Prunella vulgaris L. (PV) in the treatment of papillary thyroid carcinoma (PTC) by using network pharmacology combined with molecular docking verification. Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform database was used to predict the main active components of PV, Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, PubChem, and Swiss Target Prediction databases were used to obtain the corresponding targets of all active components. Targets collected for PTC treatment through Gene Cards, Digest and Online Mendelian Inheritance in Man databases respectively. The Search Tool for the Retrieval of Interaction Gene/Protein database was used to obtain the interaction information between proteins, and the topology analysis and visualization were carried out through Cytoscape 3.7.2 software (https://cytoscape.org/). The R package cluster profiler was used for gene ontology and Kyoto encyclopedia of genes and genomes analysis. The “active ingredient-target-disease” network was constructed by using Cyto scape 3.7.2, and topological analysis was carried out to obtain the core compound. The molecular docking was processed by using Discovery Studio 2019 software, and the core target and active ingredient were verified. The inhibition rate was detected by CCK8 method. Western blot was used to detect the expression levels of kaempferol anti-PTC related pathway proteins. A total of 11 components and 83 corresponding targets in the component target network of PV, of which 6 were the core targets of PV in the treatment of PTC. It was showed that quercetin, luteolin, beta (β)-sitosterol, kaempferol may be the core components of PV in the treatment of PTC. vascular endothelial growth factor A, tumor protein p53, transcription factor AP-1, prostaglandin endoperoxidase 2, interleukin 6, and IL-1B may be important targets for the treatment of PTC. The main biological processes mainly including response to nutrient levels, response to xenobiotic stimulus, response to extracellular stimulus, external side of plasma membrane, membrane raft, membrane microdomain, serine hydrolase activity, serine-type endopeptidase activity, antioxidant activity, etc IL-17 signaling pathway, and PI3K-Akt signaling pathway may affect the recurrence and metastasis of PTC. Kaempferol may significantly reduce the activity of Papillary cells of human thyroid carcinoma bcpap cell lines cells compared with quercetin, luteolin, β-sitosterol. Kaempferol may reduce the protein expression levels of interleukin 6, vascular endothelial growth factor A, transcription factor AP-1, tumor protein p53, 1L-1B and prostaglandin endoperoxidase 2, respectively. PV has the characteristics of multi-components, multi-targets and multi- pathways in the treatment of PTC, which network pharmacology help to provides a theoretical basis for the screening of effective components of PV and further research.To analyze the molecular mechanism of  Among thyroid cancers, papillary thyroid cancer (PTC) has the highest incidence rate, accounting for more than 80% of thyroid malignant tumors. The formation of PTC is a very complex biochemical process, characterized by the abnormality of various molecules. Large scale genome research shows that genetic changes play a key role in the occurrence and development of PTC, but the reasons for its continued high incidence are not yet clear. Thyroid disease screening has become a routine examination item of health examination, but there is still a lack of thyroid disease screening in some people’s health examination items, and some people do not have the awareness of regular health examination, and they do not go to the hospital until they find a neck lump or a symptom of neck discomfort. At present, total thyroidectomy, radioiodine therapy and thyrotropin suppression therapy have been highly developed and widely accepted.Globally, among the malignant tumors of the thyroid endocrine system, thyroid cancer has a high incidence rate, accounting for more than 80% to 90% of all endocrine tumors.Prunella vulgaris L. (PV), a traditional Chinese herbal medicine in China, is a plant of Labiatae. It is distributed around the world, mainly in temperate and tropical mountains, such as Europe, Asia, northwest Africa and North America. It is mainly distributed in the Huaihe River basin and the middle and lower reaches of the Yangtze River basin in China. According to the Pharmacopoeia of the People’s Republic of China, it has the effects of clearing the liver, purging fire, improving eyesight, dispersing knots, and reducing swelling in clinical efficacy. Therefore, PV is also commonly used in clinical treatment of thyroid cancer, breast cancer, liver injury, hypertension, hyperglycemia, prostate diseases, and other diseases.–12The adverse reaction of Traditional Chinese Medicine (TCM) is relatively small, which can help reducing the recurrence and metastasis of tumors, improving the quality of life of patients, with obvious advantages.PV mainly contains terpenoids, phenolic acids, organic acids, sterols, coumarins, flavonoids, polysaccharides, and volatile oils. Modern pharmacological studies have shown that its extracts have a variety of biological activities, such as antioxidation, regulating immune function, anti-inflammatory, antibacterial, antiviral, and regulating the microenvironment of tumor metastasis.,11 With the extensive clinical application of PV, the experimental research of PV has gradually deepened, and its pharmacological effects and molecular mechanism of action are gradually clear. However, the active ingredients contained in PV are relatively complex, and its main medicinal substances and pharmacological mechanism are still unclear. The inhibition of thyroid cancer, active ingredients and potential action targets of PV are still lack of systematic research. The network pharmacology technology can be used to obtain the relationship between “multi components and multi targets” and protein interaction, predict the TCM and its molecular mechanism of action, and make the research of TCM extend better. This study adopts network pharmacology combined molecular docking methods to explore the effective components and potential mechanism of action of PV in inhibiting PTC, so as to provide more theoretical support for clinical use of PV in treating PTC.Network pharmacology can successfully establish the relationship among “drugs-components-targets-diseases” and reveal the complex functions of Chinese medicine at multiple levels and systems.http://tcmspw.com/tcmsp.php) to search the chemical components of PV, select the components with oral bioavailability≥30% and drug like property≥0.18 as the effective components, download the corresponding chemical structure, and save it in MOL2 format.Using Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) (http://www.swisstargetprediction.ch/) database and PubChem database (https://pubchem.ncbi.nlm.nih.gov/) respectively. The target library corresponding to the main active components of PV was obtained by searching the corresponding targets of all active components in PV and removing duplicate genes. Using the Gene Cards database (https://www.genecards.org/), Disgenet database (https://www.disgenet.org/), and Online Mendelian Inheritance in Man database (https://omim.org/) respectively to collects targets for PTC treatment with the key word “papillory thyroid cancer” OR “PTC,” removes duplicate genes, and obtains the corresponding target library.Through TCMSP database, Swiss Target Prediction  to obtain the interaction information between proteins, and conduct topological analysis and visualization through R language.In order to further study the action mechanism of PV in the treatment of thyroid cancer, the R package cluster profiler was used to conduct GO and KEGG analysis on the intersection targets. The threshold values were set at P<.05, q<0.05, and finally 20 results with the lowest P value were retained for visualization. To validated the anti-PTC mechanism of PV across the key targets and multiple pathways, the KEGG mapper functional analysis was utilized to mark the target genes on the pathway associated with PTC.In order to further study the core target function and the main action pathway of https://cytoscape.org/). The function of “network analyzer” is used for topological analysis to obtain the core active ingredients.In order to analyze the correlation between active compounds, a network of “active ingredient-target-disease” was constructed by using Cytoscape 3.7.2 software  database in PDB format. First, the water molecules in the PDB structure are removed, and the docking active pocket is defined by the original ligand molecules. After setting the docking parameters, the ligand molecules in the crystal structure are extracted and re docked to the predefined active pocket. At the same time, the root mean square difference between the docked ligand molecule conformation and the initial conformation in the crystal structure is calculated. If the root means square difference value is <2.5, the molecular docking result is considered reliable. On this basis, molecular docking was performed on the core target and corresponding compounds to verify the binding strength of the core target and the main active components of 2 constant temperature incubator, Eppendorf 5702R low-speed centrifuge.Human thyroid papillary carcinoma cell Papillary cells of human thyroid carcinoma bcpap cell lines (BCPAP) was purchased from the Shanghai Cell Bank of the Chinese Academy of Sciences. Quercetin (CAS No. 117-39-5), luteolin (CAS No. 491-70-3), beta-sitosterol (β-sitosterol) (CAS No. 83-46-5), kaempferol (CAS No. 520-18-3) were purchased from Selleck China company respectively. One thousand six hundred-forty culture medium, dimethyl sulfoxide (DMSO), fetal bovine serum, penicillin streptomycin double antibody, 0.25% trypsin, cell counting kit 8 (CCK8), and DMSO purchased from Sangon Biotech (Shanghai) Co., Ltd. RIPA Lysis Buffer, rabbit derived vascular endothelial growth factor A (VEGFA) antibody, tumor protein p53 (TP53) antibody, transcription factor AP-1 (JUN) antibody, prostaglandin endoperoxidase 2 (PTGS2) antibody, interleukin 6 (IL6) antibody, IL-1B antibody, rabbit derived House keeping protein.  antibody and goat anti-rabbit IgG were purchased from Beyotime Biotechnology Co., Ltd. and ThermoFisher Scientific Co., Ltd. respectively. The instrument includes BioRad full-automatic microplate reader, BioRad chemiluminescence gel imaging system, OLYMPUS IX51 inverted microscope, MCO-15AC SANYO CO2 incubator. Cell growth was observed under inverted microscope, and cells in logarithmic growth phase were taken for subsequent experiments. Grouping method: different concentration of drug group including: 2.5, 5, 10, 20, 40, 80, 160 µmol/L, 4 active compounds quercetin, luteolin, β-sitosterol, kaempferol of PV respectively. Control group: the same volume of DMSO (0.01%). BCPAP cells were treated with 5 × 103 cells (100 μL suspension) was inoculated into 96 well plates. Place it in a 37°C, 5% CO2 incubator for 24 hours, and then the cell monolayer will cover the bottom of the hole. The concentration of 4 active compounds added to the cells at 2.5, 5, 10, 20, 40, 80, 160 µmol/L in complete medium 100 μL, each with 3 double wells respectively. Add 90 μL serum free 1640 medium and 10 μL CCK8 solution per hole, continue to culture for 2 hours, and then measure the absorbance of each hole with the microplate reader at 450 nm wavelength. Repeat the experiment for 3 times. Cells were continued to culture for 48 and 72 hours, and measured the cell activity in each group at 24, 48, 72 hours respectively. Measured the OD value of each well on the computer for the sample to be tested. The cell survival rate is expressed as a percentage, and calculate the half inhibition rate (IC50).BCPAP cell was cultured in 1640 medium containing 10% fetal bovine serum and 1% penicillin streptomycin at 37°C and 5% COWestern blot method was used to detect the expression levels of anti-PTC related proteins. Kaempferol with the final concentration of 10, 20, 40, 80 µmol/L was added to BCPAP cells, culture for 48 hours, collect cells on ice, extract the total protein of each group of cells by RIPA lysis buffer assay kit. Measure the protein concentration by BCA method, gradually carry out sample loading, electrophoresis, membrane transfer, membrane washing, and sealing. Add the corresponding primary antibody for incubation at room temperature for 1 hour according to instructions, overnight at 4 °C, add the secondary antibody after membrane washing, incubate in a shaking table for 2 hours, and wash the membrane with TBST for 3 times, 10 minutes each time. ECL imaging system is used for luminous development. The experiment is repeated at least 3 times, and the gray value is measured and statistically analyzed.https://www.graphpad.com/). Image J software (https://imagej.net/software/imagej/) was used for protein gray scale calculation, and P<.05 was considered as statistically significant difference.The data was analyzed by SPSS 20.0 statistical software , and all the images were drawn by GraphPad Prism 9.0 software , 11 main active ingredients of PV were retrieved through TCMSP, Swiss Target Prediction and PubChem database, and these targets were converted into gene names through UniProt database. Through searching Gene Cards and Online Mendelian Inheritance in Man databases, 3064 PTC related targets were obtained. The R package Venn Diagram was used to finally visualize 83 intersections of active ingredient targets and disease targets -sitosterol and kaempferol have a degree value of the first 4 drugs, which is significantly higher than other effective ingredients  were obtained from GO function enrichment analysis, including 1503 biological process entries, mainly including response to nutrient levels, response to xenobiotic stimulus, response to extracellular stimulus, response to oxidative stress, cellular response to chemical stress, response to reactive oxygen species, cellular response to oxidative stress, response to lipopolysaccharide, reactive oxygen species metabolic process, cellular response to reactive oxygen species etc. A total of 49 cellular composition entries mainly including external side of plasma membrane, membrane raft, membrane microdomain, vesicle lumen, ficolin-1-rich granule lumen, ficolin-1-rich granule, secretory granule lumen, cytoplasmic vesicle lumen, plasma membrane raft, caveola etc. One hundred-thirty molecular function entries mainly including serine hydrolase activity, serine-type endopeptidase activity, antioxidant activity, nuclear receptor activity, ligand-activated transcription factor activity, serine-type peptidase activity, RNA polymerase II CTD heptapeptide repeat kinase activity, protein serine/threonine/tyrosine kinase activity, virus receptor activity, exogenous protein binding etc.GO Fig. A and KEGq<0.05), 149 pathways were obtained. The first 20 pathways are core pathways, mainly including TFluid shear stress and atherosclerosis, AGE-RAGE signaling pathway in diabetic complications, Lipid and atherosclerosis, IL-17 signaling pathway, Malaria, Prostate cancer, Chemical carcinogenesis-receptor activation, PI3K-Akt signaling pathway, Rheumatoid arthritis, EGFR tyrosine kinase inhibitor resistance, Bladder cancer, TNF signaling pathway, Endocrine resistance, Kaposi sarcoma-associated herpesvirus infection, Breast cancer, Chemical carcinogenesis - reactive oxygen species, Relaxin signaling pathway, Melanoma, Non-small cell lung cancer, Calcium signaling pathway etc. which are mostly related to tumors, indicating that PV may treat PTC by acting on different signal pathways. Annotated map of the key target genes locations of PV in PTC related pathways was presented in Figure By KEGG pathway analysis . Therefore, kaempferol was selected as the most effective compound of PV in subsequent experiments. It was revealed that kaempferol has a significant time effect relationship and a dose effect relationship on the inhibition of BCPAP cells, and the inhibition rate is the highest.The active compounds quercetin, luteolin, β-sitosterol, and kaempferol from PV on anti-PTC, the protein expression levels of VEGFA, TP53, JUN, PTGS2, IL6, and IL-1B were detected respectively in the present study . Kaempferol could significantly reduce the expression of PTGS2 protein at concentrations of 20, 40, 80 µmol/L. In addition, kaempferol may significantly reduce the expression of JUN and VEGFA protein at concentrations of 40, 80 µmol/L respectively (P<.05).In order to explore the mechanism of udy Fig. . Compare,15 TCM has shown great potential in the prevention and treatment of tumors and other diseases. The separation and extraction of effective components from TCM is an important means of new drug development. It is reported that more than 80% of small molecule antitumor drugs are natural products and their derivatives. The diverse pharmacological activities of natural compounds provide an important basis for the study of the mechanism of biological functions. Previous studies have shown that PV may inhibit the proliferation of tumor cells, induce apoptosis, and regulate immunity in many kinds of tumors. However, due to the complexity of the components of TCM, its main effective components and related mechanisms are still unclear. Network pharmacology is to use systems biology, high-throughput screening and other technologies to systematically analyze the interaction network of “TCM components and disease targets,” and to reveal the intervention and impact of TCM on body diseases as a whole, which is consistent with the theory of TCM treatment.PTC is the most common endocrine system tumor, which belongs to the category of “goiter and tumor” disease in TCM which accounts for about 80% to 90% of DTC.PV in the treatment of PTC were preliminarily explored by network pharmacology. The results showed that there were 11 main active ingredients of PV in the treatment of PTC, including β-sitosterol, kaempferol, spinasterol, stigmasterol, delphinidin, luteolin, vulgaxanthin-I, poriferasterol monoglucoside_qt, stigmast-7-enol, morin, quercetin. According to the analysis of the network of the “active ingredient-target-disease” with Cyto scape 3.7.2, the top 4 active compounds of PV are quercetin, luteolin, β-sitosterol, kaempferol. Quercetin is a unique bioactive flavone and antioxidant, which plays a full role in reducing different human cancers that can directly promote apoptosis of tumor cells, so it can inhibit the progression of many human cancers. It has been shown that quercetin can inhibit thyroid cancer cells in vitro. In addition, it was also reported that quercetin is effective in the treatment of both medullary and papillary of human thyroid cancer. β-sitosterol is the most abundant and widely distributed in vegetable foods rich in oil. It was found that prominent in vitro antiproliferative and pro-apoptotic effects of β-sitosterol in MDA-MB231 cells. Previous study revealed that the silver nanoparticles of β-sitosterol can effectively induce the toxicity and early apoptosis of human colon cancer cells by enhancing the expression of p53 protein. Luteolin may show effective cytotoxicity to thyroid cancer cells in vitro and in vivo by blocking BANCR/TSHR signals which may become a potential important anticancer agent for thyroid cancer progression. Meanwhile, luteolin exhibits an antitumor effect in the HCC cell line SMMC-7721 by suppress cell viability, induce G0/G1-phase arrest, and increase cellular apoptosis. Kaempferol may inhibited cellular growth in a dose dependent manner in F9 and thyroid cancer cells. It was reported that kaempferol inhibits the invasion and migration of renal cancer cells through the downregulation of AKT and FAK pathways. Taken together, the 4 core components of PV showed different levels of anticancer activity.In the present study, the main active components, targets and functional pathways of  It was also revealed that the molecular state of VEGFA may play an important role in the progression of PTC. VEGFA mRNA is overexpressed in thyroid carcinoma, especially in thyroid carcinoma with lymph node metastasis. Previous research results found that the role of TP53-rs1042522 polymorphism in development of thyroid carcinoma which related to decreased risk of PTC, smaller tumor size, and lower incidence of vascular invasion. In addition, it was indicated that TP53 may lead to the risk of PTC in individuals exposed to radiation in late childhood, adolescence or adulthood in previous study. It has been demonstrated that the gene JUN was closely connected with PTC genesis which may benefit the cure of PTC patients. It was found that the PTGS2 expression was significantly higher in patients with lymph node metastasis or extrathyroidal extension. IL6 plays an important role in the progression of thyroid cancer that targeting IL6 signal transduction may help the clinical treatment of patients with thyroid cancer with more invasive tumor characteristics. The IL6/JAK2/STAT3 pathway was considered to be associated with PTC malignant behaviors. IL1B polymorphism may be associated with PTC risk and a predictor of lymph node metastasis of PTC patients in Korean population. The results of molecular docking showed that the binding strength of key components corresponding to key targets was good. It further verified that PV may play a role in the treatment of PTC through these core pharmacodynamic components acting on the corresponding targets.These active ingredients act on 83 target proteins of PTC. PPI network shows that the genes with the top 6 connectivity are VEGFA, TP53, JUN, PTGS2, IL6, and IL1B, respectively. It shows that these targets are related to the proliferation and differentiation of tumor cells and tumor progression in the present study. Among them, VEGFA is a key mediator of cancer-associated neo-angiogenesis and progression which have been explored extensively for cancer therapy. It was found that the importance of increased VEGFA protein in tumors and may explain the higher protein quantification observed in the PTC tumor samples in comparison to the goiter.PV in treating PTC mainly focused on cell proliferation, differentiation and anti-inflammatory immunity. The occurrence, development, malignant transformation, invasion, and metastasis of tumor are accompanied by inflammatory reaction. Inflammatory cells and molecules play a key role in the formation and maintenance of tumor immunity. It had been demonstrated that the level of IL6 in patients with thyroid cancer is elevated, and there is a close relationship between thyroid cancer and inflammation. The level of serum interleukin fully reflects this relationship and the potential mechanism of action. IL-17 is an proinflammatory cytokine cause continuous inflammatory reaction that increase the expression of nuclear factor kappa B, thus activating the expression of effector genes IL6 and vascular endothelial growth factor which promoting the occurrence and development of tumors. PI3K-AKT signal pathway is involved in cell proliferation, apoptosis, cycle regulation and other pathophysiological processes. P53 is one of the main apoptotic signal pathways, which can promote apoptosis by interacting with BCL-2 family proteins in the cytoplasm.PV may treat PTC through multiple pathways and multiple targets. Besides above genes and pathways, it was also reported that BRAF gene mutation and TERT promoter mutation were closely associated with PTC recurrence and prognosis which should focus on the key points research in the future.KEGG and GO analysis showed that the potential mechanism of PV, of which 6 were the core targets of PV in the treatment of PTC. Quercetin, luteolin, β-sitosterol, kaempferol may be the core components of PV in the treatment of PTC. VEGFA, TP53, JUN, PTGS2, IL6, and IL-1B were considered to be the targets for the treatment of PTC. IL-17 signaling pathway and PI3K-Akt signaling pathway may affect the recurrence and metastasis of PTC. In conclusion, this study used network pharmacology and molecular docking technology to clarify that PV may play a role in the treatment of PTC through multiple components, multiple targets and multiple pathways. In addition, further vivo experiment was carried to verify it. Kaempferol is consider to be the most useful compound which may reduce the protein expression levels of IL6, VEGFA, JUN, TP53, 1L-1B, and PTGS2, respectively. This study laid a foundation for the in-depth study of the material basis and mechanism of action of PV, and provided a scientific basis for the clinical application of PV.Eleven components and 83 corresponding targets were obtained in the component target network of We want to thank Yanling Zhou of Chongqing Three Gorges Medical College for her contribution in revision of this manuscript.Conceptualization: Yuanshe Huang, Jingxin Mao.Data curation: Xiling Zhu, Jingxin Mao.Formal analysis: Xiling Zhu, Xiaodong Wang.Funding acquisition: Jingxin Mao and Yanlin Zou.Methodology: Xiling Zhu, Yan Li, Xiaodong Wang, Yuanshe Huang, Jingxin Mao.Project administration: Jingxin Mao.Software: Xiling Zhu, Xiaodong Wang, Jingxin Mao.Supervision: Yan Li.Validation: Jingxin MaoVisualization: Jingxin Mao.Writing – original draft: Xiling Zhu, Jingxin Mao.Writing – review & editing: Yuanshe Huang, Jingxin Mao, Yanlin Zou.


To elucidate the mechanism of Spatholobi Caulis (SC) in treating osteoporosis (OP) integrated zebrafish model and bioinformatics.  Skeleton staining coupled with image quantification was performed to evaluate the effects of SC on skeleton mineralization area (SSA) and total optical density (TOD). Zebrafish locomotor activity was monitored using the EthoVision XT. Bioactive compounds of SC and their corresponding protein targets were acquired from Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. Potential therapeutic targets for OP were summarized through retrieving 5 databases, and then, the overlapping genes between SC and OP were acquired. The core genes were selected by CytoHubba. Subsequently, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) functional analysis of the intersection target genes were carried out by R software. Finally, the molecular docking simulation was manipulated between the ingredients and the hub genes. p < 0.001). 33 components of SC were associated with 72 OP-related genes including 10 core genes . Advanced Glycation End Product (AGE) Receptor for AGE (RAGE) signaling pathway was screened out as the principal pathway of SC in anti-OP. The bioactive components  have excellent affinity to core genes .  Compared with the model group, SC significantly increased the SSA and TOD at 10 mg/mL and improved the locomotor activity in a dose-dependent manner ( SC had the hierarchical network characteristics of “multicomponents/multitargets/multifunctions/multipathways” in reversing OP, but AGE-RAGE signaling pathway may be the main regulatory mechanism. Osteoporosis (OP) is a common systemic bone disease with a significant impact on human health and characterized by low bone quality, low bone density, and bone microstructure destruction, which easily leads to decreased bone strength and increased fracture risk –3. OP haSpatholobus suberectus Dunn of the family Leguminosae [, and promoted angiogenesis [Spatholobi Caulis (SC), known as Jixueteng in Chinese Pharmacopoeia (2020 version), is the vine stem of uminosae . SC is auminosae –21. In cuminosae , 23, dysuminosae , amenorruminosae , rheumatuminosae , blood duminosae . Increasuminosae , anti-inuminosae , anticanuminosae , and proogenesis . In addiogenesis . Also, rogenesis , 34. HowAs a new interdisciplinary developed in recent years, network pharmacology provides a “multiway,” “multitarget” method for drug analysis and is similar with the thoughts of traditional Chinese medicine (TCM) compound prescription, which concurs with the characteristics of the overall compatibility of TCM and comprehensive and multipathway treatment of diseases . Recentl2, 0.33 mM MgSO4, 5 mM NaCl, and 0.17 mM KCl). Zebrafish embryos were cultured in Intelligent light incubator with a 14/10 h light/dark cycle [Zebrafish larvae were purchased from Nanjing Yishu Lihua Biotechnology Co., Ltd and cultured in blank E3 medium , Etidronate Disodium group , SC-H (10 mg/mL SC + 25 μM PNSL), SC-M (1 mg/mL SC + 25 μM PNSL), and SC-L (0.1 mg/mL SC + 25 μM PNSL).Newly hatched zebrafish larvae at the age of 3 days after fertilization (DAF) were placed into 6-well plates (15 larvae in each well) , 41. TheAfter 4-day drug deliveries, zebrafish locomotor activity was monitored by EthoVision behavior system , 43. The2O2 and 0.5% KOH was added [At the 10 DAF, all zebrafish larvae were collected and killed under anesthesia by 3-Aminobenzoic acid ethyl ester methanesulfonate  . After ras added . 1.5 houas added . The staas added  were anaTraditional Chinese Medicine Systems Pharmacology database (TCMSP) was utilized to search the bioactive components of SC, with the screening conditions of “oral bioavailability (OB) ≥20% and drug like (DL) ≥0.1.” Meanwhile, the corresponding target genes of the above components were obtained , 57.https://www.genecards.org/), Online Mendelian Inheritance in Man (OMIM) [https://omim.org/, updated November 25, 2020), PharmGkb [https://www.pharmgkb.org/), Therapeutic Target Database (TTD) [https://db.idrblab.net/ttd/), and DrugBank [https://www.drugbank.org/) using the keyword “osteoporosis.” The OP-related target genes were gathered, and Venn diagram was constructed.OP-related targets were collected through retrieving GeneCards  (https:/n (OMIM)  (https:/PharmGkb  (https:/se (TTD)  , cellular component (CC), and molecular function (MF) were screened out to construct the histogram and bubble diagram. Then, the target proteins were analyzed using the KEGG enrichment analysis, and the top 30 signaling pathways were chosen to draw the histogram and bubble diagram.Cytoscape software was adopted to draw a ternary network including bioactive ingredients-target genes-signaling pathways. The above bioactive components and corresponding genes were imported into the software, and the ternary network “drug-active components-potential therapeutic targets of disease-relevant signaling pathways” was drawn , 68.https://www.ncbi.nlm.nih.gov/) platform and converted into the 3D structure by ChemBio3D software, and the energy optimization of MM2 was carried out to complete the preparation of small molecule ligands. The 3D structure of the candidate target proteins was downloaded from PDB (https://www.rcsb.org/) database, and then, the protein receptors were prepared after the water molecules, and ligands were removed by PyMOL2.4.0 software. AutoDockTools software was used to read the receptor files, which were converted to PDBQT format after hydrotreating ion modification. The ligand files were also converted to PDBQT format for saving and then converted into the 2D structure to draw the active pockets. Finally, AutoDock vina software will be used for molecular docking, and the lowest free energy model is selected for visual analysis.”The plug-in CytoHubba of Cytoscape software was used to screen top 10 hub genes. The core genes were selected to find the related drug components in the compound regulatory network as small molecular ligands. Molecular docking simulation was performed as previously described. The specific process is as follows: “the 2D structure information of drug chemical components was downloaded from PubChem . TF for SC-H, SC-M, and SC-L was 371.43%, 254.54%, and 159.62%, respectively. Also, the hot plot revealed zebrafish activity degree  entries, 106 molecular function (MF) entries, and 51 cellular component (CC) entries. As shown in Moreover, a total of 139 signaling pathways were yielded through KEGG enrichment analysis, including Bladder cancer, Lipid and atherosclerosis, Kaposi sarcoma-associated herpesvirus infection, AGE-RAGE signaling pathway, IL-17 signaling pathway, Hepatitis C, Human cytomegalovirus infection, Estrogen signaling pathway, Breast cancer, and TNF signaling pathway. As shown in 10 core genes  were identified using 12 algorithms in CytoHubba. After KEGG enrichment analysis, we searched for OP in the KEGG pathway database and found that there are mainly two pathways directly related to OP and related diseases, including AGE-RAGE signaling pathway and Estrogen signaling pathway. Subsequently, we found that five of the top 10 hub genes  were enriched in AGE-RAGE signaling pathway. Aloe-emodin, emodin, formononetin, licochalcone A, luteolin, and lopac-I-3766 were selected as the top active components for molecular docking with MAPK1, VEGFA, MMP9, AKT1, and IL6 in turn. “The binding energy between drug component ligands and target receptors is an important indicator to evaluate the binding capacity. It is generally considered that the docking affinity is stronger when the binding energy is less than—5.0 kcal/mol, and the docking activity is extremely strong when the binding energy is less than—7.0 kcal/mol.” From the docking results Tables , it was OP is a metabolic disease caused by various factors, such as age, endocrine, viral infection, and a variety of cytokines. Given that the multitarget and multipathway pharmacological properties of TCM make it more suitable for the treatment of OP, SC is a widely used traditional medicine for promoting blood circulation to remove blood stasis and nourishing blood. Modern pharmacological studies revealed that SC exerted anti-OP through inhibition of osteoclastogenesis and stimulation of chondrogenesis. However, the underlying mechanism remains unclear. The aim is to clarify the potential mechanisms of SC for OP treatment integrated zebrafish model and network pharmacology.p < 0.05; Figures μmol/L caused an apparent decrease in the SSA and TOD with values of 51423.33 and 19405.03, respectively, which corresponded to the ventral view of Alizarin Red stained zebrafish skull, as shown in p < 0.001 − 0.01). TF for SC-H, SC-M, and SC-L was 371.43%, 254.54%, and 159.62%  were identified using plug-in CytoHubba in Cytoscape. Subsequently, we found that five of the top 10 hub genes  were enriched in AGE-RAGE signaling pathway. MAPK1, generally known as ERK2, is a member of mitogen-activated protein kinase family and acts as an essential regulator of cell proliferation, differentiation, inflammation, and bone metabolism. It has been demonstrated the activation of MAPK1 could promote osteoblastogenesis and bone mineralization in zebrafish larvae. VEGFA is a signal factor promoting neovascularization and increase vascular permeability. A recent research reported that VEGFA was a latent marker of endothelial dysfunction in postmenopausal osteoporosis. Moreover, through directly targeting VEGFA, MIR-16-5P mitigated the symptom of postmenopausal women with osteoporosis. MMP9 is a member of matrix metalloproteinases family, responsible for extracellular matrix degradation and cleavage of its structural components. A previous study illustrated that MMP9 exerted a crucial role in pathogenesis of osteoporosis, and the inhibitory effect on bone resorption was emerged by inhibiting the expression of MMP9. AKT1, also called Protein Kinase B, is a crucial signal transducer of PI3K/AKT signaling pathway. The phosphorylation of AKT1 modulates the expression of multiple downstream effectors including mTOR‐C1 and FOXO3 proteins and then mitigates OP induced by iron overload. Based on the above analysis results, it is also speculated that SC against OP may play a role through the above process.GO and KEGG enrichment analysis results showed that the therapeutic targets of SC for diseases mainly enriched in Bladder cancer, Lipid and atherosclerosis, AGE-RAGE signaling pathway, Kaposi sarcoma-associated herpesvirus infection, IL-17 signaling pathway, Hepatitis C, Human cytomegalovirus infection, Estrogen signaling pathway, TNF signaling pathway, and breast cancer. Studies have shown that all of these play a crucial role in the progression of OP. We searched for OP in the KEGG pathway database and found that there are mainly two pathways directly related to OP and related diseases, including AGE-RAGE signaling pathway and Estrogen signaling pathway. Subsequently, we found that five of the top 10 hub genes  were enriched in AGE-RAGE signaling pathway. The AGE-RAGE signaling pathway plays a crucial role in bone remodeling process. In general, AGEs not only induce osteoclastogenesis by upregulation of RANKL mRNA, but they also affect osteoblasts by suppressing cell growth, promoting apoptosis, and downregulating differentiation, which impairs mineralization. It was reported that AGEs upregulated the expression of RAGE in human MSCs and then AGEs interacted with RAGE and increased the expression of TGF-b mRNA, which suppressed bone mineralization and destroyed bone remodeling . In thisp < 0.001). 33 components of SC were associated with 72 OP-related genes including 10 core genes. AGE-RAGE signaling pathway was screened out as the principal pathway of SC in anti-OP. The bioactive components  have excellent affinity to core genes . Conclusion. SC had the hierarchical network characteristics of “multicomponents/multitargets/multifunctions/multipathways” in reversing OP, but AGE-RAGE signaling pathway may be the main regulatory mechanism. We have demonstrated the anti-OP effect of SC and revealed its underlying mechanism by adopting zebrafish model and network pharmacology. SC mainly regulated AGE-RAGE signaling pathway to exert anti-OP therapeutic effect.Compared with model group, SC significantly increased the SSA and TOD at 10 mg/mL and improved the locomotor activity in a dose-dependent manner (


Taxanes are natural compounds for the treatment of lung cancer, but the molecular mechanism behind the effects is unclear. In the present study, through network pharmacology and molecular docking, the mechanism of the target and pathway of taxanes in the treatment of lung cancer was studied. The taxanes targets were determined by PubChem database, and an effective compounds-targets network was constructed. The GeneCards database was used to determine the disease targets of lung cancer, and the intersection of compound targets and disease targets was obtained. The Protein–Protein Interaction (PPI) network of the intersection targets was analyzed, and the PPI network was constructed by Cytoscape 3.6.0 software. The hub targets were screened according to the degree value, and the binding activity between taxanes and hub targets was verified by molecular docking. The results showed that eight taxane-active compounds and 444 corresponding targets were screened out, and 131 intersection targets were obtained after mapping with lung cancer disease targets. The hub targets obtained by PPI analysis were TP53, EGFR, and AKT1. Gene Ontology (GO) biological function enrichment analysis obtained 1795 biological process (BP) terms, 101 cellular component (CC) terms, and 164 molecular function (MF) terms. There were 179 signaling pathways obtained by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Twenty signaling pathways were screened out, mainly pathways in cancer, proteoglycans in cancer pathway, microRNAs in cancer pathway, and so on. Molecular docking shows that the binding energies of eight taxanes with TP53, EGFR, and AKT1 targets were less than −8.8 kcal/mol, taxanes acts on TP53, EGFR, and AKT1 targets through pathways in cancer, proteoglycans in cancer pathway and microRNAs in cancer pathway, and plays a role in treating lung cancer in biological functions such as protein binding, enzyme binding, and identical protein binding. Lung cancer, as one of the most commonly diagnosed malignant tumors and the leading causes of cancer death in the world, has a high incidence ,2,3. BecIn China, due to the influence of regional differences, lung cancer is the malignant tumor with the highest mortality rate, although its impact on different regions is different ,7. At thTaxus plants. Taxanes are a kind of diterpenoids with pentamethyl pentadecene skeleton, taxanes mainly include paclitaxel, docetaxel, and derivatives with taxanes skeleton structure, which have high-efficiency and broad-spectrum anti-tumor activity, and their development has made great contributions to drug discovery and clinical application [Lung cancer can be divided into small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) according to its pathological type, cell morphology, and histological characteristics. Taxanes have a very significant therapeutic effect on lung cancer ,11. Taxalication . Some talication ,14. Pacllication . Wang etlication , and Eiflication . In addilication . Liu et lication . Fanucchlication . As the lication . When calication .As one of the most widely used and researched natural anticancer compounds, taxanes play an important role in clinic, practice, and drug development ,24. PrevLung cancer has a high mortality rate worldwide, which seriously endangers human life, health, and safety. Taxanes are one of the most common compounds for treating lung cancer, so far there is no systematic theory that can fully explain the anti-lung cancer mechanism of taxanes. Network pharmacology is a new subject based on the theory of systems biology ,31. UsinIn the present study, taxanes and lung cancer were taken as the research objects, and the effective compounds, hub targets, core pathways, and core functions of taxanes in the treatment of lung cancer were screened and analyzed by using network pharmacology technology. Through the Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG), the pathway enrichment analysis of intersection targets was carried out, and the hub targets were verified by molecular docking technology, aiming to preliminarily clarify the molecular mechanism of taxanes in the treatment of lung cancer from the perspective of network pharmacology.https://www.cnki.net/, accessed on 6 May 2022), and the collected taxanes mainly contained eight compounds (10-deacetylbaccatin III (10-DAB III), baccatin III, 7-xylosyl-10-deacetyltaxol (7-Xyl-10-DAT), 10-deacetyltaxol (10-DAT), docetaxel, cephalomannine (CEPH), paclitaxel, and 7-epitaxol). Eight typical taxane targets were obtained by using PubChem database , and the taxane targets were matched with gene names by using Uniprot database of protein sequence and functional information resources , and repeated values were deleted to obtain taxane targets. Upload the data to Cytoscape 3.6.0 software to draw the effective compounds-targets network diagram.The literatures related to taxanes were searched through China National Knowledge Infrastructure , searched with “lung cancer” as the key word, and screened with “relevance score” ≥ 25 to obtain disease targets.We used GeneCards disease database  of the intersection targets of eight taxanes and lung cancer, and the intersection targets of eight taxanes and lung cancer was obtained. And the intersection targets were imported into the STRING database  for Protein–Protein Interaction (PPI) network analysis, and the species was defined as “Homo Sapiens”, and the “minimum required interaction score” was set to 0.4 to construct a PPI network. The PPI network map was downloaded in “TSV” format and uploaded to the Cytoscape 3.6.0 software to make a PPI network visualization.We calculated and drew a custom Venn diagram on the website of Bioinformatics Evolutionary Genomics , and the selected species was “Homo sapiens”. GO function analysis mainly includes biological process (BP), cellular component (CC), and molecular function (MF) terms. The threshold of statistical significance was set to p < 0.001, and the data results were visualized by using the free bioinformatics database . The drawing of the core pathway picture depends on KEGG Mapper–Color website .The GO function and KEGG pathway of the intersection targets were analyzed by Metascape database , and it was saved as “SDF” format. Based on PPI network analysis results , the crystal structures of TP53 , EGFR , and AKT1  were chosen as the receptor proteins from the RCSB protein data bank , and then the “SDF” format of eight taxanes is converted into “PDB” format by using OpenBabel 2.4.1 software. Autodock 4.2 software was introduced, and the small molecule and target protein were pretreated by OpenBabel 2.4.1 software, respectively, and the treated compounds were molecularly docked with the target protein by PyMOL 2.4 software. The binding energy of the compounds and targets were then determined. The binding sites were visualized on Protein–Ligand Interaction Profiler (PLIP) website . And determination of RMSD values of the compounds and targets by “align” function of PyMOL 2.4 software.In order to further analyze the research results of network pharmacology at the level of molecular relationship, with the help of molecular docking technology , the tophttps://pubchem.ncbi.nlm.nih.gov/, accessed on 14 May 2022), and the targets of effective compounds were matched with human gene names by Uniprot database . After deleting duplicate values, a total of 444 taxanes-related targets were obtained, including 444 targets for paclitaxel, 40 targets for 10-deacetylbaccatin III (10-DAB III), 40 targets for 10-deacetyltaxol (10-DAT), 48 targets for baccatin III, 48 targets for cephalomannine (CEPH), 147 targets for docetaxel, 10 targets for 7-epitaxol, and 5 targets for 7-xylosyl-10-deacetyltaxol (7-Xyl-10-DAT). Visualize with the “Analyza Network” tool in cytoscape 3.6.0 software , we searched with “lung cancer” as the key word and screened with “Relevance score” ≥ 25” to obtain disease targets, and a total of 738 lung cancer-related targets were screened.Screening of lung cancer disease targets Using GeneCards disease database , blue represents eight taxanes with 444 targets, red represents lung cancer with 738 targets, and the middle overlapping part was the intersection target of eight taxanes and lung cancer with 131 targets.As shown in http://metascape.org/gp/index.html#/main/step1, accessed on 15 February 2023), and 1795 biological process (BP) terms, 101 cellular component (CC) terms, and 164 molecular function (MF) terms were obtained. p < 0.001 was set as the screening standard, and the top 10 biological process terms with the highest correlation were selected, respectively. As shown in GO biological functions of 131 intersection target of taxanes and lung cancer genes were analyzed by Metascape database , and KEGG pathway enrichment analysis was carried out. There were 179 signaling pathways obtained by KEGG pathway enrichment analysis and the top 20 signaling pathways with the highest correlation were screened out (p < 0.001). As shown in A total of 131 intersection targets of taxanes and lung cancer genes were uploaded to Metascape database , EGFR (3POZ), and AKT1 (3OS5), respectively. Twenty-four groups of ligand-receptor docking results were obtained . TargetsAccording to the binding energies, the above eight compounds can be well-combined with the three targets. 10-DAB III has the strongest binding with AKT1 target, followed by TP53 target and the weakest binding with EGFR target. Baccatin III has the strongest binding with AKT1 target, followed by TP53 target and the weakest binding with EGFR target. 7-Xyl-10-DAT has the strongest binding with TP53 and AKT1 targets, and the weakest binding with EGFR targets. 10-DAT has the strongest binding with AKT1 target, followed by TP53 target and the weakest binding with EGFR target. Docetaxel has the strongest binding with AKT1 target, followed by EGFR target and the weakest binding with TP53 target. CEPH has the strongest binding with AKT1 target, followed by TP53 target and the weakest binding with EGFR target. Paclitaxel has the strongest binding with TP53 target, followed by AKT1 target and the weakest binding with EGFR target. 7-epitaxol has the strongest binding with TP53 target, followed by AKT1 target and the weakest binding with EGFR target.As shown in As shown in As shown in Lung cancer is the most frequent cancer type and the leading cause of tumor-associated deaths worldwide. The Tumor protein P53 (TP53) gene is a major player in cancer formation, and it is considered the most important tumor suppressor gene. The p53 protein acts as a transcription factor, and it is involved in DNA repair, senescence, cell-cycle control, autophagy, and apoptosis . TP53 geEpidermal growth factor receptor (EGFR) is a tyrosine kinase receptor for epithelial growth factor (EGF) cell proliferation and signal transduction, belonging to the ErbB receptor family, which is related to tumor cell proliferation, angiogenesis, tumor invasion, metastasis, and apoptosis inhibition . EGFR isRAC-alpha serine/threonine-protein kinase (AKT1) gene encodes serine/threonine protein kinase, which can be activated by extracellular signal through phosphatidylinositol 3 kinase (PI3K)-dependent mechanism, and participates in cellular processes, including apoptosis and glucose metabolism . AKT1 plIn this study, the targets related to taxanes and lung cancer were collected and screened by network pharmacology, and the intersection target of taxanes and lung cancer were analyzed by PPI network analysis, GO biological function enrichment analysis, and KEGG pathway enrichment analysis. To predict the core compounds, targets, pathways, and functions of taxanes in the treatment of lung cancer, eight taxanes-active compounds were screened, corresponding to 444 targets, 738 targets of lung cancer diseases, and 131 intersection target between taxanes and lung cancer. And the top 20 KEGG pathways were obtained. Finally, the top three hub targets with degree value were verified by molecular docking. The results of molecular docking showed that the binding energies of eight taxanes with TP53, EGFR, and AKT1 targets were less than −8.8 kcal/mol. The classical root mean square deviation (RMSD) value was used to assess the ability of each docking tool to predict poses similar to that of the crystallographic structure. RMSD equal to or lower than 2 Å is considered good, 2 Å < RMSD < 3 Å is acceptable and RMSD > 3 Å is bad. However, RMSD < 2 Å cut-off value is widely regarded as the most effective threshold value for validating correctly posed molecules . In thisIn the present study, the key active compounds, targets, and pathways of eight taxanes in the treatment of lung cancer were preliminarily predicted by network pharmacology and molecular docking. Eight taxanes mainly act on TP53, EGFR, and AKT1 targets through pathways in cancer, proteoglycans in cancer pathway, and microRNAs in cancer pathway, and plays a role in treating lung cancer in biological functions such as protein binding, enzyme binding, and identical protein binding. Although this study embodies the characteristics of multi-component, multi-target, and multi-pathway, and can provide new ideas for taxanes to treat lung cancer, there are some limitations in network pharmacology. The results need to be further confirmed by related experiments. This paper provides a basic theoretical basis for further study on the key mechanism of taxanes in the treatment of lung cancer in the future.


Poria cocos Wolf, a traditional Chinese herb, has potential anticancer properties, but the action and mechanism against ovarian cancer remain undetailed. Pachyman (Poria cocos polysaccharides) refers to the pharmacologically bioactive ingredients rich in Poria cocos. This study aimed to identify the potent actions and the network mechanisms of pachyman against ovarian cancer through preclinical analysis. Online‐accessible database or platform was employed to predict candidate genes and core targets associated with ferroptosis in pachyman against ovarian cancer. Enrichment analyses were used to characterize the functional action and signaling mechanism in pachyman to treat ovarian cancer. Molecular docking imitation was conducted for verification of core target proteins. Network analysis uncovered that there were 30 mutual and 13 core genes targeting ferroptosis in pachyman and/against ovarian cancer, and additional enrichment analysis characterized that these core genes may act synergistically through multiple biological processes and molecular pathways associated with ferroptosis, including anti‐inflammatory action, immunoregulation, and microenvironment modulation. The strongest affinities in core target proteins between pachyman and sarcoma (SRC), signal transducer, and activator of transcription 3 (STAT3) were further validated using molecular docking method. In conclusion, pachyman may induce antiovarian cancer potentials via regulating ferroptosis‐associated biological functions and pharmacological mechanisms based on current bioinformatics findings. We reason that pachyman, the beneficial nutraceuticals, may be used clinically for future application in ovarian cancer treatment.Ferroptosis has gained extreme purpose in targeting cancer treatment.  Our bioinformatics findings reveal the biological actions, key genes, and signaling pathways targeting ferroptosis in Pachyman treating ovarian cancer potentially. This study will better contribute to complete understanding of Pachyman‐mediated network mechanisms in treating ovarian cancer. Notably, identified interactions of drug and core gene may lay a theoretical foundation for the research and development of ovarian cancer drugs targeting ferroptosis. Secondly, FerrDb (http://www.zhounan.org/ferrdb) and GeneCards (http://www.genecards.org) databases were applied for ferroptosis‐associated target genes. Thirdly, GeneCards and Online Mendelian Inheritance in Man  were employed to select ovarian cancer‐related target genes. All data were identified on October 2022 after removing duplication. And then, the data were used for additional Venn‐map analysis to determine the correlative target genes in pachyman against ovarian cancer targeting ferroptosis.To begin with, Swiss TargetPrediction (2.2https://cytoscape.org/) and the data was processed from String database (https://string‐db.org/). The confidence score cutoff was set at 0.7. The core target genes were determined through the standard parameters, in which the upper limit of the filtering range was the maximum degree in parametrical data, and the lower limit was the median degree of freedom, as in our previous report   for identifying the core proteins in pachyman against ovarian cancer. The chemical structure of pachyman was downloaded from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/). Other three‐dimensional structures of SRC and STAT3 core proteins were obtained from Protein Data Bank  with PDB‐ID: 4F5B and PDB‐ID: 6SM8. The Autodock Tool was applied to prepare the structures before ligand docking. Molecular docking data were determined by referencing root‐mean‐square deviation (RMSD). Other details in screening were shown in previous report , Harvey rat sarcoma viral oncogene homolog (HRAS), tumor necrosis factor (TNF), vascular endothelial growth factor A (VEGFA), toll‐like receptor 4 (TLR4), mitogen‐activated protein kinase 14 (MAPK14), rapamycin (MTOR), caspase‐8 (CASP8), Mucin 1 (MUC1), galectin 3 (LGALS3), and platelet‐derived growth factor receptor beta (PDGFRB) Figure .3.3Escherichia coli infection, chemical carcinogenesis‐receptor activation, Chagas disease, toll‐like receptor signaling pathway, hypoxia‐inducible factor‐1 (HIF‐1) signaling pathway, and shigellosis , cellular components (CCs), and molecular functions (MFs). The top 20 BPs of core target genes are displayed in Figure s Figure . Briefly3.4As revealed in the data of three‐dimensional crystals, pachyman might effectively dock with SRC (4F5B) and STAT3 (6SM8), and the free docking energy and RMSD calculated for each binding model were −5.5 kJ/mol (RMSD: 1.767 Å) and −8.1 kJ/mol (RMSD: 2.181 Å), respectively. Pachyman binding amino acid residues (4F5B) via forming hydrogen bonds detailed in LEU‐206 (3.1 Å), HIS‐204 (2.9 Å), ARG‐178 (3.3 Å), ARG‐158 (3.2 Å), SER‐180 (3.2 Å), GLU‐181 (3.1 Å), and THR‐182 (2.8 Å) Figure . In addi4Poria cocos Wolf has been found with potential efficacy for adjuvant therapy in chronic disorders, such as cancers ; formal analysis ; investigation ; methodology ; validation . Yanyan Deng: Data curation ; formal analysis ; methodology ; resources ; software . Xuqiang Lin: Data curation ; formal analysis ; resources ; software . Xiaowei Wan: Methodology ; resources ; software . Jiaqi Liu: Investigation ; project administration ; resources ; supervision ; visualization ; writing – original draft ; writing – review and editing .This research is partially supported by the second affiliated hospital of Guilin Medical University and health key discipline construction project.The authors confirm that there are no known conflicts.


As one of the most frequently diagnosed mental disorders, depression is expected to become the most common disease worldwide by 2030. Previous studies have shown that Chaihu Anxin Capsule has powerful antidepressant effects. However, its mechanisms are not fully understood. The aim of our research is to reveal the mechanisms of Chaihu Anxin Capsule in treating depression.Information about the ingredients of the herb was gathered using the TCMSP. Genes associated with antidepressants were gathered from the GeneCards database. An “herbal-ingredient-target” network was constructed and analyzed using Cytoscape software. The PPI network of the antidepressant targets of Chaihu Anxin Capsule was constructed using the STRING database. KEGG pathway and GO enrichment were used to analyze the antidepressant targets. Molecular docking technology was used to confirm the capacity of the primary active ingredients of Chaihu Anxin Capsule to bind to central targets using AutoDock Vina and PyMOL software.Network analysis showed that five targets might be therapeutic targets of Chaihu Anxin Capsule in depression, namely, JUN, IL6, AKT1, TP53, and STAT3. The gene enrichment analysis implied that Chaihu Anxin Capsule benefits patients with depression by modulating pathways related to lipids and atherosclerosis and the AGE-RAGE signaling pathway in diabetic complications. Molecular docking analyses revealed that JUN, IL6, AKT1, TP53, and STAT3 had good affinities for quercetin, beta-sitosterol and kaempferol.According to the bioinformatics data, the antidepressant effects of Chaihu Anxin Capsule may be primarily linked to cholesterol and atherosclerosis as well as the AGE-RAGE signaling pathway in diabetic complications. These results emphasize that the expected therapeutic targets may be possible indicators for antidepressant activity. The freTraditional Chinese medicine (TCM) has a clinical application history of thousands of years, playing a role through multiple links, targets, and steps. TCM is widely accepted because it comes from nature and has mild effects and few side effects. Therefore, studying the efficiency and mechanism of TCM in preventing and curing depression has attracted increasing attention from experts worldwide . For exaBupleuri radix, Paeoniae Radix Alba, Puerariae Radix and other medicinal materials and is used to treat depression syndrome with good clinical effects. Wang G et al. identified the antidepressant effect of Puerariae Radix with the help of network pharmacology   is the rate at which a medicine taken orally and absorbed in the gastrointestinal system enters the bloodstream through the liver. Drug-likeness (DL) is the degree to which herbal components resemble recognized drugs structurally. With the help of the TraditionalChineseMedicineSystemsPharmacology Database and Analysis Platform  , the cheis study . Moreoveis study , 14.2.2https://www.uniprot.org/), and the targets underwent a unified conversion to abbreviated gene names (The target proteins of the Chaihu Anxin capsule were identified using the UniProt database (ne names . The Chane names .2.3https://www.genecards.org/), OMIM (https://omim.org/), DrugBank (https://www.drugbank.ca/) and Therapeutic Target Database (https://db.idrblab.net/ttd/) databases in this study   . Apart f2.7https://metascape.org/gp/index.html#/main/step1)  and a functional enrichment and labelling tool based on Gene Ontology (GO) were both used to accomplish this. The Metascape database (n/step1)  was used2.8https://www.rcsb.org/) (https://pubchem.ncbi.nlm.nih.gov) was used to obtain the structures of the ligand molecules  library (sb.org/) . The Pubolecules . The recolecules , 26. Act33.1Paeoniae Radix Alba, 19 ingredients from Radix Bupleuri and 6 ingredients from Radix Puerariae. These results are shown in The TCMSP was used to obtain information about the 260 active components in Chaihu Anxin capsule and their targets. OB≥30% and DL≥0.18 served as the criteria. There are 14 ingredients from 3.2The obtained ingredients in Chaihu Anxin Capsule and their potential targets were imported into Cytoscape software to construct the “active ingredient-target” network. There were 497 nodes and 4317 edges in the network. These results are shown in 3.3Using the term “antidepressant,” genes associated with depression were found from the GeneCards, Online Mendelian Inheritance in Man (OMIM), DrugBank and Therapeutic Target Database databases. Based on the junction results from the TCMSP and disease gene databases, gene intersections were created, and 153 intersection targets were acquired. These results are shown in 3.4The intersection targets and their active ingredients in Chaihu Anxin Capsule were imported into Cytoscape 3.9.1 to structure the “herbal-active ingredients-antidepressant targets” network. There were 351 nodes and 2803 edges in the network. These results are shown in 3.5The STRING database was used to investigate the 153 intersected genes and construct a PPI network. These results are shown in 3.6The 20 most enriched signaling pathways of Chaihu Anxin capsule were enriched and screened using KEGG pathways (P<0.05), including lipid and atherosclerosis and the AGE-RAGE signaling pathway in diabetic complications. These results are shown in The 20 pathways with the highest GO enrichment of Chaihu Anxin capsule in biological processes, cellular components and molecular functions were identified by GO-based functional enrichment and annotation. These results are shown in 3.7-1, showing good binding force. These results are shown in IL6 (PDB ID 1ALU), IL1B (PDB ID 6Y8M), AKT1 (PDB ID 1UNP), TP53 (PDB ID 1QKT), and STAT3 (PDB ID 6QHD) were selected for molecular docking analysis. For molecular docking, the top three active substances  in the network were chosen. Molecular docking results indicated that the binding energies of the three active ingredients with IL6, IL1B, AKT1, TP53, and STAT3 were less than -5.0 kcal·mol4Bupleuri radix, Paeoniae Radix Alba, Puerariae radix and other medicinal materials. This medicine is used to treat depression syndrome, the symptoms of which include dizziness, asthenia, restlessness, dreaminess, and decline of living and working abilities. The “Pharmacopoeia of the People’s Republic of China” has recorded that Bupleuri radix tastes bitter, pungent, and microcold, belonging to the liver, gallbladder, and lung meridians. It relieves exterior and antipyretic effects, lifting Yang Qi and soothing liver-qi stagnation  1/2, which are linked to brain derived neurotrophic factor (BDNF), in the prefrontal cortex (PFC) and hippocampus . Yin Y eThe PPI network identified the IL6, IL1B, AKT1, TP53, and STAT3 genes as significant targets. IL-6 is a peripheral or central cytokine that plays a significant role in stress responses and depressive disorders, particularly physical illnesses that coexist with depression, according to evidence from animal and human studies . In the The 153 possible targets were subjected to GO enrichment analysis and KEGG enrichment analysis. The findings of the GO analysis suggested that cellular response to nitrogen compound, xenobiotic stimulus, molecule of bacterial origin, neurotransmitter receptor activity, and postsynaptic membrane may play a role in the treatment of depression. These targets were mostly connected to lipids and atherosclerosis as well as the AGE-RAGE signaling pathway in diabetic complications, according to KEGG pathway analysis. The most significant cardiovascular risk factors for a poor prognosis in myocardial infarction patients now include chronic depression. In a review, the importance of the central and autonomic control of cardiac functions, or the neuro-cardiac axis, is thoroughly explained, highlighting the functions of acute and chronic stress, circadian rhythms, emotions and the social environment in initiating acute cardiac events and deteriorating heart function and metabolism in chronic cardiovascular diseases . The AGEMolecular docking results confirmed that quercetin, beta-sitosterol and kaempferol had good affinities for depression-related molecules, such as IL6, IL1B, AKT1, TP53, and STAT3. A review noted that quercetin could decrease the mRNA expression levels of IL1B . SelvaraHowever, this study has some drawbacks. More research is required to determine how Chaihu Anxin Capsule treats depression by activating the AGE-RAGE signaling pathway in diabetes complications as well as the lipid and atherosclerosis pathways. The mechanism of the Chaihu Anxin capsule identified in this study also requires more analysis and verification through experimental investigation. The effects and molecular mechanism of Chaihu Anxin Capsule in the treatment of depression will be further investigated using molecular biology techniques.5In conclusion, a total of 260 active ingredients were identified from the TCMSP database. The Chaihu Anxin capsule targets and depression targets were intersected by using a Venn tool to obtain 153 targets, identified as “key targets” for PPI network construction and GO\KEGG analysis. Targets with high degree values in the PPI network included IL6, IL1B, AKT1, TP53, and STAT3. These genes were considered significant targets involved in the effects of Chaihu Anxin capsule on depression. KEGG enrichment analyses of the 153 key targets revealed that lipid and atherosclerosis and the AGE-RAGE signaling pathway in diabetic complications were the most enriched pathways. After molecular docking, quercetin, beta-sitosterol and kaempferol were found to interact directly with IL6, IL1B, AKT1, TP53, and STAT3. Our study elaborated the multicomponent synergy mechanisms of the Chaihu Anxin capsule in the treatment of depression for the first time, which also provided a pharmacological basis for treating depression.The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/LY: Data curation, Methodology, Software, Visualization, Writing – original draft. YZ: Data curation, Formal Analysis, Investigation, Software, Supervision, Validation, Writing – original draft. RQ: Conceptualization, Investigation, Methodology, Writing – original draft. YF: Conceptualization, Methodology, Validation, Writing – review & editing. CZ: Funding acquisition, Resources, Supervision, Writing – review & editing. JY: Funding acquisition, Project administration, Resources, Validation, Writing – review & editing.


Background: Ulcerative colitis (UC) and irritable bowel syndrome (IBS) share various similarities in clinical symptoms, pathogenesis, and treatment. UC concurrent IBS tends toward more severe symptoms and worse prognosis, and promising feasible therapies for the overlapping symptoms remains a challenge. Rhubarb peony decoction (RPD) is a well-known traditional Chinese medicine that has been widely applied in treating UC. RPD may exert extensive therapeutic effects on both IBS and UC. However, the common mechanism of its treatment remains unclear. We aimed to assess the potential pharmacological mechanism of RPD in the treatment of overlapping IBS and UC.Methods: The active components and targets of RPD were retrieved from ETCM, TCMSP, BATMAN-TCM, and TCM databases. The disease targets were screened by searching the DrugBank, OMIM, TTD, and PharmGKB databases. PPI network analysis was performed and visualized via the STRING platform and Cytoscape software. GO and KEGG enrichment analyses of the hub genes of RPD were predicted to elucidate the potential molecular mechanism. Subsequently, molecular docking was carried out to verify the combination of active compounds with core targets.Results: By integrating all targets of RPD and disease, a total of 31 bioactive ingredients were identified including quercetin, kaempferol, aloe-emodin, beta-sitosterol, and (+)-catechin, etc. JUN, TP53, MAPK1, RELA, MYC, and ESR1 were explored as potential therapeutic targets among 126 common drug-disease-related targets. They were enriched in the AGE-RAGE signaling pathway in diabetic complications, as well as the NF-kappa B signaling pathway and MAPK signaling pathway. Additionally, some active ingredients were identified as candidates for binding to the hub targets via molecular docking, further suggesting their anti-inflammatory and antioxidative properties.Conclusion: RPD may exert the overall treatment effect for UC and IBS overlap syndrome via the biological mechanism of “multi-ingredients, multi-targets, and multi-pathways” on inflammation, oxidative stress, immune, oncogenicity, and gut microbiota dysbiosis. Ulcerative colitis (UC) is a chronic idiopathic inflammatory disease that affects the colon, characterized by recurrence and remission of mucosal inflammation. Mucosal inflammation begins in the rectum and continues proximally to the colon . The morRhei Radix et Rhizoma), tao ren (Persicae semen), dong gua zi (Benincasae semen), dan pi (Moutan Cortex), and Mirabilite . RPD is widely used to treat intestinal carbuncle in China. So far, its novel and effective pharmacological effects on UC have been repeatedly discovered. Luo et al. confirmed that RPD could significantly alleviate the pathological damage in the colon of UC mice by reducing the proportion of Thl7 cells and inflammatory cytokine mediators [Traditional Chinese medicine (TCM) has been considered an alternative therapy for UC and IBS. TCM is known for its mild nature and has fewer side effects than western medicines. Rhubarb peony decoction (RPD) is a well-known TCM formula, first described in the “Golden Chamber Synopsis” written by the Chinese physician Zhongjing Zhang in the Chinese Eastern Han dynasty, and has more than 2000 years of clinical application history in China. RPD is composed of five herbs: da huang  [http://bionet.ncpsb.org.cn/batman-tcm/) [http://www.tcmip.cn/ETCM/index.php/Home/Index/index.html) [http://tcm.cmu.edu.tw/) [http://www.uniprot.org/) for annotating gene names.The active chemical components of five herbs in RPD were retrieved from four public databases including the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform , the Bioan-tcm/) , the Encex.html) , and Traedu.tw/) . All of https://www.genecards.org/), Online Mendelian Inheritance in Man , PharmGKB (https://www.pharmgkb.org/), Therapeutic Target Database , and DrugBank (https://go.drugbank.com/). Finally, the common targets of UC and IBS were obtained by merging and eliminating the repeated targets of each disease database.In addition, disease-related targets were retrieved from five public databases via the keywords “ulcerative colitis” and “irritable bowel syndrome”: GeneCards  [multiple proteins” was chosen, “Homo sapiens” was set for protein species, and “highest confidence (0.9)” was the minimum interaction threshold. The PPI network was generated to visualize the complex connections. In addition, both active ingredients and corresponding targets were imported into Cytoscape 3.6.1 to further elucidate the interactions of the common target genes in the treatment of UC and IBS with RPD. The CytoNCA plugin was used to calculate the topological parameters of nodes to provide an in-depth analysis of the attributes of nodes in the interactive network. Six main reference parameters were calculated including betweenness centrality (BC), closeness centrality (CC), degree centrality (DC), eigenvector centrality (EC), network centrality (NC), and local average connectivity (LAC). Higher quantitative values of parameters indicate the greater significance of nodes in the network. Target nodes with all six parameters higher than the corresponding median values in the PPI network were selected to construct a new PPI network. The node selection criteria were repeated to obtain the core PPI network.The PPI network was constructed and clarified by STRING (db.org/) . “multip10.18129/b9.bioc.org.Hs.eg.db), the “enrichKEGG” function was applied for KEGG enrichment analysis, and the relative database was the KEGG database (https://www.kegg.jp/), respectively. It was determined that the functional terms and pathways with q-values (enrichment score) <0.05 were regarded as statistically significant and retained. The results were sorted according to the q-value, and the top 20 results were visualized as barplot or bubble diagram.Gene Ontology (GO) term enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were carried out via the R package including “colorspace,” “clusterProfiler,” “dose,” “stringi,” “enrichplot,” and “ggplot2” which were installed in software R 4.2.1. The function “enrichGO” was carried out for GO enrichment analysis, and the database was org. Hs .eg. db (DOI: https://www.rcsb.org/), and 2D molecular structures of ligands were derived from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/), respectively [The key targets were molecularly docked to the active ingredients for the primary validation. The three-dimensional(3D) structures of key target proteins were downloaded from the Protein Database Bank (ectively . Chem3D ectively . The lowectively . A heatm2SO4·10H2O) is a kind of inorganic compound that exerts effects on drug absorption by promoting small intestine movement [Through searching the TCMSP and other online databases to obtain the compounds and prediction targets of RPD. Mirabilite , TP53 (n = 38), MAPK1 (n = 38), RELA (n = 36), MYC (n = 28), and ESR1 (n = 24) ” for the minimum interaction threshold . To furt(n = 24) . These tGO biological processes and KEGG pathway enrichment analysis were carried out to elucidate the functions and the enriched pathways of the potential treatment genes of RPD. The GO analysis consists of biological process (BP), cellular component (CC), and molecular function (MF). In this study, a total of 3,963 statistically significant GO terms were obtained with q-value <0.05, including 2053 of BP, 54 of CC, and 164 of MF. The top 10 terms were visualized in a bubble chart . The red, including “AGE-RAGE signaling pathway in diabetic complications,” “Lipid and atherosclerosis,” and “Fluid shear stress and atherosclerosis.” Additionally, five main pathways were involved in the treatment of common diseases by RPD: “NF-kappa B signaling pathway” (hsa04064), “MAPK signaling pathway” (hsa04010), “Inflammatory bowel disease” (hsa05321), and “Tp53 signaling pathway” (hsa04115)  . OverallTo evaluate the affinity of the candidate bioactive compounds for related targets, molecular docking analysis was performed for mimicking the interaction between small ligand molecules and receptor protein macromolecules. The binding poses and interactions of five ingredients with six proteins were obtained with Autodock Vina v.1.2.2. Additionally, the binding energy between the two counterparts for each interaction was calculated to predict their affinity . DockingAlthough the significant difference between UC and IBS is the endoscopic manifestation, more than 30% of quiescent UC patients report IBS-like symptoms, irrespective of whether they are accompanied by low-grade inflammation or not. UC concurrent IBS tends toward more severe psychological symptoms and worse quality of life, so proper intervention is warranted , 26. DesGuided by a holistic view and syndrome differentiation, TCM achieves multi-target and multi-pathway efficacy through prescription and prescription coordination and interaction. Network pharmacology is an excellent tool to construct a drug-target network and reveal the underlying mechanisms of TCM. Spleen deficiency was regarded as the original cause of UC based on TCM theory . AdditioBy integrating all the targets of RPD and disease, 126 relative targets were identified, and top targets such as JUN, TP53, MAPK1, RELA, MYC, and ESR1 in the PPI network were considered as hub genes. Meanwhile, the GO and KEGG analysis revealed that inflammation, oxidative stress, immunity, oncogenicity, and gut microbiota dysbiosis are significantly involved in the pathological mechanisms of UC and IBS. BP enrichment results indicated that a variety of genes were associated with oxidative stress, including “response to oxidative stress,” “response to xenobiotic stimulus,” and “cellular response to chemical stress.” Emerging evidence has made great strides in clarifying that oxidative stress plays a crucial role in the development of colitis . During Furthermore, the molecular docking results indicate that MAPK1, RELA, TP53, JUN, MYC, and ESR1, have superior affinities to the five core compounds quercetin, kaempferol, aloe-emodin, beta-sitosterol and (+)-catechin, which verified that colon damage may be repaired by improving inflammation, and reducing oxidative stress. Quercetin is a natural polyphenolic compound belonging to the flavonoid family. It is considered the most effective reactive oxygen species (ROS) scavenger by upregulating proinflammatory factors. Multiple animal models have confirmed quercetin exerts antioxidant and anti-inflammatory effects  by appeain vitro and animal experiments [Likewise, aloe-emodin (a bioactive component of rhubarb), with a higher degree value in the PPI network, exerted an anti-inflammatory role by suppressing the secretion of inflammatory factors, downregulating the cascade reaction of NF-κB, MAPK, and PI3K pathways . Aloe veeriments . β-Sitoseriments . Kang eteriments . Taken tKEGG analysis results demonstrated that the mechanism of RPD in the treatment of UC and IBS was mainly related to the following pathways indicating multiple targets and multiple pathways: “AGE-RAGE signaling pathway in diabetic complications,” “Inflammatory bowel disease,” “NF-κB signaling pathway,” “MAPK signaling pathway” and “Tp53 signaling pathway.” AGE-RAGE signaling pathway was involved in and mediated various signaling pathways by activating the PI3K-Akt and MAPK as well as the NF-κB signaling pathway, to induce ROS production and lead to inflammatory responses. NF-κB is acknowledged as a sign and the central pathway of inflammatory response, mediating various signaling pathways of inflammatory response . The traIt is well-known that CRC is associated with the inflammation–dysplasia sequence, which poses a major threat to the prognosis of UC and IBS. The incidence of UC-related colon cancers was 1.6∼3.7%, accounting for 5.4% in all colon types , 54. ChrFirmicutes and Actinobacteria and reducing Proteobacteria and Bacteroidetes [Bifidobacterium, Bacteroides, and Lactobacillus increased significantly while Fusobacterium and Enterococcus decreased totally. These findings indicate that RPD has the comprehensive ability to modify gut microbiota and suppress pro-inflammatory cytokines. Therefore, our results indicate that RPD may also have a role in regulating intestinal microbiota.Gut microbiota alternation is one of the underlying factors in perpetuating IBS symptoms . Both ouroidetes . Furtherroidetes . The abuin vitro and in vivo.UC is a chronic recurrent intestinal inflammatory disease, whereas IBS is a functional intestinal disorder. The current clinical treatments for them are different, as IBS requires mainly symptomatic treatments. And the goal of UC treatment is to achieve clinical or endoscopic remission. It is challenging to tell the difference between IBS patients and UC in remission due to the numerous similarities between the two. Timely and accurate identification is key to avoiding overtreatment of IBS or delayed diagnosis of UC. When the two conditions are difficult to distinguish, Chinese medicine may be a proper option. However, the present study has several limitations. Firstly, absorption pathways, effective sites, and dose-effect outcomes, markedly effective components of bioactives in RPD, should be studied in depth. Secondly, the complex interaction between gut microbiota and herbal compounds needs more exploration. Moreover, any single certain bioactive detected in RPD is not sufficient to stand in completely for RPD. Thus, more experiments are required to further explore the potential molecular mechanism of RPD in the treatment of UC-IBS In conclusion, both network pharmacology and molecular docking were applied to predict the common mechanism of RPD for the treatment of UC and IBS. The GO and KEGG pathways significantly enriched several signaling pathways involved in inflammation, oxidative stress, immunity, oncogenicity, and gut microbiota dysbiosis. Meanwhile, molecular docking results further verified that all the key active ingredients exhibited superior affinities to their core targets. RPD has revealed synergistic therapeutic effects in the treatment of UC and IBS partly by regulating multi-component, multi-target, and multi-pathway effects, which coincide with the biological mechanism of “treating different diseases with the same treatment.” This study offers novel insights into the effective therapeutic and management strategies for patients overlapping between UC and IBS, proposing future directions for research in this stimulating field.


Saponin-rich medicinal plants, particularly ginseng and Pseudo ginseng, are valuable in traditional medical practice due to the presence of different saponins. These plants benefit from natural saponins/triterpenoids drugs, such as Ginsenosides, Gypenosides, Platycodins, and Lancemasides. Ginsenosides are highly required for research and functional materials preparation in industrial practices, and some compounds, like Compound-K, have been taken to human trials for various therapeutic applications. To elucidate the genes/transcripts profiles responsible for secondary metabolites and ginsenoside biosynthesis in Ginseng and Pseudo ginseng plant genomes, a comparative analysis was conducted in this study. Nine plant genomes with a 99% BUSCO completeness score were used, resulting in 49 KEGG secondary metabolite pathways, 571 cytochromes genes with 42 families, and 3529 carbohydrate genes with 103 superfamilies. The comparative analysis revealed 24 genes/transcripts belonging to the CYP716 family, which is involved in the ginsenoside biosynthesis pathway. Additionally, it found that various ginsenosides demonstrated strong binding affinity with twelve targets, with ginsenoside Rg3, Rg2, Rh1, Rh5, F3, Rh9, Panaxadione, Protopanaxatriol, Floral ginsenoside C, and Floral ginsenoside E exhibiting the highest binding affinities with the tested enzymes. Since these groups of enzymes are not yet fully characterized for Pseudo ginseng plants in the interconversion of triterpenoids, this comparative bioinformatics analysis could aid experimentalists in selecting and conducting characterization with practical knowledge. Araliaceae family, encompassing 15 species and 7 subspecies. The term “Panax” originates from the Greek word “panacea”, indicating a universal remedy. Notably, the anthropomorphic root of Panax ginseng stands out for its medicinal attributes and shares a homologous genome size correlation with the human genome. The usage of ginseng is very prevalent in traditional Chinese medicine (TCM)- and oriental medicine (OM)-based health supplement industries. The first generation of drug discovery was based on the alkaloid drugs that were isolated from medicinal plants. After that, the medicinal plant’s effectiveness was determined by its phytochemical ingredients [Ginseng, a non-model plant, is recognized as an adaptogen within the Panax genus in the redients . The ginredients . Among tPanax plants, leading to the discovery of around 330 ginsenosides [Panax family and have a dammarane backbone moiety with an array of glycans in their functional groups [Panax family plants characterize the ginsenoside biosynthesis pathways [Ginseng has been used for centuries in traditional Chinese medicine and oriental medicine due to its yin–yang properties. In 1854, a German scientist named Garrigues isolated the Panaquilon chemical component from enosides ,7. Thesel groups ,10. Howel groups . One sucl groups . Ginsenol groups . The conpathways ,15.Gynostemma pantaphyllum, which is often referred to as the “poor man’s ginseng”. This plant contains triterpenoids called gypenosides, which are similar to ginsenosides  and are widely used in green tea around the world [G. pantaphylum in medicinal plant research [It is not just ginseng plants that are widely valued in the market. Pseudo ginseng, which is more affordable due to its wider accessibility, has also gained popularity. One such example is he world ,17. Due Codonopsis  and platPanax ginseng (PAGI0), Panax notoginseng (PANO0), Panax japonicus (PAJA0), Panax stipuleanatus (PAST0), and Panax quinquefolius (PAQU0) [Codonopsis lanceolata (COLA0) [Platycodon grandiflorus (PLGR0) [Gynostemma pentaphyllum (GYPE0) [Daucus carota (DACA0)) were selected and downloaded from the Refseq assembly database. The respective annotations were obtained from the corresponding authors via email request [Nine assembled genomes  )) and Ps (COLA0) , Platyco (PLGR0) , Gynoste (GYPE0) , and out request ,23,24,25 request . The dethttps://www.genome.jp/kegg/pathway.html, accessed on 1 February 2023) and extracted respective protein sequences and other information, such as pathway name and KEGG orthologs ids, using Python scripts. Additionally, the coverage values for the pathway were calculated following the method described by Kim et al. [We included the manually curated ginsenoside conversion microbial enzymes  and enzym et al. , as follThe normalized value was calculated as (number of KEGG orthologs (KO) that have similar transcripts to the reference transcriptome/total number of KO in each pathway) × 100. Furthermore, we downloaded the terpenoid biosynthesis pathway proteome from UniProt database for additional confirmations.https://cyped.biocatnet.de/, accessed on 1 February 2023) [http://tree.bio.ed.ac.uk/software/figtree/, accessed on 1 February 2023) to obtain an image, which is shown in Figures 3–5 and The complete transcripts were compared with the CYPED (ry 2023)  databasery 2023) . The mulry 2023)  and werery 2023) . FinallyAs per the genome assessment carried out in this study, seven enzymes from the CYP716 family, namely, CYP716A52, CYP716A12, CYP716AL1, CYP716A15, CYP716A17, CYP716A47, CYP716A53, were found to be involved in the secondary metabolites and ginsenoside biosynthesis pathways, with reference to the MetaCyc pathway database. Additionally, the study also profiled five UGT1 family carbohydrate enzymes, UGT71A27, UGTPg101, UGTPg100, UGT74AE2, and UGT94Q2, and more details about them are provided in https://discover.3ds.com/discovery-studio-visualizer-download, accessed on 1 February 2023). Two-dimensional figures were drafted using the same software, and 2D diagrams were generated to depict hydrogen bonds and hydrophobically interacting residues. Each ligand cluster was inspected for amino acids interacting with the ligand, hydrogen bonds (H bonds), and the specific atoms involved.The 3D structures of all the selected proteins were available in their native forms and were downloaded from the RCSB PDB database  in the PC. lanceolata, P. grandiflorus, and G.pentaphyllum), and an outgroup D. carota . This study conducted a comparative genome analysis among Panax families and Pseudo ginseng plants using genome data from public repositories and published genome articles. Secondary metabolites were clustered with KEGG secondary metabolite pathways, resulting in 6933 sequences from nine genomes. Among them, 1178 and 1074 genes were present in P. ginseng [Panax and other Pseudo ginseng plants. Among those, 16 cytochrome families were found to be involved in terpenoid biosynthesis, and 19 others were found to be involved in other secondary metabolite biosynthesis pathways. According to the MetaCyc pathway database, the CYP716 family enzymes are primarily characterized for ginsenoside biosynthesis. In total, twenty-four sequences from all selected genomes were plotted as a phylogenetic tree in Panax plants were summarized into three groups based on their available ginsenoside profiles. However, due to the lack of enough datasets, a similar process has not yet been carried out for Pseudo ginseng plants. Therefore, in this study, Panax plants were considered as a model/reference for Pseudo ginseng to gain knowledge on triterpenoid biosynthesis pathway possibilities. These findings could be used to develop a similar yeast model for the industrial production of opioids cascade biosynthesis in one step [The advantage of “genome-wide” comparison is that it provides an overview of the selected targets/biosynthesis pathways from a desired plant. Earlier, a similar profiling process was conducted for cytochrome multifamily genes with expressed sequence tags (EST) in  ginseng , which w ginseng , and, fi ginseng . Limited ginseng . Only th ginseng ,46,47. Tone step . For exaone step ,50. Our one step , CYP716Aone step , and CYPone step ) group eone step , and simone step .The biosynthesis of glycosides such as Ginsenosides, Gypenosides, Platycodins, and Lancemasides in plants is diverse, and subsequent glycosylation enzymes contribute to the synthesis of various glucoside secondary metabolites. Various carbohydrates such as UDP-alpha-D-glucose, UDP-GluA, UDP-Xyl, UDP-Gal, UDP-Arap, UDP-Araf, and UDP-Rha are present in these terpenoid backbone moieties due to the presence of various carbohydrate enzymes. Since around 300 ginsenoside  and 200 Panax family plants, UGT71-100 is the most prevalent. Within this family, the UGT1 group of enzymes is the largest. Enzymes from the AA0, GH3, and GH1 families are involved in secondary metabolic pathways, while GT1,2,4 and GH1 are involved in terpenoid biosynthesis. Specifically, in the ginsenoside biosynthesis pathway, the GH1, GH3, and GT1 family enzymes are involved, as per the MetaCyc pathway database. Interestingly, the enzyme beta-glucosidase is also involved in the process of converting saponins from Pseudo ginseng to ginsenoside, similar to cytochromes [It is worth noting that there are several subcategories of enzymes that play important roles in plant physiology. For example, the Auxiliary activity family enzymes  are widely present in all genomes and are involved in handling antioxidants. Carbohydrate-binding modules  are also present in all genomes, as are members of the carbohydrate esterase family . Glycoside Hydrolase (GH1 and GH3) families are involved in ginsenoside biosynthesis. The glycosyl-transferase family (which includes 41 families) is also important, with GT1 being characterized for ginsenoside biosynthesis. Three superfamilies within this group are involved in terpenoid biosynthesis . It is interesting to note that there are two families of pectin lyase present , and among the ochromes . However−1 to −5.9 kcal/mol−1, which is significant. Further analysis of the ligand with the highest binding affinity for the twelve targets was conducted to assess the molecular interaction. You can find more details about the binding energies of the targets and ligands in the −1. It interacted with the TRP110 amino acid residue of the target. Ginsenoside Rg3, on the other hand, had a higher affinity of −11.1 kcal/mol−1 with the UGT71A27 enzyme, and interacted with the ASN366, GLU386, TYR279, and SER278 amino acid residues. The 2D structures, binding scores, and interactions of each enzyme’s top compounds are provided in Based on molecular docking studies, it was found that most of the ginsenosides tested in this study showed highly competitive binding affinity with all twelve targets. The binding energies ranged from −11.5 kcal/molThe biosynthesis of ginsenosides comes from two significant steps, i.e., formation and modification of ginsenoside backbone moiety and carbohydrates ligation and hydrolysis processes by cytochrome and carbohydrate enzymes. In the ginseng plants, the major ginsenosides are highly dominating, and the minor ginsenosides are absent or low in quantity. As explained earlier, to enhance the production of minor ginsenosides, the enzymes are taken from the microbes of the food products and ginseng plant rhizosphere. When it comes to carbohydrates, the difference in sidechains majorly takes place by the difference in cytochrome and carbohydrate enzymes present in plants. As observed in the cytochromes profile, CYP716, already well characterized for ginsenoside biosynthesis, is present in all nine plants in our study. Furthermore, two superfamilies of UDP-dependent glycosyltransferases (UGTs) are widely present in all nine plants, similar to enzymes in the ginsenoside biosynthesis pathway. The superfamily GT1 contains the plant subfamily 71–100, which contributes to inverting the catalytic function of carbohydrates. The molecular docking studies also reveal that the ginsenosides interact with the target enzymes with higher binding affinity, which require further in-depth experimental validation such as experimental assays like enzyme activity tests and targeted metabolomics, which can confirm predicted functions. CRISPR/Cas9 gene editing can be employed to validate specific gene roles. Further, integrating these experiments with computational predictions enhances understanding and aids in developing new production strategies for bioactive compounds.