exploration of traditional Indian medicinal plants or active constituents, as well as to identify biomolecular targets concerning pathophysiological alterations. In Network biology, gene enrichment analysis is generally used to predict the pathways involved in diseases. Through this study, the synergism between numerous components, targets, and pathways may also be predicted, validating the mechanistic evidence to support clinical practice and pharmaceutical impact. It also provides ideas for the establishment of further scientific evidence. Although this approach provides a theoretical basis for better clinical development of drugs for the treatment of any acute and chronic ailments, the research conducted on network pharmacology is based on database mining research, and the mechanism of drug action is only predicted. Considering the facts of metabolomics and network pharmacology, it can be one of the most promising computational techniques for the exploration of multi-therapeutic effects in both the assessment of drug development, pre-clinical or post-clinical where a drug or drug formulae are having numbers of active constituents.


The aim of this study is to evaluate the clinical efficacy of Tongxinluo capsules in preventing coronary restenosis based on meta-analysis and network pharmacology research methods and to preliminarily explore its intervention mechanism.  First, through meta-analysis, we comprehensively searched databases such as CNKI, Wanfang, PubMed, the Cochrane Library, and Web of Science to find out the randomized controlled trials of Tongxinluo capsules in the treatment of coronary restenosis until February, 2022. According to the Cochrane Library, risk bias assessment tools were used to evaluate the included literature and Review Manager 5.2 software was used to conduct statistical analysis of the included studies. Then, based on network pharmacology, through TCMSP database and BATMAN-TCM database screening, the chemical components of Tongxinluo capsules and their related effects, symptom, and common targets were analyzed. String net was used to construct protein-protein interaction (PPI) network, and R3.6.1 software was used to carry out GO biological process enrichment analysis and KEGG signaling pathway enrichment analysis to clarify key pathways.  The meta-analysis finally included 10 RCTs with a total of 1318 subjects. Meta-analysis results showed that Tongxinluo capsules combined with conventional cardiovascular drugs could significantly improve the clinical efficacy of preventing in-stent restenosis and the clinical efficacy of preventing angina pectoris. There was no significant difference in the clinical efficacy of preventing myocardial infarction. Network pharmacology obtained a total of 101 chemical components and 149 targets through the online database. The results of network analysis showed that the targets were mainly involved in receptor ligand activity, carboxylic acid binding, steroid hormone receptor activity, and other related action pathways and were also involved in AGE-RAGE signaling pathway, cell senescence signaling pathway, and other related pathways.  Tongxinluo capsules combined with conventional cardiovascular drugs can improve the clinical efficacy of preventing in-stent restenosis and angina pectoris and have a significant effect on reducing inflammatory factors. The comprehensive result of the effect is mainly through the participation of receptor ligand activity, carboxylic acid binding, steroid hormone receptor activity, and other ways to achieve the purpose of treating coronary restenosis. With the improvement of Chinese people's material living standard and the change of lifestyle, the morbidity and mortality of coronary heart disease are increasing year by year, and it has become a major health hazard disease. Cardiovascular and cerebrovascular diseases (CVD) have caused serious health problems in China. According to relevant statistics, about 45 percent of patients died of CVD in 2019. About 2.5 million of them had coronary heart disease (CHD) and about 200,000 died , with thTongxinluo capsule is based on traditional Chinese medicine (TCM) collaterals epidemiology and under the guidance of the theory of ZangXiang doctrine developed by compound Chinese medicine, by ginseng, leech, scorpion, Peony root, cicada slough, terrapin, centipede, sandalwood, incense, frankincense, sour jujube kernel, and borneol, are composed of ten aftertaste Chinese herbs, which have the effects of nourishing blood, invigorating qi, promoting blood circulation, removing blood stasis, clearing collaterals, and relieving pain. Ginseng has the effect of replenishing qi; leeches, red peony root, terrapin, and frankincense have the effect of activating blood circulation; scorpions, cicada slough, and centipedes have the function of channeling channels and collaterals, sandalwood and incense have the function of qi. Jujube seed has the effect of nourishing blood; borneol has both the function of activating blood and channeling channels. Clinically, Tongxinluo capsules combined with conventional cardiovascular drugs have been proved to be effective in preventing coronary restenosis after PCI. Unfortunately, the mechanism is not clear.This study investigated the clinical efficacy of Tongxinluo capsules combined with conventional cardiovascular drugs in preventing coronary restenosis after PCI through meta-analysis and preliminarily analyzed its target and possible pathway of action through network pharmacology to explore their intervention mechanisms, which provided a scientific basis for Tongxinluo capsules in preventing coronary restenosis.I > 70%) with coronary heart disease or myocardial infarction.The literature inclusion criteria were as follows: (1) Randomized controlled trials (RCTs) published in China and abroad; (2) the language is limited to Chinese and English; and (3) the subjects were patients after PCI, that is, patients with angina symptoms confirmed by coronary angiography (CAG) as single or multiple vessel lesions (target vessel stenosis The literature exclusion criteria were as follows: (1) Inclusion criteria were not met; (2) animal experiments; (3) literature review; (4) literature with poor design and incomplete data; (5) repeated publications; and (6) patients with other complications .In-stent restenosis (ISR), angina pectoris (AP), myocardial infarction (MI), IL-6, and total incidence of adverse cardiovascular events.https://www.cnki.net/), Wanfang Journal Database , PubMed (https://pubmed.ncbi.nlm.nih.gov), the Cochrane Library (https://www.cochranelibrary.com/), and Web of Science (https://www.webofscience.com/). The search period was from the establishment of the database to February, 2022. Chinese keywords mainly included “coronary artery,” “restenosis,” “clinical medicine,” and “Tongxinluo capsule.” English search words mainly include “Tongxinluo capsule,” and “in-stent restenosis.”China National Knowledge Infrastructure  generation of random sequences; (2) allocation hidden; (3) blind subjects or researchers; (4) data integrity; (5) whether there is selective reporting of results; and (6) other biases. According to the literature content, three grades of “low risk,” “high risk,” and “unbelievable risk” were carried out for the literature.P value and I2 index of heterogeneity test. If there was homogeneity among studies , a fixed-effect model was used for analysis; otherwise, random effect model was used. Odds ratio (OR) and 95% confidence intervals (CI) were selected to describe the results. The control group was divided into “conventional treatment” and “conventional treatment + one drug” for subgroup analysis according to different intervention measures.Manager 5.2 software was used for data analysis, and heterogeneity assessment was made for the included literature according to the https://tcmspw.com/tcmsp.php); the Bioinformatics Analysis Tool for Molecular mechanism of Traditional Chinese Medicine database  was used to search the chemical constituents of Tongxinluo capsules. The TCMSP database is screened based on oral bioavailability (OB) ≥ 30% and drug-like (DL) ≥ 0.18 in the absorption, distribution, metabolism, and excretion (ADME) parameters [P ≥ 0.5 as the standard [Chemical constituents of Tongxinluo capsules were collected through Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform . The targets of chemical components in Tongxinluo capsule were searched and the chemical components with relevant information were screened. The search term “coronary restenosis” in Online Mendelian Inheritance in Man database  and GeneCards database (https://www.genecards.org/) to find and coronary artery restenosis related targets. Through Venny2.1 database (https://bioinfogp.cnb.csic.es/tools/venny), screening of component targets, disease targets, and the intersection of targets as potential targets was performed for Tongxinluo capsule for the treatment of coronary artery restenosis.Construction of target database corresponding to components and target database related to coronary artery restenosis target database TCMSP and BATMAN-TCM database were used to retrieve the targets of each chemical component in Tongxinluo capsules, and the chemical components with relevant information were screened. Targets for each chemical component are standardized using the Search Tool for the Retrieval of Interacting Genes/Proteins database  Network, taking degree value as reference. We calculate the “connectivity,” “closeness centrality (CC),” and “betweenness centrality (BC)” of all nodes to determine the key targets in the network.R3.6.1 software was used for enrichment analysis of GO biological process and KEGG signal pathway, and histogram, bubble diagram, and pathway diagram were drawn for visualization. GO bioanalysis was explained and annotated from three aspects: biological process, molecular function, and cellular location.Based on the above retrieval strategy, a total of 86 Chinese literature and 10 English literature were retrieved, and 36 literature were obtained after removing duplicates. After further screening, 10 Chinese literature were included, with a total of 1318 patients. The literature screening process and results are shown in A total of 1318 patients were included in 10 studies, including 668 in the experimental group and 650 in the control group. The included basic characteristics are shown in The Cochrane Risk Assessment Scale was used to assess the risk of bias and the quality of the 10 included articles was evaluated. In this study, 1 literature  was grou(1) Evaluation and Analysis of Prevention of ISR. A total of 10 literature [2 = 3.50, DF = 9 (P=0.94), I2 = 0%). Due to high experimental homogeneity and zero experimental heterogeneity, the fixed-effect model was adopted. According to the results of meta-analysis , Z = 5.97, P < 0.00001), the effective rate of the experimental group was significantly higher than that of the control group, and the frequency of ISR in the experimental group was significantly lower than that of the control group, with a statistical significance. Therefore, it can be considered that Tongxinluo capsules combined with conventional cardiovascular drugs can improve the clinical treatment efficiency of preventing ISR  Prevention of AP Analysis. A total of 8 literature [2 = 20.17, DF = 7 (P=0.005), I2 = 65%). Due to high heterogeneity, the random-effect model was adopted. According to the results of meta-analysis , Z = 4.23, P < 0.0001), the effective rate of the experimental group was significantly higher than that of the control group, while the number of angina cases in the experimental group was significantly lower than that in the control group with a statistical difference. Therefore, it can be considered that Tongxinluo capsules combined with conventional cardiovascular drugs group can improve the clinical effective rate of prevention of angina pectoris  Analysis of Prevention of MI. A total of 6 literature [2 = 3.84, DF = 5 (P=0.57); I2 = 0%). Due to homogeneity, the fixed-effect model was adopted. According to the results of meta-analysis , Z = 0.91, P < 0.36), the results showed that the effective rate of the experimental group was not significantly higher than that of the control group, which was not statistically significant. Therefore, it is not considered that Tongxinluo capsules combined with conventional cardiovascular drugs can improve the clinical treatment efficiency of preventing myocardial infarction  IL-6 Level. A total of 3 literature [2 = 9.69, DF = 2 (P=0.008), I2 = 79%), indicating large heterogeneity, so the random effect model was adopted. According to the meta-analysis results , Z = 4.00, P < 0.001), there was a statistical difference between the treatment group and the control group. The level of IL-6 in the treatment group was significantly lower than that in the control group, which proved that Tongxinluo capsules had a good function of improving the IL-6 level  Incidence of Total Adverse Cardiovascular Events (TACE). A total of 3 literature [2 = 5.86, df = 2 (P=0.05); I2 = 66%). Due to high heterogeneity, the random effect model was adopted. According to the results of meta-analysis , Z = 3.50, P=0.0005), there was a statistical difference between the treatment group and the control group. The number of patients having adverse cardiovascular events in the treatment group was significantly lower than that in the control group, so Tongxinluo capsules can be considered to have a good therapeutic effect in adverse cardiovascular events  Publication Bias Test Funnel Plots. Publication bias test funnel plots were used to test a publication bias, an outcome measure of clinical efficacy in preventing ISR, showing asymmetrical distribution between studies, suggesting a high possibility of bias  ≥ 30% and drug-like (DL) ≥ 0.18 in the ADME parameters . The BAThttps://www.omim.org/) and GeneCards database (https://www.genecards.org/) to find coronary artery restenosis-related targets. Using Venny 2.1 database (https://bioinfogp.cnb.csic.es/tools/venny), we screened component targets and disease targets the intersection of targets, namely, for Tongxinluo capsules in the treatment of coronary artery restenosis potential targets.Construction of target database corresponding to components and target database related to coronary artery restenosis was performed. TCMSP database and BATMAN-TCM database were used to retrieve the targets of each chemical component in Tongxinluo capsules, and the chemical components with relevant information were screened. Targets for each chemical component are standardized using the STRING database. The targets of chemical components in Tongxinluo capsules were searched and the chemical components with relevant information were screened. The search term “coronary restenosis” in OMIM database ,” and “betweenness centrality (BC)” of all nodes to determine the key targets in the network.2.2.4 GO biological analysis, and KEGG Pathway Analysis R3.6.1 software was used for enrichment analysis of GO biological process and KEGG signal pathway, and histogram, bubble diagram, and pathway diagram were drawn for visualization. GO bioanalysis was explained and annotated from three aspects: biological process, molecular function, and cellular location.P ≥ 0.5 were the screening conditions. A total of 101 chemical components were retrieved after weight removal. See The ADME and prediction target component scores of Tongxinluo capsules were searched by TCMSP and BATMAN-TCM databases, and OB ≥ 30% and DL ≥ 0.18 were obtained. Score ≥ 20 and The chemical targets of Tongxinluo capsules were obtained by searching TCMSP and BATMAN-TCM databases, and 678 targets were obtained after weight removal. A total of 763 disease targets were identified in GeneCards and OMIM databases using “coronary restenosis” as the key word. The drug action targets and disease targets were mapped and compared, and 149 intersection targets were obtained. The intersection results are shown in The common targets were input into STRING database, the species were defined as human, the protein interaction relationship was obtained, and the TSV format file was saved and imported into Cytoscape software for visualization. The results are shown in P < 0.05, R3.6.1 software was used to conduct GO enrichment analysis on the intersection target of Tongxinluo capsules and coronary artery restenosis. “Receptor ligand activity,” “carboxylic acid binding,” “receptor ligand activity,” and 148 items including “steroid hormone receptor activity” (PCI is currently the main means for the treatment of acute coronary syndrome (ACS). Although PCI can effectively and quickly relieve the symptoms of patients, the incidence of postoperative coronary artery restenosis is still high, between 20% and 30%, accompanied by the occurrence of AP and MI, mentioned adverse cardiac and cerebrovascular events (MACCE), etc.The Tongxinluo capsule is widely used in the treatment of cardiovascular diseases. Its main components are ginseng, borneol, leeches, centipede, turtle worm, peony root, etc., which have the effects of antiplatelet aggregation and antithrombosis and lowers blood lipids. Combination drug therapy can effectively reduce the incidence of restenosis after PCI.Network pharmacology partial coronary restenosis ISR is a serious problem in patients undergoing PCI. In this study, the ADME and predictive target component scores of single drug in Tongxinluo capsules were searched through the advantages of network pharmacology, which is broad, multiaspect, and multitarget, to explore the possible mechanisms of active components, key targets, and potential pathways in the treatment process, so as to provide scientific basis for the treatment of coronary artery restenosis by Tongxinluo capsules.A total of 101 effective components related to Tongxinluo capsule in the treatment of coronary artery restenosis were identified. However, due to the complex composition of the Tongxinluo capsule, the core components in the treatment of coronary artery restenosis cannot be determined temporarily.R3.6.1 software was used to conduct GO enrichment analysis on the intersection targets of Tongxinluo capsules and coronary artery restenosis. Through KEGG pathway analysis of common targets, it was found that the age-rage signaling pathway may indirectly improve diseases such as angiogenesis, inflammation, and atherosclerosis through a series of signal transduction by acting on AGEs molecules. It can promote the treatment of coronary artery restenosis with Tongxinluo capsules.κB. It directly acts on VEGF, McP-1, TNF-α, IL-6, IL-1, and IL-8 genes, and ultimately indirectly improves angiogenesis, inflammation, and atherosclerosis  Only two of the literature included in this study MACCE, so the sample size was insufficient to conduct effectiveness analysis; (2) the quality of the literature included in this study was uneven, only two literature clearly pointed out that the blind method was applied, so various biases might be generated; (3) a small number of research literature were included, resulting in a small sample size, which may produce bias; (4) the course of treatment and dose selected in the included literature are inconsistent, which may cause bias; (5) most of the included literature have few indicators and cannot be effectively analyzed; (6) network pharmacology is based on the results of network data and computational simulation and has not been verified by Based on the meta-analysis and network pharmacology research techniques, this study first evaluated the clinical efficacy of Tongxinluo capsules in treating ISR and analyzed its potential mechanism of action. The results showed that in 10 studies, the experimental group was significantly better than the control group in the treatment of ISR, AP, inflammatory cytokine IL-6, and the incidence of total adverse cardiovascular events. However, there was no significant difference in the treatment of MI between the control and treatment groups. A total of 101 effective components related to Tongxinluo capsules in the treatment of coronary artery restenosis were identified. There were 148 related pathways, mainly involving the age-rage signaling pathway and cell senescence signaling pathway, etc. Tongxinluo capsules may improve coronary artery restenosis through the age-rage signaling pathway and cell senescence signaling pathway.


YuPingFeng Granules (YPFGs) is an herbal formula clinically used in China for more than 100 years to treat pneumonia. Nevertheless, the mechanism of YPFG in pneumonia treatment has not been established. This network pharmacology-based strategy has been performed to elucidate active compounds as well as mechanisms of YPFG in pneumonia treatment.  First, active compounds of YPFG were identified in the traditional Chinese medicine systems pharmacology (TCMSP) database, and then the targets related to the active compounds were obtained from TCMSP and Swiss Target Prediction databases. Next, using DisGeNET, DrugBank, and GeneCards databases, we got therapeutic targets of pneumonia and common targets between pneumonia targets and YPFG. After that, a protein-protein interaction (PPI) network of pneumonia composed of common targets was built to analyze the interactions among these targets, which focused on screening for hub targets by topology. Then, online software and the ClusterProfiler package were utilized for the enrichment analysis of gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) data. Finally, the visualization software of Autodock was used for molecular docking among the hub target proteins.  10 hub genes were selected by comparing the GO and KEGG functions of pneumonia targets with those of the common targets of YPFG and pneumonia. By using molecular docking technology, a total of 3 active ingredients have been verified as being able to combine closely with 6 hub targets and contribute to their therapeutic effects.  This research explored the multigene pharmacological mechanism of action of YPFG against pneumonia through network pharmacology. The findings present new ideas for studying the mechanism of action of Chinese medicine against pneumonia caused by bacteria. Pneumonia is an infectious inflammation of the alveoli, lung interstitium, and distal airways. Its etiologic agents include viruses, bacteria, and other pathogens. Lower respiratory tract infections were the third leading cause of total years of life lost (YLLs) in 2016 . With rePneumonia including COVID-19 has resulted in hospital services becoming overwhelmed . CurrentYuPingFeng Granules (YPFGs) are a complex and classic traditional Chinese prescription. It is composed of FangFeng1 (FF), BaiZhu2 (BZ), and HuangQi3 (HQ). YPFG is commonly used to treat inflammation-related diseases, including asthma , chronicTo decipher the mechanisms of YPFG on pneumonia, we searched for YPFG targets as well as pathways of YPFG in pneumonia treatment. To screen the active compounds of the 3 herbs in YPFG, a search in TCMSP  , GeneCards database (the score of targets were set as no less than 5), and DisGeNET database (the score-gda of targets were set as no less than 0.2). Standardization of these targets were also carried out in UniProt.Homo sapiens” as the organism and at ≥0.4 as the confidence score. Other parameters were the default settings.String  is a datk core = 2, and degree cutoff = 2).Cluster analyses are aimed at screening similar or same nodes as well as protein complexes from complex PPI networks . ClusterConsidering intersections between pneumonia targets and YPFG, shared targets were identified. A PPI network for disease targets, a PPI network for common targets, and a network for common targets active compounds, as well as a disease-hub gene active compounds network were built and their visualization is carried out by utilizing Cytoscape  (versionhttps://www.kegg.jp/kegg/kegg1.html) integrating chemistry, the genome, and system function data. “ClusterProfiler” in R Studio Software was utilized for GO and KEGG analyses, with the screening criterion adjusted to p ≤ 0.05[GO annotations are utilized to determine the roles of gene products based on three aspects: cell components (CCs), molecular functions (MFs), and biological processes (BPs). KEGG is a database . By using the string database online, we obtained the PPI network pneumonia targets in GO enrichment analysis revealed that activation of CCs related to pneumonia occurs on the external side of the plasma membrane, membrane raft, and membrane microdomain. The molecular functions of pneumonia would be highly associated with receptor-ligand activities, cytokine activities, as well as cytokine-receptor binding. The BPs of pneumonia would be highly associated with cytokine-mediated signaling, leukocyte migration, and positive regulation of cytokine production in Figures p ≤ 0.05). We obtained top10 significantly enriched terms in BPs and MFs, the top 9 significant terms in CCs, and 10 significantly enriched KEGG pathways .We performed KEGG and GO analyses on the 40 shared targets by the ClusterProfiler software package of the RStudio. Then, 9 CCs, 60 MFs, 1540 BPs, and 73 KEGGs were identified , IL-17 signaling pathway (hsa04657), and TNF signaling pathway (hsa04668). Although less than five hub genes are enriched in the NF-kappa B signaling pathway (hsa04064) [By comparing the GO and KEGG functions of pneumonia targets with those of the common targets of YPFG and pneumonia, 9 CCs that were overlapping, 30 MFs that were overlapping, 1232 overlapping BPs, and 63 overlapping KEGG pathways were identified. Because hub genes play vital roles in pneumonia treatment via YPFG, we chose overlapping GO, as well as KEGG terms containing hub genes for subsequent analyses. Then, we identified one key cellular component, which contained no less than 3 hub genes, namely, collagen-containing extracellular matrix (GO:0062023). We obtained 17 key biological processes, which contained more than 5 hub genes. We obtained 4 key molecular functions, which contained more than 5 hub genes. We obtained 13 key KEGGs, which contained more than 5 hub genes. The key molecular functions were mainly associated with cytokine activities (GO:0005125), receptor-ligand activity (GO:0048018), and cytokine receptor binding (GO:0005126). The key biological processes were mainly associated with leukocyte migration (GO:0050900), positive regulation of cell adhesion (GO:0045785), and response to lipopolysaccharide (GO:0032496). The key KEGGs were mainly related to Cytokine-cytokine receptor interaction (hsa04060), on hsa051, IL-17 sWe build the pneumonia-hubgenes-activecompounds-YPFG network  containiThree key active components and some hub genes act as ligands and receptors, respectively. The result of molecular docking is shown in Yersinia infection pathway , as well as the NF-kappaB signaling pathway . By comparing the hub genes with the top ten genes of pneumonia, we found 5 overlapping genes , which might interpret on how the YPFG exerts a therapeutic effect in some types of pneumonia but not all types of pneumonia. Therefore, we will focus on discussing these genes and pathways. In addition, Wang et al. [We investigated the mechanisms of YuPingFeng Granules in pneumonia treatment using network pharmacology. Performing the enrichment analyses of common targets as well as pneumonia targets, respectively, and selecting their overlapping terms, we found that these genes are highly involved in host immune-inflammatory responses, inhibiting cell migration. Li et al.  confirmeg et al.  exposed Pneumonia is associated with infectious inflammations of the lung interstitium, alveoli, as well as distal airways, and its etiologic agents include all kinds of pathogens. Those pathogens induce the host to produce a high abundance of inflammatory factors and cytokines, including IL-6, IL-1B, IL-10, and TNF –40. HighPseudomonas aeruginosa, Riquelme et al. [α) and bacterial particles and is facilitated by transcriptional factors, activator protein-1 (AP-1), and NF-κB [Lappalainen et al.  reportede et al.  found sue et al.  found thnd NF-κB . In addind NF-κB . Variousnd NF-κB . In geneThrough KEGG analyses, it was established that proinflammatory cytokines associated with the IL-17 signaling pathway and synthesis of inflammatory mediators and inflammatory cytokines facilitated by the TNF signaling pathway were associated with inflammatory responses in the lungs. Autoimmune pathology induced by the IL-17 signaling pathway and leukocyte recruitment facilitated by the TNF signaling pathway were associated with host immune responses. Responses to lipopolysaccharides (LPSs) were the highly enriched biological process. As we all know, LPS is a component of the outer wall of the cell wall of Gram-negative bacteria, and the IL-17 signaling pathway mainly occurs in the case of bacterial infection, which suggests that YPFG may be mainly suitable for bacterial pneumonia.κB from translocating to the nucleus, which improves the anti-inflammatory response [In vitro experiment demonstrates that wogonin (MOL000173) shows a significant neuroprotective effect by inhibiting oxidation and inflammation. These protective effects are through the reduction of caspase-3, TNF, and toll-like receptor 2 expression [In vivo experiments in mice suggest that wogonin inhibits the PI3K/Akt/NF-κB signaling pathway, reducing autophagy and inflammation, and then reducing renal tubular cell damage [Through constructing the pneumonia-hubgenes-activecompounds-YPFG network, we obtained pivotal active compounds. It is found quercetin (MOL000098) negatively regulates the TLR4 signaling pathway, that is, induced by LPS. Quercetin reduces the expression of TLR4 in peripheral blood mononuclear cells and macrophages of humans and prevents NF-response . Some reresponse . In vitrpression . In vivol damage .α, IL-1β, and IL-6 by affecting TLR4-dependent NF-κB signaling pathways [Staphylococcus aureus virulence factor Hla. The study also observed that kaempferol shows a good protective effect on MRSA-induced pneumonia in mice. Through the IL-17 signaling pathway, γδT cells that can produce IL-17 are shown to control neutrophil influx under infection [Yersinia lung infection are severe pulmonary inflammation and a high abundance of neutrophil infiltration [Yersinia infection pathway, there is a great risk of death. In our overlapping GO enrichment analysis, leukocyte migration was the most important BP, suggesting that YPFG could inhibit a large number of neutrophils moving to the lung. Molecular docking is a key tool in structural molecular biology and computer-assisted drug design. The goal of ligand-protein docking is to predict the predominant binding mode of a ligand with a protein of a known three-dimensional structure. Successful docking methods search high-dimensional spaces effectively and use a scoring function that correctly ranks candidate dockings. Docking can be used to perform virtual screening on large libraries of compounds, rank the results, and propose structural hypotheses of how the ligands inhibit the target, which is invaluable in lead optimization. Through the verification of molecular docking technology, the 3 active ingredients can combine closely with the hub targets and play a therapeutic role. Meanwhile, the results of molecular docking also exposed the active ingredients of YPFG could tack a part in modulating the progression of pneumonia via MMP9, CCL2, IL-1B, IL-6, CXCL8, and TNF. However, there were still some limitations to the present study. First, due to the slow update of the TCMSP database, the active compounds were not selected enough. Thus, we failed to consider other targets within the datasets. Second, moreover, the lack of validation in vitro and in vivo experiments is a restriction of the study. Furthermore, investigations are needed to confirm the role of active compounds in pneumonia in vivo and to explore its precise mechanisms.Kaempferol (MOL000422) downregulates the levels of inflammatory markers, such as TNFpathways . A studypathways  has demonfection . Treg cenfection . The chaltration  because YPFG may be mainly suitable for bacterial pneumonia. The multitarget action mode of YPFG could effectively treat some types of pneumonia, which are mainly involved in the host immune-inflammatory response and inhibiting cell migration.For the treatment of pneumonia, traditional Chinese medicine may provide a new direction. Our research has theoretically proved that YPFG can effectively treat pneumonia and provides theoretical support for the continued clinical use of YPFG.


Since osteoporosis critically influences the lives of patients with a high incidence, effective therapeutic treatments are important. Quercetin has been well recognized as a bone-sparing agent and thus the underlying mechanisms warrant further investigation. In the current study, the network pharmacology strategy and zebrafish model were utilized to explain the potential pharmacological effects of quercetin on osteoporosis. The potential targets and related signaling pathways were explored through overlapping target prediction, protein–protein interaction network construction, and functional enrichment analysis. Furthermore, we performed docking studies to verify the specific interactions between quercetin and crucial targets. Consequently, 55 targets were related to osteoporosis disease among the 159 targets of quercetin obtained by three database sources. Thirty hub targets were filtered through the cytoNCA plugin. Additionally, the Gene Ontology functions in the top 10 respective biological processes, molecular functions, and cell components as well as the top 20 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were depicted. The most significance difference in the KEGG pathways was the TNF signaling pathway, consisting of the Nuclear Factor Kappa B Subunit (NF-κB), Extracellular Regulated Protein Kinases (ERK) 1/2, Activator Protein 1 (AP-1), Interleukin 6 (IL6), Transcription factor AP-1 (Jun), and Phosphatidylinositol 3 Kinase (PI3K), which were probably involved in the pharmacological effects. Moreover, molecular docking studies revealed that the top three entries were Interleukin 1 Beta (IL1B), the Nuclear Factor NF-Kappa-B p65 Subunit (RelA), and the Nuclear Factor Kappa B Subunit 1 (NFKB1), respectively. Finally, these results were verified by alizarin red-stained mineralized bone in zebrafish and related qPCR experiments. The findings probably facilitate the mechanism elucidation related to quercetin anti-osteoporosis action. Osteoporosis (OP) is a multifactorial skeletal disease with an increased risk of fracture . With thEucommia ulmoides and Epimedium brevicornu Maxim on OP through network pharmacology analysis, where the hub genes included Mitogen-Activated Protein Kinase 1 (MAPK1), Tumor Necrosis Factor (TNF), AKT serine/threonine kinase 1 (AKT1), Cyclin D1 (CCDN1), Fos Proto-Oncogene (FOS), Jun, and Tumor Protein P53 (TP53) [Sinomeniicaulis, Rhizoma drynariae, and Astragaloside IV, etc. [With the emergence of systems biology, network pharmacology has become a promising paradigm of drug development . Numerou3 (TP53) . The act3 (TP53) . In the IV, etc. .15H10O7) is a naturally occurring flavonoid which is an active ingredient in TCM preparations. This ingredient is present ubiquitously in fruits and vegetables with a variety of biological activities, such as effectively regulating cell cycle process and signals and auxin transport related to plant growth and development [Quercetin , 48 molecular functions (MF), and 21 cell components (CC). All of the top 10 key targets were graphed using the bioinformatics online platform A. The BPp-value (≤0.05) to elucidate the critical pathways among the 55 potential targets in terms of OP therapy [Additionally, we filtered the KEGG pathway according to the  therapy ,30. UltiAmong the KEGG-enriched pathways, the TNF signaling pathways had the most significance difference. The predicted targets in the TNF signaling pathway are shown in The results of the target-pathway network indicated that nine genes appeared frequently (≥10 times) in the top 20 KEGG pathways , which sThrough a molecular docking analysis, the binding and interaction between the target proteins and the small molecules could be predicted. The molecular docking of QCT with nine important targets IL1B, RelA, NFKB1, MAPK1, TNF, IL6, Jun, MAPK3, and PIK3CA were studied. These targets were selected because they both represented the key nodes of the PPI network and played significant roles in the KEGG signaling pathways. The molecular docking results are shown in We selected the top three genes with a high affinity and then drew a 3D docking map with PyMOL and a 2D diagram with LigPlus+. The docking results suggested that the receptor–ligand interactions of the QCT and OP were involved in hydrophobic interactions and polar interactions. The details are described below.In In addition, the results in As displayed by p < 0.05). Compared with the model group, the BMA and IOD of the zebrafish skulls in the positive control Etidronate disodium (ED) and QCT groups were significantly increased at 12.5 and 25 µM (tnf-α (p < 0.5), il1β (p < 0.01), and p65 increased in the DEX group while they reduced in the ED and QCT groups , a kind of glucocorticoid, was used to construct a zebrafish model . We usednd 25 µM B,C. In oT groups D. These With the rapid growth of the global population and the increasingly serious problem of population aging, the OP disease is a growing health problem worldwide . Hence, Firstly, 55 common targets screening for QCT and OP were illustrated in the Venn diagram. In the PPI network, 30 key targets were picked out according to four correlations . The results of the GO Enrichment analysis suggested that the mechanism of action was mainly involved in 186 biological processes (BP), 48 molecular functions (MF), and 21 cell components (CC). In terms of the KEGG enrichment analysis, the pathways in cancer (hsa05200), Influenza A (hsa05164), the TNF signaling pathway (hsa04668), Chagas disease (American trypanosomiasis) (hsa05142), the Estrogen signaling pathway (hsa04915), etc., were the vital signaling pathways linked to anti-OP. The targets  were enriched in the pathways in cancer. A therapeutic mechanism for the pathways in cancer has been observed for other active TCM molecules, such as the Xianlinggubao capsule, resveratrol, and Wuling Powder . The infp-value). TNF had an important effect on bone metabolism which is consistent with that previously reported in the Zhao’s study [Among the KEGG-enriched pathways, the TNF signaling pathways had the most significance difference  were frequently (>10 times) present in the top 20 KEGG pathway analyses. To further explore the underlying mechanisms of the effects, we performed a molecular docking of the nine targets. The docking scores of QCT and the frequently (>10 times) present genes were found to be negative, indicating that they could bind spontaneously. The top three goals for the docking scores were IL1B, RelA, and NFKB1, respectively, since a score  indicated a strong binding activity . These til1β (p < 0.01), tnf-α (p < 0.5), and RelA/p65 decreased compared with the DEX model group, which was consistent with the network analysis results.Zebrafish could be used to construct an osteoporosis model because of their transparent body and bone structure, their metabolism, as well as their signal pathway which is highly similar to human beings . In thisIn short, the potential targets of the pharmacological mechanism of QCT on anti-OP activity have been uncovered with in silico and in vivo models. However, the present study highly relies on network pharmacological analysis to predict the potential intersection targets of QCT and OP. In fact, the targets from websites are not comprehensive owing to the limited literature. Hence, many targets that probably exhibit crucial effects have not yet been predicted by network analysis. In further research, this limitation can be well resolved through multi-omics integration with in vivo models. Taken together, the presented findings indicated the potential anti-OP mechanism of QCT, which may provide a broad direction for further studies on the exact mechanism of QCT in the treatment of OP. However, the exact regulation mechanism still needs to be further verified in mammalian models in consideration of further clinical applications.https://www.genecards.org (accessed on 27 October 2021)), DisGeNET (http://www.disgenet.org (accessed on 10 February 2021)), OMIM (https://www.omim.org (accessed on 29 September 2021)), and TTD (http://db.idrblab.net/ttd/ (accessed on 29 September 2021)). GeneCards is a well-established, searchable, and integrative database that offers concise genomic-related information on annotated and predicted human genes [We screened OP-related targets from GeneCards (an genes . DisGeNEan genes . OMIM isan genes . TTD proan genes .https://tcmsp-e.com/ (accessed on 20 November 2013)) using QCT as the search term. The TCMSP is a system pharmacology platform focusing on Chinese herbal medicines that records the relationships between drugs, targets, and diseases [https://pubchem.ncbi.nlm.nih.gov/ (accessed on 9 August 2021)), and the geometry of QCT was optimized in Avogadro (Version 1.0.2) with the MM94 force field. The optimized 3D structure was imported into the TCMSP, PubChem, and Swiss target prediction (http://www.swisstargetprediction.ch/ (accessed on 20 July 2019)) to achieve the QCT-related targets.Briefly, we gained the structure and target information of QCT from the TCMSP (diseases . The 3D http://www.biovenn.nl/index.php (accessed on 20 October 2008)) [http://string-db.org (accessed on 35 August 2021)). “Homo sapiens” was selected as the parameter in the column of species. The minimum interaction score required was higher than 0.7; meanwhile, the max number of interactors was no more than 50, under hiding the disconnected nodes. The PPI was subjected to a network topological analysis by Cytoscape 3.8.2 software [The QCT-related and OP-related targets were uploaded to the website to draw the Venn diagram (r 2008)) . The intsoftware . The plusoftware . The gresoftware . BC, a msoftware . CC refesoftware . SC charsoftware .https://david.ncifcrf.gov (accessed on 15 December 2021)) for the GO functions and KEGG pathways enrichment analysis [p-value ≤ 0.05 was designated as the threshold value for statistical significance. A GO analysis could further explain the intersection genes in the molecular function, biological processes, and cellular composition of anti-OP processes. The KEGG enrichment analysis revealed the major signaling pathways involved in anti-OP for QCT. The top 10 GO terms and 20 KEGG pathways were visualized through column and bubble charts, respectively, using the online platform WeiShengxin (http://www.bioinformatics.com.cn/ (accessed on 10 October 2021)). Additionally, a target-pathway network was described by Cytoscape software. Potential hub targets of QCT toward anti-OP activity in the TNF signaling pathway were constructed using the KEGG mapper.The functional annotation of the core targets were performed using the DAVID database ). The docking pockets were predicted through the DoGSiteScorer server (https://proteins.plus/ (accessed on 23 November 2021)) [Among the results of the KEGG pathway analysis, key targets which appeared frequently (>10 times) were docked with QCT. The crystal structures of the targets were obtained from the PDB protein database (r 2021)) . The prer 2021)) . Subsequr 2021)) . Additior 2021)) .The wild type zebrafish were cultured in an E3 embryo culture medium supplied with a 0.003% 1-phenyl-2-thiourea (PTU) solution at 28 °C. These embryos at 5 dpf were placed into a six-well plate, each of who’s well contained 20 larvae. The zebrafish larvae were divided into four groups including the control group, model group, model + positive rescue group, and model + compound group. The control group was maintained in the medium with a working-PTU solution. The model group was treated with 5 μM DEX. The model + positive rescue group and model + compound group were exposed to DEX and 300 mg/L ED, DEX and 12.5 μM QCT, and DEX and 25 μM QCT, respectively. The processing time was from 5 to 9 days.2O2, 0.5% KOH) for 1 h. Next, the larvae were washed with a Polybutylece Terephthalate (PBT) solution for 5 min, which was repeated 3 times. A gradient elution was immediately carried out with 25% methanol-75% PBT, 50% methanol-50% PBT, and 100% methanol for 5 min each time, respectively. Subsequently, the zebrafish were stored at—20 °C overnight with 20% DMSO-80% methanol. In the next day, the samples were rehydrated with a PBT/methanol series . Then, all the samples were stained with alizarin red at room temperature in the dark for more than 12 h. Finally, the zebrafish were washed with PBT until colorless and were stored with glycerin. The dorsal aspect of the zebrafish head was photographed using a fluorescence stereomicroscope (Leica M205 FA stereomicroscope). The staining area and IOD were calculated by Image-ProPlus 6.0 software to investigate the bone mineralization area and the bone mineral density.At 9 dpf, all the zebrafish larvae were anesthetized by 0.02% tricaine. After the removal of the tricaine solution, the zebrafish were fixed in 4% paraformaldehyde at 4 °C overnight and were transferred into a bleach solution . The mRNA expression levels were detected by a real-time fluorescence quantitative PCR kit . The results were normalized to β-actin expression and quantified by the 2−ΔΔCt method. Forward and reverse primers were listed in The total RNA of the zebrafish was extracted from different groups of larvae (n = 40 larvae/group) using TransZol Up reagent (ET111–01). Then, the RNA was reverse transcribed into cDNA through a reverse transcription kit   were identified. Moreover, molecular docking studies revealed that the targets  displayed the top three strongest binding affinity, which probably explained the anti-OP activity of QCT. Furthermore, the results of the zebrafish model and the qPCR experiments were also consistent with the action. Taken together, the presented findings systematically analyzed the potential mechanism of QCT in the treatment of OP, which may provide a broad direction for further studies on the exact mechanism of QCT in the treatment of OP.


Atherosclerosis (AS) is a vascular disease with plaque formation. Unstable plaques can be expected to result in cardiovascular disease, such as myocardial infarction and stroke. Studies have verified that long noncoding RNAs (lncRNAs) play a critical role in atherosclerotic plaque formation (APF), including MALAT1, GAS5, and H19. A ceRNA network is a combination of these two interacting processes, which regulate the occurrence and progression of many diseases. However, lncRNA-associated ceRNA network in terms of APF is limited. This study sought to discover novel potential biomarkers and ceRNA network for APF. We designed a triple network based on the lncRNA-miRNA and mRNA-miRNA pairs obtained from lncRNASNP and starBase. Differentially expressed genes (DEGs) and lncRNAs in human vascular tissues derived from the Gene Expression Omnibus database  were systematically selected and analyzed. A ceRNA network was constructed by hypergeometric test, including 8 lncRNAs, 243 miRNAs, and 8 mRNAs. APF-related ceRNA structure was discovered for the first time by combining network analysis and statistical validation. Topological analysis determined the key lncRNAs with the highest centroid. GO and KEGG enrichment analysis indicated that the ceRNA network was primarily enriched in “regulation of platelet-derived growth factor receptor signaling pathway,” “negative regulation of leukocyte chemotaxis,” and “axonal fasciculation.” A functional lncRNA, HAND2-AS1, was identified in the ceRNA network, and the main miRNA (miRNA-570-3p) regulated by HAND2-AS1 was further screened. This present study elucidated the important function of lncRNA in the origination and progression of APF and indicated the potential use of these hub nodes as diagnostic biomarkers and therapeutic targets. Atherosclerotic cardiovascular disease is a major threat to human health and quality of life in modern society . The forNoncoding RNAs (ncRNAs) refer to the functional RNAs that cannot encode proteins in transcriptome, including microRNAs (miRNAs) and long noncoding RNAs (lncRNAs). miRNAs are a class of highly conserved single-stranded noncoding small RNAs with posttranscriptional regulatory activity. Long noncoding RNAs (lncRNAs) are longer than 200 nucleotides with no protein coding capacity or limited protein coding potential –7. AlthoCompetitive endogenous RNA (ceRNA) is the basis of a novel regulatory mechanism between noncoding RNA and coding RNA. lncRNA can be used as ceRNA to competitively bind miRNA with target genes, thereby reducing the inhibitory effect of miRNAs on target genes . Therefohttp://bioinfo.life.hust.edu.cn/lncRNASNP/)  > 1.5 were applied.To identify the main DEGs between normal blood vessels and the blood vessels containing atherosclerotic plaques, microarray data GSE97210 and GSE43292 were downloaded from the GEO database (lgorithm . DEGs wehttps://blast.ncbi.nlm.nih.gov/Blast.cgi).Since the differentially expressed lncRNAs that have been screened out were replaced by sequence numbers of probes, they were further reannotated through the BLAST software  according to the Benjamini and Hochberg method  > 1.5 and adjusted 1 Tables .First, the lncRNASNP database was used to predict differentially expressed miRNAs (DEMis) associated with DELs. The starBase V2.0 database was used to predict miRNAs that interact with DEGs. Then, a hypergeometric test was utilized to further detect the significance of these lncRNA-miRNA pairs and mRNA-miRNA pairs. Finally, we constructed a new lncRNA-miRNA-mRNA network related to APF in Cytoscape software . It consEnrichment analysis of GO classification and KEGG pathway was performed on the DEGs in APF-related networks by employing ClueGO plugin in Cytoscape software. The results are shown in First, we used Cytoscape software to calculate the topology parameters of the nodes in the APF-related ceRNA network. Then, all of the nodes' topological parameters in the network were ranked . It was APF is a complex disease that has brought a heavy burden to people all over the world. Since the pathogenesis and process of this disorder are complex, it is necessary to solve the problem through a more comprehensive perspective. In recent years, with the rapid development of high-throughput genomics, noncoding RNA has received extensive attention. Noncoding RNA includes lncRNA and miRNA, which are involved in the regulation of multiple biological processes . ceRNA iFirst of all, construct a global triple network based on the ceRNA theory by using the interactive data of lncRNASNP and starBase . Then, wAPF has been shown to be closely related to inflammation and oxidative stress , 36. Stuα (HIF-1α) [α has also been confirmed to promote macrophage necroptosis by regulating miRNA-210 and miRNA-383 [The functionality of lncRNA HAND2-AS1 has been well characterized in several types of human cancers , 43. Fur(HIF-1α) . HIF-1α iRNA-383 . HoweverAs far as we know, this research constructed a ceRNA network containing lncRNA HAND2-AS1, hsa-miRNA-570-3p, and APF-related genes in APF. Furthermore, KEGG analysis has shown that the “regulation of platelet-derived growth factor receptor signaling pathway” may be the main pathway resulting in APF. It was previously reported that platelet-derived growth factor receptor (PDGFR) signaling pathway could regulate smooth muscle cell (SMC) migration and proliferation in the vascular wall, leading to increased predisposition to cardiovascular disease . It has In this study, a global triple network including lncRNAs, miRNAs, and mRNAs was constructed based on the ceRNA hypothesis, and then, a regulatory network of APF was screened. lncRNA HAND2-AS1, hsa-miRNA-570-3p, DPP4, MYOCD, CNTN4, and CNTN1 were identified as the key genes. These findings complemented our understanding of APF and may provide potential diagnostic biomarkers or therapeutic targets in APF.


Our study majorly utilizes network pharmacology combined with molecular docking to explore the latent active components and associated pivotal targets of Guyuan Decoction (GYD) in the treatment of frequently relapsing nephrotic syndrome (FRNS).in vitro and to determine the effects of luteolin on modeled cells.All active components and latent targets of GYD were retrieved from TCMSP database. The target genes for FRNS in our research were obtained from the GeneCards database. The drug-compounds-disease-targets (D-C-D-T) network was established using Cytoscape 3.7.1. STRING database was applied to observe the protein interaction. Pathway enrichment analyses (GO and KEGG) were conducted in R software. Moreover, molecular docking was employed to further validate the binding activity. MPC-5 cells were treated with adriamycin to mimic FRNS via regulating AKT1 and CASP3.A total of 181 active components and 186 target genes of GYD were identified. Meanwhile, 518 targets related to FRNS were also revealed. Based on the intersection using a Venn diagram, 51 common latent targets were recognized to be associated with active ingredients and FRNS. Additionally, we identified the biological processes and signaling pathways involved in the action of these targets. Molecular docking analyses illustrated that AKT1 and CASP3 interacted with luteolin, wogonin, and kaempferol, respectively. Moreover, luteolin treatment enhanced the viability but inhibited the apoptosis of adriamycin-treated MPC-5 cells Our study forecasts the active compounds, latent targets, and molecular mechanisms of GYD in FRNS, which helps us to understand the action mechanism of GYD in FRNS comprehensive treatment. Nephrotic syndrome is the most common glomerular disease in childhood, with an average incidence of 2–16.9 per 100,000 children worldwide . The patAstragali Radix (Huangqi), Pseudostellariae Radix (Taizishen), Rhizoma Atractylodis Macrocephalae (Baizhu), Poria cocos (Fuling), Saposhnikoviae Radix (Fangfeng), Glycyrrhizae Radix et Rhizoma (Gancao), Phellodendri Chinensis Cortex (Huangbai), Amomi Fructus (Sharen), and Stigma maydis (Yumixu). Previously, Wen X et al. analyzed the latent targets and molecular mechanisms of Astragali Radix in the treatment of nephrotic syndrome using network pharmacology [Poria cocos improved nephrotic syndrome in rats via restraining water and sodium channels [Astragali Radix, Pseudostellariae Radix, Rhizoma Atractylodis Macrocephalae, and Poria cocos are the most commonly used core herbal medicine for the treatment of chronic kidney disease [As one of the most popular complementary and alternative medicine models in China, traditional Chinese medicine (TCM) is gradually accepted by foreigners due to its obvious curative effect, abundant resources, and low toxicity, which is increasingly used in Western countries . Guyuan macology . Anotherchannels . Based o disease . These aNetwork pharmacology, which is firstly proposed by Andrew L Hopkins, a pharmacologist at Dundee University in 2007, is a new discipline based on systems biology, computer technology, network biology, and other emerging technologies to select specific signal nodes for multi-target drug molecular design . NetworkThis study, accordingly, intends to screen the main active components of GYD and predicts its targets based on the method of network pharmacology, while constructing the visualized network relationship of drug-components-disease-targets (D-C-D-T) at the same time. By doing so, some theoretical support for more comprehensive and in-depth exploration of the pharmacodynamic material basis and molecular mechanism of GYD can be provided, which, we hope, can contribute to the clinical application and further experimental research of GYD.http://tcmspw.com/tcmsp.php). In combination with the analyses of the existing literature, 6 of 9 compounds were selected finally, namely, atractylenolide, atractylon, prim-o-glucosylcimifugin, astragaloside, glycyrrhizic acid, and glycyrrhetinic acid [Nine TCM compounds in GYD were obtained from the TCMSP database  criteria, followed by the prediction on the targets of all compounds . For theHomo sapiens’. We also used the UniProt database (http://www.uniprot.org/) to correct and unify the names of these targets, and then applied the Swiss Target Prediction database (http://www.swisstargetprediction.ch/) to supplement the information of these target genes.The genes related to the active components of GYD in this study were retrieved from the TCMSP database under the condition of ‘https://www.genecards.org/) using the keyword of ‘frequently relapsing nephrotic syndrome’.The target genes for FRNS in our research were also obtained from the GeneCards database (https://bioinfogp.cnb.csic.es/tools/venny/), we inputted the targets of chemical components and FRNS, respectively. A Venn diagram was subsequently drawn to obtain the common targets of components and FRNS.On the Venny2.1 online software mapping tool platform . In detail, for the construction of a PPI network, the species restriction was set to ‘Homo sapiens’, and the required minimum interaction score > 0.4 was selected. The R package was exploited to screen central proteins and rank them according to the degree of association between proteins.The association in the retrieved targets of GYD active ingredients and FRNS was analyzed through STRING database  of ingredients and FRNS was/were transformed into entrezID. Then, we installed ‘clusterProfiler’ package in R software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses on the key target genes were performed at http://www.rcsb.org/pdb/home/home.do) was taken to acquire the 3D structure of proteins.In the target interaction network obtained from PPI analysis, 2 targets with maximum count scores were selected, namely, AKT1 and CASP3. Thereafter, we verified the compound-target correlation with the help of molecular operating environment (MOE) software (v2015.10). Then, PDB database (2.Mouse kidney podocytes MPC-5 (CTCC-400-0327) purchased from Meisen Chinese Tissue Culture Collections (China) was maintained in RPMI-1640 medium  containing 10% fetal bovine serum  and 1% penicillin-streptomycin solution  at 37 °C with 5% COin vitro, MPC-5 cells were stimulated with 10 µM adriamycin  for 6 h (h).To mimic FRNS 4 cells/well and treated with 100, 150, 200 or 250 μM luteolin  for 48 h to screen out the appropriate drug concentration. After the completion of drug treatment, 10 μL of CCK-8 reagent  was added to incubate with the MPC-5 cells. After the reaction time of 4 h, the 96-well plate was placed under a microplate reader  to test the absorbance (at 450 nm) of cells under different treatment conditions.MPC-5 cells were seeded into a 96-well plate at a density of 1 × 10Thereafter, CCK-8 assay was performed again to determine the effect of LUT  on the viability of ADR-treated MPC-5 cells.Annexin V-FITC Apoptosis Detection Kit (C1062) available from Beyotime (China) was utilized to test the apoptosis of cells. MPC-5 cells were resuspended in 195 μL Annexin V-FITC binding buffer, reacted with 5 μL Annexin V-FITC and mixed with 10 μL propidium iodide (PI) staining solution for 20 min (min). Finally, the cell apoptosis was detected using the flow cytometer .Total protein in MPC-5 cells was extracted using the RIPA reagent . Then, the concentration of protein samples was quantified by BCA protein quantitation kit . Next, sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) gels were exploited to separate the protein sample, which was then moved to polyvinylidene fluoride membranes . The membranes were sequentially soaked in blocking solution to reduce nonspecific binding and incubated with primary antibodies against Cleaved (Clea)-caspase-3 , AKT1 , phosphorylated (p)-AKT1 , and GAPDH  at 4 °C overnight. Next, the membranes were incubated with the secondary antibodies including goat anti-rabbit IgG  and rabbit anti-mouse IgG  for 2 h. Excellent Chemiluminescent Substrate Detection Kit  was used to measure the protein bands, and ImageQuant LAS 4000MINI Ultra-Sensitive Chemiluminescence Imager  was employed to scan the bands. GAPDH served as the loading control of this assay.post hoc test. The data with p < 0.05 were deemed to be statistically significant.All results from at least triplicate experiments were expressed as mean ± standard deviation. All statistical analyses were carried out using SPSS 20.0 . One-way ANOVA was used to evaluate the significance among multiple groups, followed by the Bonferroni The thresholds of OB ≥ 30% and DL ≥ 0.18 were set in the TCMSP database to screen the active ingredients of 9 TCMs in GYD. In this study, atractylenolide, atractylon, prim-o-glucosylcimifugin, astragaloside, glycyrrhizic acid, and glycyrrhetinic acid were selected, and a total of 181 active ingredients were obtained. Next, we inputted the targets corresponding to the active ingredients into the UniProt database and used the Swiss Target Prediction database to supplement, delete, and deduplicate the target information. A sum of 186 drug targets was finally screened out. The number of components and predicted targets corresponding to various TCMs is presented in In this research, we searched the database of GeneCards and obtained 518 potential targets following the removal of duplicate targets. These targets were strongly associated with the initiation and development of FRNS.A Venn diagram was drawn by inputting 186 drug targets and 518 FRNS targets into the online software Venny2.1. The generated Venn diagram suggested that 51 common potential targets were related to the active ingredients and FRNS .To explore the latent mechanism underlying the functions of GYD on FRNS, we established a D-C-D-T network utilizing Cytoscape 3.7.1 software .To elucidate the mechanism accounting for the interaction of these overlapping genes, the aforementioned 51 common targets were analyzed in the STRING database, and then a PPI network was correspondingly constructed . Each edp-value from small to large , cellular composition (CC), and molecular function (MF) from 51 common targets by GO analysis after the processing with R language. The top 8 enriched GO terms were confirmed by GO analysis, as presented in the bar plot . BP enrito large . The firSubsequently, we selected the first two targets (AKT1 and CASP3) with high scores from 51 latent targets for molecular docking with 3 active components of GYD .Firstly, AKT1 interacted with luteolin, wogonin, and kaempferol. The docking scores of luteolin, wogonin, and kaempferol with AKT1 were 8.0, 7.7, and 4.5, respectively . Meanwhip < 0.05, p < 0.001, p < 0.05, p < 0.05, p < 0.01, According to the results of CCK-8 assay, 100, 150, and 200 μM of LUT had no significant effect on the viability of MPC-5 cells, while 250 μM of LUT led to the obvious decrease in cell viability  with high scores were singled out from 51 latent targets, followed by molecular docking with 3 active components of GYD . It turned out that AKT1 or CASP3 interacted with luteolin, wogonin, and kaempferol, respectively, unveiling that AKT1 and CASP3 may be the key targets of luteolin, wogonin, and kaempferol against FRNS. Furthermore, cell experiments showed that luteolin treatment was able to enhance the viability and inhibit the apoptosis of FRNS-modeled cells In conclusion, the chemical components like luteolin, wogonin, and kaempferol in GYD, the core targets including AKT1, CASP3, and IL6, the processes such as muscle cell proliferation, membrane raft and cytokine receptor binding, as well as the signaling pathways such as AGE-RAGE signaling pathway in diabetic complications, lipid, and atherosclerosis, TNF signaling pathway, etc., are the potential mechanisms accounting for the effects of GYD in the treatment of FRNS. The innovation of this paper is our first discovery of active compounds, latent targets, and molecular mechanisms of GYD in FRNS, which provides us with a better understanding on the therapeutic role of GYD on FRNS. Despite these considerable findings, there are still some limitations in this study that should be addressed. Firstly, we may ignore the roles of some compounds and target genes in FRNS due to the continuous updates of the public databases. Secondly, additional animal experiments and clinical experiments are required to further support and verify the specific mechanism of GYD in the treatment of FRNS.