The Traditional Chinese Medicine (TCM) formula Yi-Fei-Jian-Pi-Tang (YFJPT) has been demonstrated effective against Corona Virus Disease 2019 (Covid-19). The aim of this article is to make a thorough inquiry about its active constituent as well as mechanisms against Covid-19 via TCM network pharmacology.  All the ingredients of YFJPT are obtained from the pharmacology database of the TCM system. The genes which are associated with the targets are obtained by utilizing UniProt. The herb-target network is built up by utilizing Cytoscape. The target protein-protein interaction network is built by utilizing the STRING database and Cytoscape. The critical targets of YFJPT are explored by Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). α nuclear factor of kappa light polypeptide gene enhancer in Bcells inhibitor, alpha (NFKBIA), nuclear factor-k-gene binding (NFKB), nitric oxide synthase 3 (NOS3), intercellular adhesion molecule 1 (ICAM1), hypoxia inducible factor 1 subunit alpha (HIF1A), mitogen-activated protein kinase 3 (MAPK3), epidermal growth factor receptor (EGFR), interleukin 10 (IL10), jun proto-oncogene (JUN), C-C motif chemokine ligand 2 (CCL2), C-X-C motif chemokine ligand 8 (CXCL8), tumor protein p53 (TP53), interleukin 1 beta (IL1B), AKT serine/threonine kinase 1 (AKT1), tumor necrosis factor (TNF), interleukin 6 (IL6), erb-b2 receptor tyrosine kinase 2 (ERBB2), RELA proto-oncogene (RELA), NF-κB subunit, caspase 8 (CASP8), peroxisome proliferator activated receptor alpha (PPARA), TIMP metallopeptidase inhibitor 1 (TIMP1), transforming growth factor beta 1 (TGFB1), interleukin 1 alpha (IL1A), signal transducer and activator of transcription 1 (STAT1), mitogen-activated protein kinase 8 (MAPK8), myeloperoxidase (MPO), matrix metallopeptidase 3 (MMP3), matrix metallopeptidase 1 (MMP1), and NFE2 like bZIP transcription factor 2 (NFE2L2). The gene enrichment analysis prompts that YFJPT most likely contributes to patients related to Covid-19 by regulating the pathways of cancers.  The outcomes show that YFJPT might has 33 therapeutic targets on Covid-19, namely, interleukin 2 (IL2), heme oxygenase 1 (HMOX1), interleukin 4 (IL4), interferon gamma (FNG),  That will lay a foundation for the clinical rational application and further experimental research of YFJPT. The infection of a new beta-coronavirus which is the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and affecting the socioeconomic conditions of billions of people worldwide spreads around the world and results in a potentially lethal disorder: the Corona Virus Disease 2019 (Covid-19) since December 2019 . A largehttps://www.megabionet.org/tcmid/), which is the Traditional Chinese Medicine integrative database for herb molecular mechanism analysis, to achieve the aim of collecting the compounds of YFJPT; the Traditional Chinese Medicine Systems Pharmacology Database , which is a typical system pharmacology platform that is designed for Chinese herbal medicines; and the TCM Database@Taiwan (https://tcm.cmu.edu.tw/) as the most comprehensive TCM database universally [We use the Traditional Chinese Medicine Integrated Database  provides information on chemical substances and biological activities. We make a decision to eliminate some chemicals after the replicated data is deleted due to the lack of accurate structural information of the targets of the compounds, which is unable to be forecasted successfully [UniProt , Online Mendelian Inheritance in Man(OMIM) (https://www.omim.org), GeneCards (https://www.genecards.org), and Kyoto Encyclopedia of Genes and Genomes(KEGG) (https://www.genome.jp/kegg) [The genes in relation to Covid-19 which are different are obtained from National Center for Biotechnology Information (NCBI) (jp/kegg) , 38  with the species which are confined to “Homo sapiens” extracts the data of protein-protein interaction (PPI). Meanwhile, STRING database defined PPI with confidence ranges for data scores , which is a database of predicted protein-protein interplay [The STRING  could fit the visualizing networks of intermolecular interactions well, so it is utilized with the intention of displaying all of the networks presented below and provided a powerful suit of visualization functions, data analyzing and integration to make an analysis for the complex networks [4The network visualization software Cytoscape  is applied to achieve the aim of performing KEGG pathway enrichment analysis and GO, which provides a biologist-oriented resource for the investigation of systems-level datasets. Enriched GO terms and pathways are dealed by utilizing the WeiShengXin tools (https://www.bioinformatics.com.cn) which is an online platform free of cost for database analyzing [The Database for Metascape -target network is described in The YFJPT targets' PPI network is displayed in A compound-target-Covid-19 PPI network is built up by using 33 nodes and 946 edges with the intention of analyzing the significance of compound targets after filtrating the database by the Cytoscape. It shows us an intuitive concept to distinct those core nodes with high connectivity from the others in the network –60. The We carry out a GO enrichment analysis for the function of molecules, cellular ingredient as well as the biological process of the 30 targets which are chosen to clarify the multiple mechanisms of YFJPT on Covid-19. We predict 33 potential targets in our present study, which suggests that YFJPT is a complex prescription consisting of multiple components so as to affect an enormous variety of different targets. The data investigation reveals that YFJPT is likely to apply the pharmacological influences on Covid-19 by regulating certain targets which consists of MPO, CCL2, IL2, IFNG, IL4, TP53, and NOS3. The GO investigation of targets uncovers that it is possible for the constituent of YFJPT to bring about synergistic influences for treating Covid-19 primarily through accommodating relevant biological courses, such as paths in cancer, HIF-1 signal path, IL-17 signal path, and antigen processing and presentation . At the


For many years, vitamin D (VD) has been known to be an essential micronutrient with important relevance not only for the skeletal system, but also for numerous other mammalian organ systems. Low levels of VD result in a VD deficiency, which is a global health problem. Moreover, VD deficiencies are linked to several pathologies, for instance, diseases of the cardiovascular system, diabetes mellitus, or sub- and infertility. In the past two decades, an increasing body of evidence has shown that adequate physiological levels of VD are crucial for the female gamete and its microenvironment, and VD deficiency has been associated with decreased live birth rates among women undergoing in vitro fertilization (IVF). With regard to the female reproductive tract, VD receptors (VDRs) have been detected in the ovary, endometrium, and the placenta. Although it has been reported that VD seems to be relevant for both calcium-dependent and independent pathways, its relevance for the oocyte’s developmental competence and life span remains elusive. Therefore, herein, we aim to provide an update on the importance of VD and VD deficiency for the oocyte and the follicular microenvironment. There is no doubt that vitamin D (VD), VD deficiency, and VD supplementation are of important relevance for medicine and public health, since bone fractures, osteoporosis, or low bone mass are a general problem, especially in the elderly. People now tend to reach old age more often, and there has also been a detectable age shift in terms of women’s first pregnancy, which further underlines the importance of the aforementioned fact. In consequence, research over the past two decades did not only concentrate on the importance of VD for the skeletal system and bone mineralization, but also for the female reproductive system. Prior to going into detail on VD’s relevance for the oocyte, some general facts on VD will be provided in this introduction section. To begin with, it is important to know that the main site of VD production is the skin, and the reaction substrate for the synthesis of this secosteroid is 7-dehydro-cholesterol (7-DHC). Ultraviolet (UV) radiation converts it into previtamin D. The isomeric form of previtamin D, cholecalciferol, either reaches the liver unbound or bound to vitamin D-binding protein (DBP) via the blood stream . There, Interestingly, VD biosynthesis appears to also be possible at the ovarian site . In the During early folliculogenesis, by far the most important controller of follicle development is the anti-Müllerian hormone (AMH) ,18,19. AMoreover, VD signaling leads to an increased production of steroid hormones in granulosa cells  26], wh, wh26], 2+ oscillations are required for crucial processes such as the resumption of meiosis, polyspermy block, male chromatin decondensation, recruitment of maternal mRNAs, and pronuclear formation [2+ stored in the ER, altered cytoplasmic Ca2+ uptake due to decreased sarcoplasmic reticulum Ca2+ ATPases (SERCA2) expression, and diminished ATP availability secondary to altered mitochondrial functionality [Adequate levels of calcitriol seem to be necessary to regulate key processes during development, differentiation, and genomic imprinting through epigenetic mechanisms in oocytes. VD and its clinical implications regarding the developmental competence and fertilization of oocytes has prompted researchers’ attention. As previously mentioned, VD deficiencies in both serum and follicular fluid may lead to fertility disorders . Due to ormation . Interesionality . Moreoveionality .In addition, it was recently indicated that there is a significantly higher level of follicular fluid VD in women with a lowered ovarian reserve when compared to women with a normal ovarian reserve . This maVD receptors (VDRs) are present in many tissues and have numerous functions in specific organs all over the body . With re3+ group on lysine. Consequently, modifications within histones modulate the euchromatin density. Other auxiliary proteins may also interact with the VDR. One of these proteins is the nuclear receptor co-repressor 2 (NCOR2), which recruits DNA deacetylases to the promoter site [Interestingly, it has been indicated that VD may regulate the degree of cytosine methylation in the promoter region of vitamin D-regulated genes  via inteter site . A similter site . The SNWter site . Interester site . Deactivter site .Vitamin D insufficiency or deficiency and its association with sub- or infertility is a difficult challenge for numerous clinicians and reproductive medicine specialists. Therefore, the safe and ethical modulation of VD and oocyte quality requires a more comprehensive understanding of their interplay. As presented in this article, VD appears to not only have stimulatory effects on folliculogenesis, but also a negative impact on oocyte maturation, based on the adequate concentration and supplementation, respectively. Therefore, VD supplementation in women prior to or during pregnancy is still controversial, since further elucidation is required to answer the question of the extent to which these antagonistic effects are related to individual patients, genetics, or epigenetics. There is no doubt that optimal serum and follicular fluid levels of VD are of high relevance for female reproduction, with the oocyte at the top. Importantly, the establishment of accessible and non-invasive tests in which VD can be used as a biomarker for oocyte quality would be especially helpful to determine which therapeutic strategy is best suited to individual clinical cases. Taken together, elucidating the molecular mechanisms and the unique role of VD for females and for their oocytes would be a solid basis to identify therapeutic targets to improve oocyte health. Keeping in mind the negative associations also related to VD supplementation, appropriate concentrations of VD could be set for specific patients as a new strategy to enhance and prolong female reproductive fitness.


Using previously approved medications for new indications can expedite the lengthy and expensive drug development process. We describe a bioinformatics pipeline that integrates genomics and proteomics platforms to identify already-approved drugs that might be useful to treat diabetic retinopathy (DR).Proteomics analysis of vitreous humor samples from 12 patients undergoing pars plana vitrectomy for DR and a whole genome dataset (UKBiobank TOPMed-imputed) from 1330 individuals with DR and 395,155 controls were analyzed independently to identify biological pathways associated with DR. Common biological pathways shared between both datasets were further analyzed  to identify target proteins for probable drug modulation. Curated target proteins were subsequently analyzed by the BindingDB database to identify chemical compounds they interact with. Identified chemical compounds were further curated through the Expasy SwissSimilarity database for already-approved drugs that interact with target proteins.The pathways in each dataset (proteomics and genomics) converged in the upregulation of a previously unknown pathway involved in DR , with an emphasis on its role in angiogenesis and blood–retina barrier. Bioinformatics analysis identified U.S. Food and Drug Administration (FDA)-approved medications  that, in theory, may modulate this pathway.The bioinformatics pipeline described here identifies FDA-approved drugs that can be used for new alternative indications. These theoretical candidate drugs should be validated with experimental studies.Our study suggests possible drugs for DR treatment based on an integrated proteomics and genomics pipeline. This approach can potentially expedite the drug discovery process by identifying already-approved drugs that might be used for new indications. The International Diabetes Federation estimated that 463 million individuals had diabetes mellitus (DM) worldwide in 2019 and predicted that this number will increase to 700 million by 2045.–The integration of computer science into the biological field has created a surge of high-throughput data and has challenged the science community to store, organize, and extract meaningful information from them.–,––,––The bioinformatics studies mentioned above have often utilized in silico tools at the genetic, proteomic, or pharmacological levels separately.This study integrated whole genomic sequencing data from the UKBiobank dataset and proteomics data from samples collected from patients with DR who underwent pars plana vitrectomy to identify already-approved drugs that might be repurposed for the treatment of DR. This drug discovery pipeline highlights pathologic pathways shared by the two datasets and identifies probable protein targets within each pathway. In the current report, the two independent proteomics and genomics datasets converged into identical pathways and protein clusters. By applying chemical binding search platforms and pharmacologic agent databases, we identified U.S. Food and Drug Administration (FDA)-approved drugs that, in theory, can be used for the treatment of DR. Such candidate drugs should be confirmed with experimental studies.1.Proteomics analysis of human vitreous humor samples from patients with proliferative diabetic retinopathy (PDR) and whole-genome sequencing (WGS) genomic data from the UKBiobank database from patients with DR2.Identification and comparison of biological pathways in each dataset (proteomic and genomic) to identify shared pathways using the STRING and REACTOME databases3.Using the REACTOME database to identify potential proteins within the shared pathways to be used as target proteins for drug discovery4.Using the BindingDB and Expasy SwissSimilarity databases to identify FDA-approved drugs targeting proteins in the shared biological pathwayThis bioinformatics pipeline was composed of various publicly available databases . The PDR group did not receive anti-vascular endothelial growth factor (VEGF) treatment or laser treatment at any point within 3 months prior to sample collection. Vitreous samples from 14 patients with epiretinal membranes (ERMs) undergoing pars plana vitrectomy were collected as controls. Individuals with a history of retinal vascular diseases leading to ERM were excluded from the control group.,P < 0.05; fold change [FC] threshold = 2) in the DR group when compared to the ERM group were considered candidates for STRING analysis following the method outlined below (A tandem mass tag (TMT)-based quantitative proteomics strategy was used to screen for differentially expressed proteins of vitreous humor between the DR and ERM groups. The details of TMT method can be found in our previous publications.ed below E, 3F.,,P values for case–control ratios and accounts for case–control ratio unbalance, resulting in the output of binary phenotypes (control or disease).P < 0.001, and based on an initial MAF range of 0 to 0.5,A systematic search of the UKBiobank TOPMed-imputed PheWeb databaseP ≤ 1.0e-16). Only proteins that demonstrated protein–protein interactions  were considered for pathway analysis following the method outlined below (P = 0.282). Only proteins that demonstrated protein–protein interactions  were considered for pathway analysis following the method outlined below   . A side-The pathway shared between the genomic and proteomic datasets was curated for proteins that converged in the modulation of the expression and activation of the shared pathway, as well as extracellular signals that converged or diverged with the shared pathway .50). Chemical structures for each compound were further analyzed utilizing the Expasy SwissSimilarity databaseProteins in the shared pathway were analyzed utilizing the BindingDB database,Proteins that were part of the shared pathway  and drug,Vitreous samples taken from human subjects diagnosed with PDR were compared with samples from human subjects diagnosed with ERMs A.32,33 TConstituents from the proteomics and genomics datasets were independently analyzed utilizing the REACTOME database, which revealed seven biological pathways associated with the proteomics dataset and 10 biological pathways associated with the genomics dataset . Major b50  with a wide range of biological functions, including embryonic development, cell proliferation, differentiation, lineage determination, apoptosis, and hematopoiesis.,,LGALS3 is a β-galactoside-binding protein that has been associated with various biological functions that include cell–cell adhesion, cell–matrix interactions, macrophage activation, angiogenesis, metastasis, and apoptosis.,–O-glycosylation in corneal epithelial cells,O-linked glycosylation  pointing toward RUNX2 pathway activation being associated with DR, as recently demonstrated by an experimental study.The results of our study should be inspected considering its theoretical nature and the limitations and strength of this approach. We explored shared pathways between proteomics of “advanced DR” from an Asian population and genomics of “any DR” from a mostly European population (the UKBiobank does not identify DR subclasses, so individuals with early and advanced DR are all included in one categoryOur study is a theoretical venture and the candidate drugs identified by its approach must be validated in experimental studies. The outcomes of the pipeline we suggest depend on when the search is run. The REACTOME and other pathway databases such as PANTHER and KEGG are a consortium of various public academic institutions that gradually and manually review, curate, and include newly found pathways in the database. As new pathways are being discovered they will be included in the database with a lag. Thus, the pathways observed in our study are reflective of the status of the REACTOME database at the time of our analysis, which is expected to be updated in future.–We analyzed proteomics and genomics information from two diverse population with extended analyses to include a drug discovery arm. Each step of the pipeline provided input for the subsequent dataset, eventually converging at a shared target that can in theory be potentially modified with available drugs. Doing so, our approach can accelerate drug discovery and significantly reduce the costs of finding new therapeutics. In particular, identifying already FDA-approved drugs largely expedites their application for bedside treatment. Previous studies (mostly in the field of cancer medicine


Nitazoxanide has been investigated for colorectal cancer and breast cancer. However, its molecular targets and pathways have not yet been explored for hepatocellular carcinoma (HCC) treatment. Utilizing a network pharmacology approach, nitazoxanide’s potential targets and molecular pathways for HCC treatment were investigated. HCC targets were extracted from the GeneCards database. Potential targets of nitazoxanide were predicted using Swiss Target Prediction and Super Pred. Intersecting targets were analyzed with VENNY online tool. Using Cytoscape, a protein-protein interaction (PPI), cluster, and core targets-pathways networks were constructed. Using the Database for Annotation, Visualization and Integrated Discovery (DAVID), gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted. The nitazoxanide was molecularly docked with anti-HCC core targets by employing Auto Dock Vina. A total of 168 potential targets of nitazoxanide, 13,415 HCC-related targets, and 153 intersecting targets were identified. The top eight anti-HCC core targets were identified: SRC, EGFR, CASP3, MMP9, mTOR, HIF1A, ERBB2, and PPARG. GO enrichment analysis showed that nitazoxanide might have anti-HCC effects by affecting gene targets involved in multiple biological processes (BP)  signaling pathway, positive regulation of MAP kinase activity, etc.). KEGG pathways and core targets-pathways network analysis indicated that pathways in cancer and proteoglycans in cancer are two key pathways that significantly contribute to the anti-HCC effects of nitazoxanide. Results of molecular docking demonstrated the potential for active interaction between the top eight anti-HCC core targets and nitazoxanide. Our research offers a theoretical basis for the notion that nitazoxanide may have distinct therapeutic effects in HCC, and the identified pharmacological targets and pathways might function as biomarkers for HCC therapy. HCC is a kind of cancer that often affects people who have a history of hepatitis or cirrhosis. Owing to increasing malignancy and morbidity, it is the second leading cause of global cancer-related demise . SeveralMoreover, chemotherapy treatment with sorafenib (tyrosine multi-kinase inhibitor) has also been identified as a promising therapeutic for an advanced stage of HCC. However, its treatment can only increase overall survival by about 3 months . On the In this instance, scientists are trying very hard to find effective therapeutics for the treatment of HCC by adopting a drug repurposing strategy compared to traditional drug designing and development owing to its several limitations, including failure in expensive late-stage clinical trials, high attrition rates, takes a long time, high cost, etc. . RepurpoNitazoxanide was first developed as an anthelmintic agent and is an antimicrobial agent authorized by the FDA . Müller Network pharmacology, multi-omics data, molecular docking, and public medical databases have enabled an alternative computational drug discovery approach and are extensively used to design and develop therapeutic drugs for many cancer types . Computahttp://www.swisstargetprediction.ch/, accessed on 12 May 2022) and SuperPred  web servers with limitations to “Homo sapiens”  database for the terms “hepatic cancer, hepatic carcinoma, hepatocellular carcinoma, and hepatoma”   . These ihttps://string-db.org/, version 11.5, accessed on 12 May 2022) database with limitations to “Homo sapiens” and at a medium confidence score of 0.400  , and the results are displayed in the form of a bubble plot  using the database for annotation, visualization, and integrated discovery  (ay 2022) . Both anay 2022) . The resble plot . The enrThe network was established between anti-HCC core targets and molecular pathways using Cytoscape software  to determine the intricate relationship between them in the treatment of HCC with nitazoxanide .http://gepia.cancer-pku.cn/, accessed on 14 May 2022) was used to examine the expression of the top eight anti-HCC core targets (determined in section 2.4.) in liver hepatocellular carcinoma (LIHC)  . 3D struThe nitazoxanide targets were predicted using the Swiss Target Prediction and Super Pred web servers with “Homo sapiens” limitations . A totalBy exploring the GeneCards database for the terms “hepatic cancer, hepatic carcinoma, hepatocellular carcinoma, and hepatoma,” 13,415 HCC-related targets were retrieved .A total of 153 intersecting targets were identified between HCC-related and potential targets of nitazoxanide using the VENNY 2.1 online tool  Figure . These iIntersecting targets (153) were uploaded to the STRING database with limitations to the species “Homo sapiens” . A PPI nThe results demonstrated that the PPI network consists of 148 nodes (with the elimination of five disconnected nodes) and 939 edges . The eliFurther, a hub network of targets with degrees greater than the average DC (12.84) was extracted and identified 55 potential HCC targets, which were classified as anti-HCC core targets . The ideThe cluster network analysis was further carried out on the constructed PPI network  using thThe expression of the top eight anti-HCC core targets  in LIHC and normal samples were analyzed using the GEPIA database. The analysis results demonstrated that anti-HCC core targets were differentially expressed in LIHC and normal samples . These rAnti-HCC effects of nitazoxanide drug were further investigated by performing GO enrichment analysis on 153 intersecting targets. The top 10 enriched GO terms  were identified. The results are presented in p ≤ 0.05. The top 30 KEGG pathways were presented in The molecular mechanisms involved in the anti-HCC effects of nitazoxanide drug were further investigated by performing a KEGG pathway enrichment analysis on 153 intersecting targets. A total of 78 enriched KEGG pathways were identified at To identify the major pathways involved in the anti-HCC effects of the nitazoxanide drug, a network between the top eight anti-HCC core targets and their corresponding pathways were constructed. The network results demonstrated that seven anti-HCC core targets  followed the pathways in cancer (degree 7). On the other hand, SRC, CASP3, EGFR, ERBB2, mTOR, MMP9, and HIF1A followed the proteoglycans in cancer (degree 7) .Moreover, the pathways were further ranked by DC greater than the average DC (3.35) in the network to find the major pathways. A total of nine major pathways were identified and presented in a bar graph, as shown in The nitazoxanide drug was molecularly docked with the top eight anti-HCC core targets , and the findings are shown in via network pharmacology  signaling pathway, positive regulation of MAP kinase activity, peptidyl-serine phosphorylation, etc.). Protein phosphorylation is vital for performing various activities such as biological processes, cellular localization, etc.; however, its aberrant regulation contributes to several conditions such as HCC, etc. . MAP kinThe KEGG enrichment analysis revealed that the molecular pathways underlying the anti-HCC effects of the nitazoxanide drug might involve pathways in cancer, PI3K-Akt signaling pathway, MAPK signaling pathway, proteoglycans in cancer, EGFR tyrosine kinase inhibitor resistance, apoptosis, hepatitis B, ErbB signaling pathway, microRNAs in cancer, etc. In spite of the fact that the PI3K–AKT signaling pathway regulates a wide range of cellular processes, its abnormal activation promotes the development of HCC . ConsequTo further validate the results, nitazoxanide’s impact on the eight anti-HCC core targets  was investigated in silico. The targets’ molecular interactions with nitazoxanide demonstrated efficient binding in docking studies. Together, our findings show that patients with HCC have elevated levels of transcriptional expression of the expected targets and that therapy with nitazoxanide may suppress the translational expression of those targets.In this study, we have successfully identified the anti-HCC core targets and their biological functions, molecular pathways, and the effect of nitazoxanide on HCC. The constructed network pharmacology revealed the significant interaction among the predicted targets that identified eight anti-HCC core targets  as the active bio targets of nitazoxanide in HCC. Furthermore, we found that nine key pathways are likely to be involved: pathways in cancer, proteoglycans in cancer, MicroRNAs in cancer, central carbon metabolism in cancer, lipid and atherosclerosis, Kaposi sarcoma-associated herpesvirus infection, ErbB signaling pathway, and EGFR tyrosine kinase inhibitor resistance, by which nitazoxanide treats HCC. Our study validates the notion that nitazoxanide’s anti-HCC effects may emerge from synergistic interactions across several targets and pathways, and our data offer evidence to support this notion. A molecular docking simulation demonstrated the potential for active interaction between the anti-HCC core targets and nitazoxanide. Our study provides a theoretical foundation for the idea that nitazoxanide may have unique therapeutic benefits in HCC, and the pharmacological targets that have been identified may be potential biomarkers in the treatment of HCC.


Currently, the prevention and treatment of HCC remains a major challenge. As a traditional Chinese medicine (TCM) formula, Ruangan Lidan decoction (RGLD) has been proved to own the effect of relieving HCC symptoms. However, due to its biological effects and complex compositions, its underlying mechanism of actions (MOAs) have not been fully clarified yet. In this study, we proposed a pharmacological framework to systematically explore the MOAs of RGLD against HCC. We firstly integrated the active ingredients and potential targets of RGLD. We next highlighted 25 key targets that played vital roles in both RGLD and HCC disease via a protein-protein interaction (PPI) network and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Furthermore, an ingredient-target network of RGLD consisting of 216 ingredients with 306 targets was constructed, and multilevel systems pharmacology analyses indicated that RGLD could act on multiple biological processes related to the pathogenesis of HCC, such as cellular response to hypoxia and cell proliferation. Additionally, integrated pathway analysis of RGLD uncovered that RGLD might treat HCC through regulating various pathways, including MAPK signaling pathway, PI3K/Akt signaling pathway, TNF signaling pathway, and ERBB signaling pathway. Survival analysis results showed that HCC patients with low expression of VEGFA, HIF1A, CASP8, and TOP2A were related with a higher survival rate than those with high expression, indicating the potential clinical significance for HCC. Finally, molecular docking results of core ingredients and targets further proved the feasibility of RGLD in the treatment of HCC. Overall, this study indicates that RGLD may treat HCC through multiple mechanisms, which also provides a potential paradigm to investigate the MOAs of TCM prescription. Hepatocellular carcinoma (HCC) is one of the pathological types of primary liver cancer, characterized by insidious onset, rapid progress, high mortality, and along with poor prognosis –3. To daPinellia ternata (Thunb.) Breit. , Bupleurum chinense DC. , Sedum sarmentosum Bunge. , Glycyrrhiza uralensis Fisch. , Panax ginseng C.A. Mey. , Scutellaria baicalensis Georgi. , Curcuma Longa L. , Grangea maderaspatana , Prunella vulgaris L. , Corydalis yanhusuo W.T. Wang , and Artemisia capillaris Thunb. . Our previous clinical studies have found that RGLD can effectively reduce transaminase, protect liver function, help prevent recurrence and metastasis of patients with HCC, and prolong the disease-free survival of HCC [+, CD4+, and CD4+/CD8+, improving patients' immune function and their quality of life after chemotherapy [Traditional Chinese medicine (TCM) can prolong the survival period of patients with cancer via enhancing the body's immunity, as well as having the characteristics of low toxicity and reversal of multidrug resistance. It is also an important part of comprehensive treatment measures for malignant tumor –14. Indel of HCC , 18. In otherapy . HoweverSystem pharmacology is an emerging discipline that can describe the complex interactions between the drugs and biological systems, including the human body, organs, and diseases from the perspective of network. This approach is aimed at investigating the changes in the functions and reactions within the human body induced by drugs, thus providing new tools and strategies for the interpretation of complex disease mechanisms and modernization of TCM , 21. IndIn the study, we attempted to establish a complete pharmacological framework to systematically explore the molecular MOAs of RGLD against HCC . Specifihttp://tcmspw.com/tcmsp.php) database was used to collect the effective components and related targets of the 11 herbs in RGLD. The screening criteria were oral bioavailability (OB) > 30% and drug-likeness (DL) > 0.18 [TCMSP  > 0.18 , 24, sinhttps://www.genecards.org/), DisGeNET database (http://www.disgenet.org/), and OpenTarget database (https://platform.opentargets.org/) [Using “Hepatocellular Carcinoma” as the key word, we screened the disease genes of HCC from GeneCards database (ts.org/) , 26. Thehttps://string-db.org/) to construct a PPI network [The intersection targets of drug-target-disease genes were imported into the STRING database ( network . The deg network .https://david.ncifcrf.gov/home.jsp) was used to perform GO terms for further exploring the potential mechanism of RGLD against HCC, including BP analysis, MF analysis, and CC analysis. All gene names were entered into the DAVID database and limited the species to Homo sapiens. Only those terms with the P value < 0.05 were retained [DAVID database  to analyze the correlation between the expression of crucial anti-HCC targets in RGLD and the survival rate of HCC patients. The targets with P value < 0.05 were selected [We imported overlapped targets of drugs and diseases to the Kaplan-Meier plotter (selected . Furtherhttp://www.rcsb.org/) and PubChem (https://pubchem.ncbi.nlm.nih.gov/) [The molecular docking analysis was performed on AutoDock Vina and AutoDock Tools. Targets of HCC and 2D structures of the active ingredients of RGLD were downloaded from the Protein Data Bank (PDB) database (ih.gov/) , 33. Then = 4), including beta-sitosterol, kaempferol, poriferasterol monoglucoside_qt, and quercetin. Beta-sitosterol has been reported to exhibit ameliorative effects on HCC due to its antioxidant activities [n = 191), which implies that they may play synergistic effects on HCC. These targets include PGR, PTGS1, NCOA2, progesterone receptor, prostaglandin G/H synthase 2, and beta-1 adrenergic receptor. Studies have deciphered that NCOA2 is an important tumor suppressor gene, and activation of NCOA2 is beneficial to inhibit the occurrence and development of HCC [As a key theory of TCM, “Jun-Chen-Zuo-Shi” has guided physicians to formulate herbal medicines for over thousands of years . This prtivities . Kaempfetivities . In additivities . Interest of HCC . Taken tWe acquired 170 HCC genes from DisGeNET, OpenTarget, and GeneCards databases after removing duplicated genes. The detailed information of the 170 disease genes were provided in Table We further performed KEGG pathway enrichment analysis of the 25 intersection targets by using DAVID online platform. As displayed in D) includes quercetin (D = 1063), beta-sitosterol (D = 277), kaempferol (D = 252), stigmasterol (D = 186), isorhamnetin (D = 148), luteolin (D = 114), baicalein (D = 74), cavidine (D = 56), wogonin (D = 45), and 7-methoxy-2-methyl isoflavone (D = 43). Emerging evidence shows that these components are highly related to HCC. For example, baicalein can suppress HCC cell growth and survival through downregulation of CD24 [K = 155) has the highest compound connections, followed by CALM1 (K = 141) and ESR1 (K = 105). As a family member of heat-shock proteins (HSPs), HSP90AA1 is a potential diagnostic and prognostic biomarker and therapeutic target for HCC, acting as an active role in tumor and immune-related signaling pathways [To construct a drug-target network for RGLD, we integrated the herbal ingredients of RGLD and its relative targets. A total of 5320 drug-target interactions (DTIs) were obtained in the network, connecting 216 ingredients with 306 targets. Interestingly, we found that these 306 targets were composed of 25 HCC targets and 281 non-HCC targets. Since TCM has the characteristics of multitarget pharmacological action, it can not only act on disease genes directly but also exert the therapeutic effect of HCC by acting on other related genes , 45.  Fi of CD24 . Moreove of CD24 . In additin D = 1, luteolipathways . CALM1 apathways . Moreovepathways , 52.We next performed GO enrichment analysis on the top 30 targets in the drug-target network. As shown in In order to construct an HCC-integrated pathway, targets of RGLD were mapped into these pathways associated with the pathological process of HCC. As depicted in Proliferation and apoptosis of cells have been considered as a contributing factor in the occurrence, development, and prognosis of HCC . AbnormaAutophagy is a lysosomal-dependent catabolic pathway, which is closely related to the pathogenesis of HCC . Indeed,α, can promote tumor growth and poor prognosis of HCC [It is acknowledged that persistent chronic inflammation is a cancer promoter while HCC is one of the most common inflammation-related cancers . The occs of HCC . Additios of HCC , 77. As The epidermal growth factor receptor (ERBB) signaling pathway is a transmembrane receptor tyrosine kinase, which plays a significant role in HCC, such as controlling cell migration and invasion , 79. RecIn order to evaluate the potential clinical significance of these targets, we performed survival analysis of 25 overlapped targets in RGLD and HCC by using the Kaplan-Meier plotter. As shown in To explore the feasibility of RGLD in the treatment of HCC, molecular docking analysis was performed on the core active ingredients of HCC  and the key targets of HCC . The PDB numbers of the crystal structures of VEGFA, HIF1A, CASP8, and TOP2A were 3QTK, 4H6J, 1QTN, and 4MF9, respectively. In Figures HCC is the most common type of liver cancer and also the second leading cause of cancer-correlated mortality worldwide . SurgicaIn this study, we firstly performed overlap analysis on herbal ingredients and potential targets to investigate the rationality of RGLD. We next integrated the PPI network of 25 hub targets and performed KEGG pathway enrichment analysis. We further constructed a drug-target network of RGLD and proposed multilevel analysis to explore the potential mechanism of RGLD in the treatment of HCC through GO term annotations, HCC-integrated pathway analysis, and survival analysis. According to the systems pharmacology results, RGLD may play a reliable intervention effect on HCC through multipathway, multitarget, and multimechanism. For example, the targets of RGLD are enriched in PI3K/Akt pathways, ERBB pathways, TNF pathways, MAPK pathways, etc. . These pAlthough the current drug compositions and dose of RGLD showed efficacy on HCC patients, there were still several limitations in our study. Firstly, due to the complexity of HCC disease and the intrinsic interactions and multiple complicated ingredients in the mixture of different plants, thus, our study could not entirely reflect the actual function of different drug dosages of RGLD in the human body. Secondly, the systems pharmacology results are based on the interaction between components and drug targets of medicinal materials, which rarely depend on the drug dosages. Therefore, the current study does not consider the effect of different drug dosages on systems pharmacology results. Collectively, it is necessary to further explore the possible mechanism and the most suitable dose of RGLD in the treatment of HCC in future clinical and experimental studies.


Alternative splicing (AS) events are extensively involved in the progression of diverse tumors, but how serine/arginine-rich splicing Factor 10 (SRSF10) behaves in hepatocellular carcinoma (HCC) has not been sufficiently studied. We aimed to determine SRSF10 associated AS mechanisms and their effects on HCC progression.The expression of SRSF10 in HCC tissues was examined, and the in vitro and in vivo functions of SRSF10 were investigated. The downstream AS targets were screened using RNA sequencing. The interaction between SRSF10 protein and exclusion of cell division cycle 25 A (CDC25A) mRNA was identified using RNA immunoprecipitation and crosslinking immunoprecipitation q-PCR. The effects of SRSF10 on CDC25A posttranslational modification, subcellular distribution, and protein stability were verified through coimmunoprecipitation, immunofluorescence, and western blotting.SRSF10 was enriched in HCC tissues and facilitated HCC proliferation, cell cycle, and invasion. RNA sequencing showed that SRSF10 promotes exon 6 exclusion of CDC25A pre-mRNA splicing. As a crucial cell cycle mediator, the exon-skipped isoform CDC25A(△E6) was identified to be stabilized and retained in the nucleus due to the deletion of two ubiquitination  sites in exon 6. The stabilized isoform CDC25A(△E6) derived from AS had stronger cell cycle effects on HCC tumorigenesis, and playing a more significant role than the commonly expressed longer variant CDC25A(L). Interestingly, SRSF10 activated the carcinogenesis role of CDC25A through Ser178 dephosphorylation to cause nuclear retention. Moreover, CDC25A(△E6) was verified to be indispensable for SRSF10 to promote HCC development in vitro and in vivo.We reveal a regulatory pattern whereby SRSF10 contributes to a large proportion of stabilized CDC25A(△E6) production, which is indispensable for SRSF10 to promote HCC development. Our findings uncover AS mechanisms such as CDC25A that might serve as potential therapeutic targets to treat HCC.The online version contains supplementary material available at 10.1186/s13046-022-02558-0. Liver cancer tumors are among the five most lethal solid tumors in China and the third most lethal neoplasms worldwide. Hepatocellular carcinoma (HCC) accounts for more than 80% of all liver cancer cases, and the common difficulties in most cases are early diagnosis, the aggressive invasiveness of tumors, and the lack of a favorable response to pharmacotherapy . AberranDeregulation of AS is implicated as a relevant source of molecular heterogeneity in cancer. Editing of immature mRNA (pre-mRNA), “constitutive splicing” is carried out by the spliceosome. This process is a fundamental step for intron removal and exon ligation as part of an integrated mechanism involved in the gene regulatory network . In contThe sequential interaction of spliceosome elements such as small nuclear ribonucleoproteins (snRNPs) is affected by the balance between members of serine/arginine (SR)-rich proteins and heterogeneous nuclear ribonucleoproteins (hnRNPs), which determines the outcome of mRNA maturation , 12. AmoTo date, the potential functions of SRSF10 in tumorigenesis are undocumented for most cancer types, and its pathological mechanisms are poorly characterized. In our previous study, SRSF10 was found to be significantly upregulated in HCC tumorigenesis, but how SRSF10 behaves in HCC is not clear. Our initial observations indicate that SRSF10 overexpression stimulates HCC cell growth and invasion. Intriguingly, SRSF10 has an essential role in affecting several AS events, such as downstream cell division cycle 25 A (CDC25A) proteins. The following data collectively indicate that CDC25A regulated by SRSF10 contributes to HCC progression, thus identifying the AS of CDC25A, such as exon skipping, as a potential therapeutic target in HCC.2.Six HCC cell lines  were purchased from ATCC . Cells were continuously cultured in Dulbecco’s modified Eagle’s medium  containing 10% fetal bovine serum (FBS) , 100 IU/ml penicillin G and 100 μg/ml streptomycin . All cell lines were incubated at 37 °C in a humidified atmosphere with 5% COSRSF10-shRNA, plasmids for SRSF10 overexpression with and without Flag-tag, CDC25A-overexpressing plasmids tagged with and without GFP-Flag, and CDC25A-shRNA targeting various sites were purchased from GeneChem Biotechnology Company . The shRNA sequences and primer information are described in more detail in Supplementary Table The 24/48 h transfection and knockdown efficiency were assessed by immunofluorescence and western blot analysis. The knockdown efficiency was determined using two different RNAi, and the sequence with the higher result was selected for further experiments.Total RNA was extracted from cells using an RNeasy Mini kit . Complementary DNA (cDNA) synthesis was performed with a GeneAmp RNA PCR kit (Life Technologies) using 1 µg RNA per sample. qPCRs were set up using the iScriptTM two-step RT–PCR kit with SYBR Green (Invitrogen) and the targeting gene primers .The chemical reagents rabusertib , and MG132  were obtained from Selleckchem . CHX  was obtained from Cell Signaling Technology . Commercially available antibodies for western blotting, immunoprecipitation, immunohistochemistry, and immunofluorescence staining are described in more detail in Supplementary Table Mutation and truncation of SRSF10 and CDC25A were performed by PCR-based methods. The CDSs of SRSF10 (NM_054016.4) and CDC25A (NM_001789) were synthesized and subcloned into the vector pEGFP-C1 . Point mutation of CDC25A in Lys150 and Lys169 was introduced to arginine (R), while its Ser178 was replaced by alanine (A) or glutamic acid (E). For SRSF10, deleting the 11–84 aa sequence led to a mutation lacking the RNA recognition motif (RRM), also known as SRSF10 (ΔRRM1). Both SRSF10 and CDC25A wild-type and mutants were validated by DNA sequencing and western blotting with the help of Kangchen Biotech .Cell proliferation was analyzed using a commercial CCK-8 assay kit  and EdU detection kit . Fluorescence-activated cell sorting (FACS) was used to assess the cell cycle with a PI staining kit . Cell invasion was assessed by the transwell assay with a 6-well insert device  and Biocoat Matrigel (BD Biosciences) according to the manufacturer’s instructions.Cells were treated with 10 μM cycloheximide (CHX) for the indicated periods  to block protein synthesis. MG132 (20 μM) was also administered to inhibit the proteasome before harvesting. Endogenous and exogenous CDC25A protein expression was then assayed as described previously .−kt; where k is the decay rate constant, y is the relative amount of RNA, and t is the time). The rate of mRNA turnover was estimated according to the half-life t1/2 = ln(2)/k. The transcript 18S rRNA, which does not decay over time, was detected as a control.To measure mRNA stability, 5 g/ml actinomycin D  was added to cells to inhibit transcription, followed by incubation for the different times indicated. Total RNA was extracted at each time point and quantitated by RT‒PCR. The transcript levels were plotted to create the appropriate nonlinear regression curves using a one-phase decay equation. Exponential fitting curves were determined to quantify the RNA decay rate constant .Immunoprecipitation was performed using protein G-agarose . Blots were then developed with ECL western blotting reagents . The signal intensity was quantified with ImageJ .Tissues were obtained from the specimens of HCC patients who met the following criteria: 1) informed consent was provided; 2) the patients were clinically and pathologically diagnosed with HCC; 3) the patients did not undergo any neoadjuvant therapy before surgery; and 4) adjacent nonneoplastic liver tissues were available for comparison. A total of 74 paired HCC specimens embedded in paraffin were cut into 5-µm slides. The sections were counterstained as previously described .The degree of immunostaining was reviewed and scored separately by two independent pathologists who were blinded to the histopathological features of the samples. Based on the proportion of tumor cells, the following scores were assigned: 0, no tumor cells; 1, < 10% tumor cells; 2, 10 − 35% tumor cells; 3, 35 − 75% tumor cells; and 4, > 75% tumor cells. The staining intensity was scored as follows: 1, no staining; 2, weakly stained (light yellow); 3, moderately stained (yellow brown); and 4, strongly stained (brown). The staining index was determined by multiplying the staining intensity score by the tumor cell proportion score. A staining index ≥ 6 was considered to indicate high expression of SRSF10, while an index < 6 indicated low expression.Cells grown on coverslips were stained as previously described . The antImmunoprecipitation targeting CDC25A pre-mRNA was performed using Magna RIP™  according to the manufacturer’s protocol. The SRSF10 antibody or IgG-immunoprecipitated RNA extracts were reverse-transcribed using TRIzol Reagent , and the quantification of target RNA was performed by RT‒qPCR).In the CLIP study of Flag-SRSF10, we tested the recognition of CDC25A. Three primer pairs for exon 5, exon 6, and exon 7 were designed to evaluate precipitated RNA levels as previously described . The seq6 cells) of SRSF10, CDC25A(△E6), CDC25A(L), sh-CDC25A(△E6), or sh-CDC25A(FL) in HepG2 cells and control cells. The size of the palpable tumors was recorded every 3 days by measuring the tumor length  and width , which were recorded six consecutive times. All mice were sacrificed after 35 days. The tumor volume (V) was calculated according to the formula V = 1/2 (L × W2).Five-week-old male BALB/c nude mice were randomly divided into six groups. Specifically, xenograft tumors were generated by subcutaneously inoculating the right axillary fossa with 200 μl (1 × 10http://gepia.cancer-pku.cn), the starBase Pan-Cancer Analysis Platform (http://starbase.sysu.edu.cn/panCancer.php), the Cancer Genome Atlas (TCGA) database (https://cancergenome.nih.gov/), Cancer RNA-Seq Nexus (CRN) database (http://syslab4.nchu.edu.tw/), and NCBI’s Gene Expression Omnibus database (https://www.ncbi.nlm.nih.gov/geo/). PhosphoSitePlus (https://www.phosphosite.org/) was applied to predict the PTM sites. The Ensembl Genome Browser (https://www.ensembl.org/) was used to blast RNA sequences of CDC25A variants. Gene set enrichment analysis (GSEA) of SRSF10- and CDC25A-relevant gene signatures was performed with GSEA software v.2.0 according to a reported protocol [The survival, differential expression, and correlation of the candidate gene were assessed using the Gene Expression Profiling Interactive Analysis (GEPIA) database . The results are displayed as the mean ± SD or mean ± SEM, and two-group comparisons were evaluated using Student’s t test.2 test. On the basis of the correlation between the IHC score and patient survival, the cutoff point of each dataset subgroup was determined using the survminer R package. The “surv-cut point” function, which repeatedly tested all potential cut points to find the maximum rank statistic, was applied to the IHC score. Patients were then divided into high- and low-score groups on the basis of maximally selected log-rank statistics to reduce the batch effect of calculation. In the univariate survival analysis, cumulative survival curves were calculated according to the Kaplan–Meier method, and the survival curves were analyzed using the log-rank test.The relationship between SRSF10 expression and clinicopathological characteristics was analyzed using the χn = 74) was highly correlated with the neoplastic grade  and tumor size (P < 0.001)  vs. tumor (35)) and TCGA datasets  vs. tumor (373)) revealed significantly enriched SRSF10 in HCC versus normal tissue. SRSF10 was also associated with a shorter overall survival rate in HCC patients from public data  term enrichment analysis of the RNA-seq data demonstrates that exon skipping (ES) was the most frequent AS event regulated by SRSF10 Fig. A. FurtheCDC25A RNA fragments  and CDC25A(△E6) were first utilized for HepG2 and Hep3B cell lines transfected with either SRSF10-overexpressing or sh-SRSF10 plasmids  is critical for affecting malignancies in HCC cells. Stronger CDC25A(△E6) signals were observed in HCC tissues than in adjacent nontumor tissues in most of the 10 HCC cases, suggesting that highly expressed CDC25A(△E6) may have profound impacts on the biological effects of HCC cells Fig. A. To stuThe high expression of CDC25A(△E6) and its greater tumorigenesis ability in HCC prompted us to examine the diverse regulatory mechanisms of proteins in comparison to CDC25A(△E6) and CDC25A(L). The significantly activated protein might depend on the seemingly “slight transformation” of exon 6 skipping. Since the CDC25A phosphatase domain 376–482 aa) did not reside in its exon 6 (144–183 aa) region, it is tempting to speculate that CDC25A function largely depends on the expression and stabilization of mRNA and/or protein. PTMs came to light since they have been identified to jointly control protein fates. We predicted the potential modified sites in CDC25A exon 6 sites, and selected two ubiquitinating sites and one phosphorylating site  to CDC25A(△E6) is easily detected as a consequence of the SRSF10-related splicing mechanism, but it is unclear whether ubiquitin in CDC25A-specific sites could individually determine its protein fate. Next, GFP-CDC25A(L) plasmids with single or double ubiquitin site mutations were transfected into HCC cells. Both K150 and K169 in exon 6 were responsible for CDC25A ubiquitination, and two locus mutations could drastically inhibit its process. Intriguingly, the input of GFP showed more CDC25A shorter isoform expression in these mutated conditions compared to wild-type conditions, and this splicing tendency toward shorter isoforms was more obvious in the double-mutated system. The above results might also hint at the close association among dynamic ubiquitination in exon 6, splicing isoforms (such as CDC25A(△E6)), and the corresponding protein stability  and positively regulates the activities of CDK4, CDK6, and CDK2 . CDC25A To evaluate the impact of this phosphorylation event on CDC25A properties, we generated full-length CDC25A versions substituting S178 with alanine (A) or glutamic acid (E), which lack phosphorylation or mimic constant phosphorylation, respectively. As CDC25A phosphorylation is often accompanied by proteasome-dependent degradation, we utilized CHX and MG132 experiments to determine whether CDC25A phosphorylation was modulated by this mechanism . MutatioCDC25A lacking exon 6 contributes to protein stabilization and activation based on reduced ubiquitination and phosphorylation at specific sites, but whether SRSF10 is crucial for CDC25A-mediated aberrant cell cycle regulation still needs to be validated. Silencing of specific CDC25A (L), CDC25A (△E6), or all segments of CDC25A(FL) was employed to demonstrate the CDC25A exon 6 skipping-mediated effect Fig. .Fig. 7CDWe next evaluated the in vivo behavior and phosphorylation status of CDC25A(L) and CDC25A (△E6) in response to SRSF10 using xenograft models of HepG2 cells. In agreement with the above data that SRSF10 acted as an HCC promoter, we found markedly larger tumor volumes accompanied by increased CDC25A and shrinking p-CDC25AS178), and depletion of both CDC25A (△E6) and CDC25A (FL) effectively counteracted the promotion of tumorigenic ability in the presence of SRSF10, as anticipated  or AAAGACAAA [Most functional studies on human AAGACAAA . MeanwhiAAGACAAA , 42. TheAAGACAAA , 44. On In this study, we identified a large number of AS events through RNA sequencing following SRSF10, which were also preliminarily validated by our group. CDC25A is worthy of attention because its overexpression in cancer has frequently been associated with genetic instability and checkpoint abrogation, contributing to malignancy and a poor prognosis. CDC25A phosphatase plays a vital role in initiating the G1 to S phase transition via the cyclin E/Cdk2 complex . Apart fDespite the documented role of CDC25A in cell cycle regulation, its expression and kinase activity are tightly controlled by phosphorylation events. We observed that the phosphorylation of CDC25A was also reduced by SRSF10 transfection. CDC25A was previously phosphorylated on specific residues, and its upstream kinases described to date are CHK1 and CHK2, p38 MAPK, CK1α, and NEK11 . Site muIn summary, we show that SRSF10 promotes exon 6 exclusion of CDC25A pre-mRNA splicing that yields the production of CDC25A(△E6). Importantly, CDC25A(△E6) is proven to be more stable, and the nucleus is retained due to the deletion of ubiquitinating and phosphorylating sites in exon 6, thus playing a stronger cell cycle role than CDC25A(L). Our work implicates dysregulated exon skipping in HCC and provides proof-of-concept evidence for a potentially appealing therapeutic target in this process.Additional file 1:Table 1. Primers and shRNA used in this study.Additional file 2:Table 2. Antibodies for western blot, immunoprecipitation, immunofluorescence, and immunohistochemistry in this study.Additional file 3:Table 3. Correlation between SRSF10 expression and clinicopathologic characteristics of the hepatocellular carcinoma patients. Percentage values are shown in parentheses.Additional file 4:Fig. 1. Comparison of the SRSF10 mRNA level between HCC and adjacent nontumor tissue from the GEO database.Additional file 5:Fig. 2. Immmunohistochemical staining of SIRT1 in HCC tissue and matching adjacent nonneoplastic hepatocyte tissue.Additional file 6:Fig. 3. Correlation analysis between the five key genes and SRSF10 in HCC tissues.Additional file 7:Fig. 4. The CDC25A mRNA level and its related survival curve in HCC patients from the NODE, GEO and TCGA databases.Additional file 8:Fig. 5. Cell viability and invasion affected by wild-type and RRM-mutated SRSF10.Additional file 9:Fig. 6. Identification of the effects of endogenous CDC25A and exogeneous full-length CDC25A on HCC biological functions.Additional file 10:Fig. 7. Abundant CDC25A(△E6) in HCC results in more malignant phenotypes than the CDC25A(L) isoform.Additional file 11:Fig. 8. Comparison of the effects of endogenous CDC25A(L), CDC25A(△E6) and CDC25A(FL) on HCC biological functions.Additional file 12:Fig. 9. Measurement of the RNA stability of CDC25A by RT‒qPCR in presence of the transcriptional inhibitor Actinomycin D (ActD) at indicated time points.Additional file 13:Fig. 10. SRSF10 activates CDC25A through Ser178 dephosphorylation.Additional file 14:Fig. 11. CDC25A(△E6) production is indispensable for SRSF10-mediated HCC progression in vitro and in vivo.


Buyang Huanwu decoction (BYHWD), as one of the traditional Chinese medicine formulas, is widely used in the clinical treatment of lumbar disc herniation (LDH) with curative effect. It has the characteristics of multi-component, multi-target, and mutual synergy, but the mechanism of action is often unclear. It needs some research to explore the molecular mechanism of BYHWD in the treatment of LDH based on network pharmacology and molecular docking. Screen the active compounds of BYHWD and predict drug-related gene/protein targets, which could determine the specific target of BYHWD in the treatment of LDH. Construct the “Drugs-Compounds-Targets” network and search for the core targets. Use Gene Ontology functional enrichment analysis, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, and molecular docking verification to explore the possible molecular mechanism. Eighty-two effective compounds and 666 targets of BYHWD, 187 targets for LDH treatment, and 20 core candidate targets were excavated. A total of 3414 entries were identified by Gene Ontology enrichment analysis, 173 related signal pathways were identified by Kyoto Encyclopedia of Genes and Genomes enrichment analysis, and 5 core compounds were identified by molecular docking, which had a good affinity with core genes STAT3, JUN, AKT1, MAPK1, RELA, and PIK3CA. BYHWD may play the role of analgesic and improving function by synergistic anti-inflammatory and analgesic compounds, regulating cell metabolic differentiation, regulating immunity, and anticoagulation. BYHWD in the treatment of LDH may play a role in analgesia and improve function through multiple signaling pathways, including PI3K-Akt, mitogen-activated protein kinase, tumor necrosis factor, and interleukin-17. The PI3K-Akt signaling may be one of the key mechanisms. LDH patients showed a variety of clinical manifestations such as low back pain, numbness, fatigue of lower limbs, etc. In severe cases, cauda equina nerve injury occurs, resulting in defecation disorder and even paralysis. The occurrence and progress of LDH have a serious impact on the quality of life, and it also brings serious economic pressure to patients’ families due to the high disability rate. The treatment scheme of LDH includes conservative treatment and surgical treatment. Studies have shown that surgical treatment is more effective for patients with severe nerve root compression and inflammation symptoms, or without improvement after 3 to 6 months of non-surgical treatment. However, conservative treatment is still the first choice for LDH. Therefore, the development of complementary and alternative therapies for LDH is crucial.Lumbar disc herniation (LDH) is a clinical syndrome in which the annulus fibrosus of the lumbar disc is partially or completely ruptured due to various reasons, and nucleus pulposus tissue protrudes backward from the rupture opening, stimulating or compressing nerve root and cauda equina nerve. With the aging of population and the change of lifestyle, the incidence of LDH has increased significantly and tends to be younger.,5 The TCM formula such as BYHWD has the characteristics of multi-component, multi-target, and mutual synergy, but the mechanism of action is often unclear. Network pharmacology screens synergistic multiple compounds from TCM formula in a high-throughput manner and explains the combination rules and network regulatory effects of TCM formulas.,7 We analyzed key targets and signal pathways of BYHWD in the treatment of LDH and explored its possible molecular mechanism based on network pharmacology, bioinformatics, and molecular docking , one of the complementary therapies, has achieved significant effects in treating LDH and helped broaden the ideas of therapeutic approaches for LDH. Buyang Huanwu decoction (BYHWD), as one of the TCM formulas, including Huang-Qi, Dang-Gui, Tao-Ren, Hong-Hua, Chi-Shao, Chuan-Xiong, and Di-Long, is widely used in the clinical treatment of LDH with curative effect.ing Fig. .https://tcmspw.com/tcmsp.php/); PubChem Database (https://pubchem.ncbi.nlm.nih.gov/); Swiss ADME Database (http://www.swissadme.ch/); Swiss Target Prediction Database (http://swisstargetprediction.ch/); Gene Cards Database (https://www.genecards.org/); Database of Online Mendelian Inheritance in Man ; Pharm GKB Database (https://www.pharmgkb.org/); DisGeNET (https://www.disgenet.org/); The Genetic Association Database ; Uniprot Database (https://www.uniprot.org/); STRING 11.0 (https://string-db.org/); and Protein Date Bank (PDB) (https://www.rcsb.org/).Database and Analysis Platform of Systematic Pharmacology of Traditional Chinese Medicine  was used for text, document collection, and data collation; R 4.0.3 software (R Development Core Team) and associated toolkits were used to analyze and complete visualization; Cytoscape 3.8.2 ) and related plug-ins are used to build visual networks; ChemBio 3D Ultra 14.0.0.117 (PerkinElmer) was used to convert the 2D structure to 3D form; PyMOL 2.4.0 (Schrodinger) was used to remove small-molecule ligands and water molecules and visualize them; Auto Dock Tools 1.5.6 (The Scripps Research Institute) software was used for hydrogenation and other processes; Vina 1.1.2 (Dr. Oleg Trott from The Scripps Research Institute) was used to process molecular docking and analyze binding activity; and GraphPad Prism 8.3.0 (GraphPad Software) was used to build heatmaps. This study was approved by the Ethics Committee of the First Affiliated Hospital of Zhejiang Chinese Medical University.,9 We collected potential protein targets for each drug in “Related Targets”. For drugs that could not be retrieved in the database, their ingredients were obtained by searching the literature. We downloaded their structures from the PubChem database and entered them into the Swiss ADME platform. In the results of “pharmacokinetics”, “GI absorption: high” was set as the precondition, and the standard that 2 or more other indicators display “yes” was used to screen compounds.,11 We subsequently obtained the compound corresponding acting target proteins by inputting the compounds in the Swiss Target Prediction platform and eliminated items with “probability” as “0”. Finally, we filtered the items by “reviewed” in the UniProt database with the species selection “Homo sapiens (human)” to normalize the resulting protein targets.Each Chinese herb included in BYHWD  was used as keywords for retrieval in the TCMSP database. The effective compounds of Chinese herbs were obtained from “Ingredients” and screened according to 2 criteria, “oral bioavailability ≥30%” and “drug-like index ≥0.18”.We selected “lumbar disc herniation” as the keyword and screened disease-related targets in GeneCards, OMIM, PharmGKB, DisGENET, and GAD databases. The Venn diagram was drawn by R 4.0.3 software and packages. We eliminated the duplicate items in Excel and obtained unique LDH-related targets.We used R software to match and map drug prediction targets to disease targets. We drew the Venn diagram of the “drugs-disease targets” intersection and extracted the common targets—the key targets of BYHWD in treating LDH. Then we used Cytoscape to form a “Drugs-Compounds-Targets” visualization network.We uploaded the key proteins obtained from network analysis to the online STRING 11.0 (ELIXIR infrastructure) database, setting the type as “homo sapiens”, setting the confidence threshold as “highest confidence (0.900)”, hiding the disconnected nodes, and kept other setting parameters unchanged to obtain protein-protein interaction (PPI) network.We imported the PPI network into Cytoscape and CytoNCA network topology analysis plug-in was used to calculate the betweenness centrality, closeness centrality, degree centrality, eigenvector centrality, local average connectivity, and network centrality. We screened out the nodes whose above indexes were greater than the median of all gene nodes of each index by R software. Then we created the sub-network, and key genes were calculated and screened again.We used R software “ClusterProfiler” package to perform Gene Ontology (GO) function enrichment analysis at the different biological process, cellular component, and molecular function levels of key targets. Then Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was carried out at key targets.We downloaded the active ingredients’ 2D structure of small molecule ligands from the PubChem database, and imported them into ChemBio3D Ultra, then calculated and set them as the 3D structure with minimum free energy. We downloaded 3D structure files of core target proteins from the PDB database and imported them into PyMOL software to remove small-molecule ligands and water molecules, then we used Auto Dock Tools software for hydrogenation. Finally, we performed molecular docking of ligand and receptor via Vina, analyzed binding activity, and constructed the heatmap with Prism. and 20 effective compounds were screened on the SwissADME (Swiss Institute of Bioinformatics) platform. Finally, we obtained a total of 82 effective ingredients by combining all the active ingredients and removing repetitive items. A total of 3107 targets were corresponding to the effective ingredients of these 7 drugs. The protein targets were standardized, and 666 unique protein targets were obtained after removing unrecognized and duplicate items.According to the TCMSP database, the effective compounds of Astragalus Mongholicus, Angelica Sinensis, Radix Paeoniae Rubra, Peach Kernel, Safflower, and Ligusticum chuanxiong were 119, 66, 189, 87, 189, and 125, respectively. Then, based on oral bioavailability ≥30% and drug-like ≥0.18, 103 compounds were screened out, including 20 of Astragalus Mongholicus, 2 of Angelica Sinensis, 29 of Radix Paeoniae Rubra, 23 of Peach Kernel, 22 of Safflower, and 7 of Ligusticum chuanxiong. Eighty-six compounds of “Earthworm” were obtained through literature reports,A number of 396, 17, 1658, 1, and 3 disease targets of LDH were obtained in the databases of Gene Cards, OMIM, Pharm GKB, DisGeNET, and GAD, respectively, and 1953 LDH-related targets were obtained after merging and de-duplication Fig. A. After We used Cytoscape to draw the relationship between the above active ingredients and targets. Two hundred fifty-one nodes and 959 relationship edges were obtained, and a visual network diagram of “Drugs-Compounds-Targets” was constructed. Compound nodes were presented as pie charts and different colors, and different colors represent that the compounds come from multiple Chinese herbs and drugs Fig. .P value <1.0e−16 ” according to the complexity of the network. We hid the disconnected nodes and kept other setting parameters unchanged, and ultimately constructed the PPI network diagram. The PPI network contains 187 proteins, 995 action edges, and 324 expected edges with enrichment The above data files were imported into Cytoscape to generate a protein interaction network diagram, and the betweenness centrality, closeness centrality, degree centrality, eigenvector centrality, local average connectivity, and network centrality were calculated by CytoNCA network topology analysis plug-in, and finally, 175 nodes and 995 interaction edges were obtained. The nodes with the above indexes greater than the median of all gene nodes of each index were screened out, and a total of 52 nodes and 402 edges were obtained. Then the matrix was imported into Cytoscape to extract sub-networks, and 20 key nodes and 224 edges were calculated and screened again. Finally, the core network was extracted, and the nodes were key genes. The corresponding indexes were calculated in descending order of degree . Its biological processes mainly include epithelial cell proliferation, response to lipopolysaccharide, response to bacterial molecules, gland development, and so on. Cell compounds mainly include membrane raft, membrane microdomain, membrane region, transcription regulatory complex, focal adhesion, and so on. Molecular functions mainly include DNA and RNA transcription factor binding, protease activity, cytokine receptor binding, nuclear receptor activity, transcription factor activity, etc  signaling pathway, hepatitis B, tumor necrosis factor (TNF) signaling pathway, interleukin (IL)-17 signaling pathway, etc. Thirty pathways with a large number of enriched genes were screened out, of which the PI3K-Akt signaling pathway was the most significantly enriched Fig. B and C.−1, indicating that the ligand has a certain binding activity with the receptor. The binding activity is better when it is less than –5.0 kcal mol−1, and strong when it is less than –7.0 kcal mol−1. The top 8 active ingredients of the “Drugs-Compounds-Targets” network, including quercetin, kaempferol, beta-sitosterol, (+/–)-18-hydroxy-5Z, 8Z, 11Z, 14Z, 16E-eicosapentaenoic acid, luteolin, tridecanoic acid, arachidonic acid, and baicalein, were individually docked with the top 6 core protein targets, including STAT3, JUN, AKT1, MAPK1, RELA, and PIK3CA, and the binding energy threshold was set as less than –5.0 kcal mol−1. The results showed that quercetin, kaempferol, beta-sitosterol, luteolin, and baicalein were successfully docked to the corresponding proteins with good stability. Among them, the strongest binding was between beta-sitosterol and AKT1 , and except the binding energy between beta-sitosterol and STAT3 was –6.5 kcal mol−1, all others had strong binding activity. This indicated that these compounds played a role through multiple targets. The binding activity of tridecanoic acid was the weakest in the overall level. Its binding activity with AKT1 was –5.6 kcal mol−1, which was stable, and the binding activities with other genes were greater than –5.0 kcal mol−1, which were relatively poor. All the compounds were successfully docked with AKT1 and had good binding activity  by inactivating the L-PGS/PI3K/Akt pathway. Upregulation of Nav1.6 can increase neuronal excitability and participate in neuropathic pain of DRG. By activating the TNF-/STAT3 pathway, histone H4 is superacetylated in the STAT3-mediated DRG Scn8a promoter region, resulting in L5-VRT-induced neuropathic pain.One hundred seventy-three signaling pathways were found by KEGG enrichment analysis. The pathways with higher gene ratio include PI3K-Akt signaling pathway, MAPK signaling pathway, virus infection-related pathway, tumor-related pathway, diabetic complication-related pathway, TNF signaling pathway, IL-17 signaling pathway, etc. Among them, the PI3K-Akt signaling pathway was the most significant enrichment. LDH has no significant correlation with tumor-related pathways and virus infection-related pathways, so we would not pay attention to them for the time being. IL-17A promotes intervertebral disc degeneration by inhibiting autophagy through activation of the PI3K/Akt/Bcl-2 signaling pathway.However, there are also deficiencies. First, the information of drug ingredients in databases and literature may still not be exhaustive, and insect drugs have a different research system than herbs. Then again, this study was only corroborated by relevant literature. Therefore, in a follow-up study, our group intends to intervene biological samples with full prescription drug delivery and decoupled drug delivery, and carry out high-throughput assays such as transcriptomics and proteomics to obtain the effect target profiles of BYHWD, to provide a high-quality data resource for more comprehensive annotation of the action mechanism of BYHWD.In this study, we explored the mechanism, core targets, and signaling pathways of BYHWD in the treatment of LDH through network pharmacology and bioinformatics analysis. It was speculated that BYHWD plays a role in the treatment of LDH through multiple signaling pathways such as PI3K-Akt, MAPK, IL-17, and TNF, and PI3K-Akt signaling pathway may be one of the key mechanisms. These were conducive to optimize the experimental design, provide a reference for new drug development, and save costs to a certain extent. We also hope to promote BYHWD as a supplement and alternative treatment for LDH.GY wrote the paper. ZHJ, WXJ, ZSX, and LSJ performed the literature search and revised the paper. TPJ and LSJ guided the writing of the paper and reviewed the manuscript. All authors critically reviewed progressive drafts of the manuscript and approved the final version.Methodology: Shanxing ZhangProject administration: Shuaijie LvResources: Shuaijie LvSupervision: Peijian Tong, Shuaijie LvVisualization: Xiaojian Wang, Xiaojian Wang,Writing – original draft: Xiaojian Wang, Yong GuWriting – review & editing: Haijia Zhu


This study is aimed at exploring the molecular mechanism of Shufeiya recipe in the treatment of pulmonary hypertension (PH) using network pharmacology and molecular docking analysis.  Active components and their target proteins in the recipe were screened using the TCMSP database. PH-related core proteins were screened using GeneCards, STRING database, and Cytoscape-v3.8.2. Common proteins were obtained by intersection of the target proteins of these recipe active components and pH-related core proteins. Rx64 4.0.2 software was used to perform GO functional enrichment analysis and KEGG pathway enrichment analysis on the common proteins to obtain pathway-enriched proteins, and then core enriched proteins were further screened. We analyzed the relationship between the active components and pathway-enriched proteins using Cytoscape-v3.8.2. AutoDock Vina was used to dock their core proteins into the components.  Shufeiya recipe contained 67 active components. 61 common proteins of the target proteins of the active components and PH-related core proteins were obtained. The treatment involved both functional and pathway regulations. The core pathway-enriched proteins were prostaglandin G/H synthase 2 (PTGS2), epidermal growth factor receptor (EGFR), and RAC-alpha serine/threonine-protein kinase (AKT1), and their binding energies to the corresponding components were all less than -5 kJ•mol-1.  It was found that the main mechanism might be the active components acting on the core pathway-enriched proteins to regulate related signaling pathways, thereby playing roles in anticoagulation, vasodilation, anti-PASMC proliferation, promotion of PAECs apoptosis, inhibition of oxidative stress, and anti-inflammatory effects. Pulmonary hypertension (PH) is a chronic progressive pulmonary vascular system disease caused by pulmonary arteriole obstruction, and it is characterized by pulmonary artery vasoconstriction and remodeling, increased pulmonary circulatory resistance, and increased pulmonary artery pressure (mean pulmonary artery pressure at rest ≥ 25 mmHg). Its clinical manifestations include chest tightness, shortness of breath, fatigue, and dyspnea, which can eventually lead to right-sided heart failure and death . EpidemiSalvia miltiorrhiza (Danshen), safflower (Honghua), and Cornus officinalis (Shanzhuyu). Previous animal studies suggested that Shufeiya recipe could downregulate serum reactive oxygen species levels in rats with pulmonary hypertension induced by monocrotaline; upregulate serum NO, sGC, cGMP, PKG, PTGS1, PTGS2, and Mn-SOD activity; inhibit oxidative damage; promote the expression of SIRT3, FOXO3a, p-PI3K, p-AKT, and p-eNOS protein in the pulmonary artery; downregulate the protein expression of Ras, p-MEK1/2, p-ERK1/2, and c-fos in the pulmonary artery; and reduce the thickening of the pulmonary vascular wall and pulmonary artery pathological injury such as cavity stenosis, thereby reducing pulmonary artery pressure in the model group [The clinical practice of PH treatment in our country not only fully applies modern research results but also recognizes that traditional Chinese medicine (TCM) has the synergistic effects of improving clinical symptoms and quality of life, increasing exercise tolerance, and even improving prognosis. The combination of Chinese and western medicine has become a generally accepted treatment strategy for PH in our country. Based on his clinical practice and researches of many years, Professor Mao Jingyuan, as a “Qihuang Scholar,” and national leading talent of TCM, concludes that Shufeiya recipe can be used for the treatment of PH; this recipe is composed of platycodi radix (Jiegeng), el group , 5. Howehttp://tcmspw.com/tcmsp.php) [Salvia miltiorrhiza, safflower, and Cornus officinalis were screened, and the target proteins were imported into the UniProt database (https://www.uniprot.org/) [Based on the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) (msp.php)  and the ot.org/)  to standhttp://www.GeneCards.org/) [http://string-db.org) [Based on the GeneCards database (ds.org/) , PH-rela-db.org)  was used-db.org)  was usedP < 0.05 as the screening criteria. GO functional enrichment analysis mainly included three aspects: biological processes (BP), molecular functions (MF), and cellular components (CC). The top ten functions obtained in each aspect by GO enrichment analysis were visualized using a bar chart. The top 30 signaling pathways obtained by KEGG pathway enrichment analysis were visualized using a bubble chart, where the ordinate represents the pathway name, the abscissa represents the gene ratio, the bubble size represents the number of enriched proteins, the color represents the degree of enrichment, and the darker the red, the stronger the enrichment. PH-related pathways were screened by referring to the literature, and enriched proteins were obtained from KEGG pathway enrichment analysis. The map of the pathways most significantly related to the treatment of PH by Shufeiya recipe was obtained from the KEGG database (https://www.kegg.jp/) [The “drug-disease” targets were subjected to GO functional enrichment analysis, and KEGG pathway enrichment analysis using Rx64 4.0.2 software , with P egg.jp/) . The redThe enriched proteins of PH-related pathways were imported into the STRING database, and Cytoscape-v3.8.2 software was used to screen the core enriched proteins of PH-related pathways with the condition that the degree, betweenness, closeness, network, and LAC were all greater than the median value. Then, PH-related pathways and these enriched proteins were imported into Cytoscape-v3.8.2 software for topology analysis and visualization, and a pathway-target topology network was constructed.The active components of Shufeiya recipe and pathway-enriched proteins were imported into Cytoscape-v3.8.2 software for topology analysis and visualization, and the component-target topology network was constructed, where nodes represented components and targets, and edges represented interactions between nodes.https://pubchem.ncbi.nlm.nih.gov/) [https://www.uniprot.org/), and entered into the PDB database (http://www.rcsb.org/) [Molecular docking was performed with the core-enriched proteins as the receptor, and the corresponding drug components as the ligand. The 2D structure of the drug component was downloaded from the PubChem database (ih.gov/)  and imposb.org/)  to obtaisb.org/) , “removesb.org/) , added HSalvia miltiorrhiza, 10 active components from safflower, and 4 active components from Cornus officinalis  and an imbalance in the ratio of antioxidant enzymes to lipid peroxides , 25. ROSmodeling . The MAPferation . PH causmodeling . p38 MAPmodeling . ERK actmodeling , 29. Themodeling , 30. Formodeling , 30. Scrmodeling ; luteolimodeling ; baicalemodeling ; kaempfemodeling ; tanshinmodeling –36; and modeling , 38. Thesilicon computers, and predicting herb targets only used one platform (TCMSP). Therefore, we will explore more detailed information about the recipe by searching a few more platform, such as BATMAN-TCM, Herb, and TCMID, and in vivo and in vitro experiments need to be performed for further validation in the future.However, there are some limitations in this study. Our results were derived only from the analysis and prediction of the public database and In summary, the molecular mechanism of Shufeiya recipe in the treatment of PH was analyzed using network pharmacology. We screened the active components and their targets of Shufeiya recipe in the treatment of PH, constructed component-target networks, analyzed their biological process annotations, and signaling pathways, and systematically studied the potential mechanism of Shufeiya recipe in treating PH. It was found that the main mechanism of this recipe in the treatment of PH might be that the active components of this recipe, including quercetin, luteolin, baicalein, kaempferol, tanshinone IIA, and cryptotanshinone, acted on the core proteins, including PTGS2, EGFR, AKT1, VEGFA, and MAPK1, to regulate signaling pathways such as PI3K-AKT, IL-17, TNF, MAPK, HIF-1, and Toll-like receptors, thereby playing the roles of anticoagulation, vasodilator, anti-PASMC proliferation, promotion of PAEC apoptosis, inhibition of oxidative stress, and anti-inflammatory effects. Our present study identified the core targets of Shufeiya recipe in the treatment of PH at the molecular level, clarified its potential material basis and mechanism, and provided a general reference for the clinical application and experimental research of traditional Chinese medicine in the treatment of PH. However, these results need to be confirmed by more experiments and clinical practices in the future.


Gynostemma pentaphyllum (Thunb) for its anti‐insulin resistance effect indicates that potential therapeutic value may be found in Thunb for NAFLD. Hence, this research aims to discover the latent mechanism of Thunb for NAFLD treatment. To achieve the goal of discovering the latent mechanism of Thunb for NAFLD treatment, molecular docking strategy integrated a network phamacology was adopted in the exploration. We acquire Thunb compounds with activeness from TCMSP database. We collect the putative targets of Thunb and NAFLD to generate the network. Key targets and mechanism are screened by PPI analysis, GO and KEGG pathway enrichment analyses. Molecular docking simulation is introduced into the study as assessment method. Through network analysis and virtual screening based on molecular docking, 2 targets (AKT 1 and GSK3B) are identified as key therapeutic targets with satisfying binding affinity. Main mechanism is believed to be the biological process and pathway related to insulin resistance according to the enrichment analyses outcomes. Particularly, the P13K–AKT signalling pathway is recognized as a key pathway of the mechanism. In conclusion, the study shows that Thunb could be a potential treatment against NAFLD and may suppress insulin resistance through the P13K–AKT signalling pathway. The result of the exploration provides a novel perspective for approaching experimental exploration.As a progressive chronic disease, the effective treatment for non‐alcoholic fibre liver disease (NAFLD) has not yet been thoroughly explored at the moment. The widespread use of  It is currently recognized as a commonly seen long‐lasting and recurrent hepatic illness almost throughout the world, which is also most common for westerners.Gynostemma pentaphyllum (Thunb), a plant belonging to the Cucurbitaceae family, has been mentioned in the books to have various therapeutic effects.In China, nowadays, the traditional Chinese medicine (TCM) has been made into practice for centuries. Increasing attention to it has been attracted because of its great effectiveness and minimal side effect upon preventing and treating metabolic disturbance, particularly in NAFLD.NAFLD is regulated by multiple genes or targets. For single target highly selective ligands drugs often do not change the overall state of the disease, it is difficult to effectively control or prevent the development of disease; therefore, the outcomes of the clinical trials were not satisfactory. Morphy et al. provide a new idea for drug discovery: multi‐target therapy.22.1http://lsp.nwu.edu.cn/tcmsp.php).The data of Thunb are mainly from a verified target databases: (1) pharmacology database of traditional Chinese medicine system2.2In the clinical application of Thunb, oral administration has been normally utilized in Chinese medicine. Therefore, these two ADME models of oral bioavailability OB16 and d2.3http://lsp.nwu.edu.cn/tcmsp.php) and SymMaphttps://www.symmap.org/), to predict these targets of Thunb components. Considering that every interaction put forward should possess traceability to the original information sources in this database.Currently, there are many methods to predict drug targets, according to its prediction principle, classification of those approaches into four types is performed:(1) Structure‐based prediction approaches, which are based on the structural properties of compounds; (2) Molecular Activity‐based prediction approaches, which are upon the basis of the protein interaction network (PIN); (3) Side‐effect‐based prediction approaches upon the basis of the adverse reactions; (4) Multi‐Omics‐based predictions methods, upon the basis of the predicting theory that identical medication has action upon those identical targets.2.4http://www.drugbank.ca). ‘Non‐alcoholic fibre liver disease/ non‐alcoholic steatohepatitis’ should be utilized to be a keyword in searching the GeneCardshttp://www.genecards.org/).Depending on the features of every database, this exploration chose to use distinctive keywords and standards to retrieve NAFLD‐related targets. ‘non‐alcoholic fibre liver disease/ non‐alcoholic steatohepatitis’ should be utilized to be a keyword in searching the Drugbank database2.5https://string‐db.org/), the identifiers meant ‘Homo sapiens, multiple proteins’; the data sources of PPI were chosen. After that, construction of PPI networks for targets in relation to NAFLD/NASH and Thunb was done. Identification of essential targets in anti‐NAFLD and anti‐NASH system should be performed through utilization of network data for topology features analyses.The normal life activities of cells are inseparable from the interaction of proteins and other molecules, like genes, small molecule compounds and other proteins. A complete organism interaction set can be shown through a PPI network, in which a single protein is thought to be a node, while a pair of proteins have a physical interaction as an edge.2.6http://david.ncifcrf.gov/), for performing KEGG pathway analyses and GO functional analyses. Functional annotation of enrichment was performed by Benjamini correction (P < 0.05). KEGG pathway enrichment maps and GO enrichment were performed under R version 3.2.0.As a reference knowledge base, KEGG can be utilized to interpret massive molecular data sets from biology, like genome and metagenome sequences. It has accumulated experimental knowledge of advanced functions of cells and organisms represented by KEGG molecular network, comprising KEGG pathway diagram, Brite hierarchy and KEGG module.2.7http://cytoscape.org) as the biomolecular interaction network integration model of software environment, the following were built:(1) the compound‐target network; (2) PPI network of compound‐NAFLD/compound‐NASH target; and (3) compound‐target‐pathway network.Using Cytoscape3.6.1Three metrics had been utilized for evaluating the topology features for every node. (1) ‘Betweenness Centrality’: The ratio of nodes has the shortest path through the network,2.82.8.1http://www.pdb.org/). Modification of those complexes already downloaded was done through utilizing the AutoDock Tools 1.5.6http://mgltools.scripps.edu/documentation/links/autodock) for removing the water molecules, which had been utilized for preparing receptors, comprising the addition of hydrogen and set‐up of docking paraments. Upon maximizing the settings, ‘Grid box’ had been utilized for performing the subsequent docking.Downloading of the crystal structures for hub genes was made out of RCSB Protein Data Bank2.8.2https://tcmspw.com/tcmsp.php) and applied minimum energy to do subsequent docking.Prior to docking, we downloaded the 3D structure of Thunb from TCMSP , altogether, 24 active constituents had been screened, and Table 3.2According to Figure 3.3Upon the basis of outcomes hereinabove, the 150 assumed targets of Thunb were mapped to 937 NAFLD‐related targets for obtaining overlapping targets. Thus, 84 targets had been confirmed to be candidates for the treatment of NAFLD Figure  and 91 t3.4For additionally expounding the mechanism of drug therapy in a systematical manner, utilization of DAVID had been done for performing enrichment analyses of genes. The top10 KEGG pathways and GO items were selected according to gene count and P value. According to the findings from biological processes, the targets were enriched in negatively regulated apoptotic process (GO:0043066), signal transduction (GO:0007165), positively regulated apoptotic process (GO:0043065), response to insulin (GO:0032868) and glucose metabolic process (GO:0006006) Figure . A total3.5In this study, we investigated the potential interaction activities between 13 hub genes of Thunb and their relevant compounds by molecular docking verification. Meanwhile, the docking affinity values revealed by Autodock Vina4Recently, an increasing quantity of explorations had been conducted in medication discovery and combination therapy of traditional Chinese medicine for complex diseases such as NAFLD, among which network pharmacological methods have played an important role. The multiply components and multiply target features of traditional Chinese medicine make it possible to control symptoms through different biological processes and effectively prevent the deterioration of the disease.Upon integration and consolidation of data out of multiple accessible databases, 4 active compounds of Thunb had action upon 84 different targets in association with NAFLD and 91 different targets in association with NASH. Our previous studies have shown that Thunb can reduce insulin resistance in NAFLD,A widely reported viewpoint rests with that insulin resistance has a central function during those procedures through permitting too much fatty acid to flow into adipose tissue and impairing the disposal of peripheral glucose.As is universally known, P13K/Akt/GSK3β pathway functions as one of the most important insulin signalling pathways. Massive proof indicated the direct increase in de novo lipogenesis by deregulated P13K/Akt/GSK3β signalling pathway and indirect elevation of FFA flux to the liver through the increase in adipose tissue lipolysis.Glycogen synthase kinase‐3 (GSK‐3) serves as a post‐insulin receptor signalling protein. There are two isomers, GSK‐3β and GSK‐3α,Cunzhi Wang: Conceptualization (lead); data curation (lead); formal analysis (lead); investigation (lead); methodology (lead); resources (lead); validation (lead); visualization (lead); writing – original draft (lead). Wenbin Chen: Methodology ; project administration ; supervision ; validation . Yanyan Bai: Conceptualization ; project administration ; supervision ; writing – review and editing . Pengrui Wang: Formal analysis (supporting); investigation (supporting); resources (supporting); software (supporting).The authors make a declaration that there is non‐existence of any competitive economic interests or personal relations amid themselves, because of which it will not produce any impact on the work involved in this article.