Atherosclerosis is a common cardiovascular disease that requires urgent and careful attention. This study was conducted to predict and validate the potential molecular targets and pathways of Astragalus membranaceus and Angelica sinensis (A&A) in the treatment of atherosclerosis using network pharmacology. The active ingredients of A&A were obtained using the TCMSP database, while the target genes of atherosclerosis were acquired using 2 databases, namely GeneCards and DrugBank. The disease-target-component model map and the core network were obtained using Cytoscape 3.8.2 and MCODE plug-in, respectively. The core network was then imported into the STRING database to obtain the protein-protein interaction (PPI) network diagram. Moreover, gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analyses were performed using the HIPLOT online website. Finally, the small molecules related to key signaling pathways were molecularly docked and visualized. Under the screening conditions of oral bioavailability ≥ 30% and drug-likeness ≥ 0.18, 22 active ingredients were identified from A&A, and 174 relevant targets were obtained. Additionally, 54 active ingredients were found in the extracted core network. Interleukin (IL)-17 signaling pathway, tumor necrosis factor (TNF) signaling pathway, and Toll-like receptor (TLR) signaling pathway were selected as the main subjects through KEGG enrichment analysis. Core targets  and active ingredients  were selected and validated using molecular docking. This study identified multiple molecular targets and pathways for A&A in the treatment of atherosclerosis. A&A has the potential to treat atherosclerosis through an antiinflammatory approach.Since the 20 Atherosclerosis is a common cardiovascular disease. Because atherosclerosis is a chronic inflammatory disease with a complex and interrelated mechanism, its pathophysiology is not fully understood. The most striking feature of atherosclerosis is plaque formation, where inflammation, oxidative stress, and autoimmune functions are contributing factors. Plaque formation in atherosclerosis undergoes the following 4 stages: endothelial cell dysfunction, lipoprotein deposition and oxidation, inflammatory factor effects, and fibrous cap development. Atherosclerosis mainly occurs in the coronary arteries. The continuous growth of plaques and the instability of rupture may cause local blood flow destabilization, angina, myocardial infarction, and even cardiac arrest that can endanger the life of patients. Currently used pharmacological treatments target the inflammatory response to atherosclerosis and control the excessive stress of immune cells to protect the blood vessels.Cardiovascular diseases have been the leading cause of death worldwide since the beginning of the 20 Chinese herbs have been widely used in clinical practice in Asian countries, especially China. However, due to a lack of rigorous clinical trials and unclear pharmacological mechanisms, many western countries still have reservations about Chinese medicine. For traditional Chinese medicine (TCM), combination therapy using different herbs may offer new treatment options for atherosclerosis. In TCM, the treatment methods for atherosclerosis rely on activating blood, replenishing qi, clearing heat, and removing stasis,–9 which are proven to have specific curative effects. Compared with a single drug, TCM combines several drugs and the small molecules in different herbs, which may act synergistically to facilitate the treatment of diseases.Several drugs are available to treat this disease, but the primary treatment option is statin-based lipid-lowering drugs that can counter the inflammatory response in atherosclerosis.Astragalus membranaceus (AM) include polysaccharides, saponins, and flavonoids, which have antiinflammatory and antioxidant effects. AM exhibits significant treatment effects in colitis, diabetes, and kidney disease and protects the cardiovascular and respiratory systems.–13 The present study shows that AM can interfere with AMP-activated protein kinase (AMPK), nuclear factor-κB (NF-кB), and other signaling pathways to reduce inflammation and excessive immune response. Another traditional Chinese herb, Angelica sinensis (AS), has long been used to tonify and invigorate the blood, relieve pain, and moisten the intestines. AS extracts have been shown to protect the liver, treat cerebral ischemia-reperfusion injury, reduce inflammation, and alleviate atherosclerosis.,19The combination of A&A is widely used in TCM prescriptions for treating cardiovascular diseases. The main ingredients of ,21 In this study, network pharmacology was used to elucidate the potential mechanism of the combination of A&A in the treatment of atherosclerosis and reveal the potential targets and pathways. The detailed workflow diagram of the study is presented in Figure TCM uses a combination of A&A for treating atherosclerosis. However, the underlying mechanism is not yet elucidated due to the lack of relevant studies. Network pharmacology is an analytical method that combines a biological network of systems with pharmacology, and it reflects the holistic philosophy of TCM. (https://tcmspw.com/tcmsp.php) was applied to select 2 drugs, Astragalus and Angelica, by setting oral bioavailability (OB) ≥ 30% and drug-likeness (DL) ≥ 0.18. Genes related to atherosclerosis were collected by using DrugBank (https://www.drugbank.ca/) and GeneCards databases (https://www.genecards.org/MyGenes/) with the keyword “Atherosclerosis.”The TCMSP databaseThe components of each herbal medicine obtained using the TCMSP database were imported into Cytoscape 3.8.2 software, and the ingredients present in each drug were visualized and analyzed.https://www.uniprot.org/) was used to transform the names of the collected disease variant genes and drug targets and to make them compatible. The genes were then imported into the “VENNY 2.1” online tool (https://bioinfogp.cnb.csic.es/tools/venny/index.html) to obtain the common genes.The UniProt database , and the species was selected as “Homo sapiens.” The results were then imported into Cytoscape 3.8.2 software in “tsv” format to analyze the core network further.The prior collection of common genes was entered into the STRING online database , where the KEGG database was selected, and the species was set to Homo sapiens. The results reflected the biological processes, molecular functions, cellular compositions, and pathways implicated during the treatment of atherosclerosis. The results are presented as a bubble or bar chart; the smaller the P-value, the higher the enrichment; the larger the bubble, the richer the genes are.The core genes were imported into the HIPLOT online analysis website  were downloaded from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/) in SDF format and then converted to mol2 format using Chem 3D software. The structures of the proteins  were downloaded from the RCSB database (https://www.rcsb.org/) in PDB format. Pymol software was applied to remove solvent molecules and ligands, and AutoDock Tools 1.5.6 software was used to add hydrogen, calculate the charge, and assign atomic types. Finally, the results were saved in pdbqt format. Autodock vina 1.1.2 was used for molecular docking, and the 6 combinations with the lowest binding energy were selected for visualization and analysis of the docked conformations using Discovery Studio 2020.The study of active ingredients of A&A and their targets for the treatment of atherosclerosis using molecular docking techniques can help illustrate the mechanism of action and binding activity of active ingredients and target proteins to a certain extent.AM and AS were searched separately in the TCMSP database to screen for active ingredients meeting an OB value ≥ 30% and a DL ≥ 0.18. The results showed 20 active ingredients in AM -10,13-dimethyl-17-[-5-propan-2-yloctan-2-yl]-2,3,4,7,8,9,11,12,14,15,16,17-dodecahydro-1H-cyclopenta[a]phenanthren-3-ol, isorhamnetin, 3,9-di-O-methylnissolin, 5’-hydroxyiso-muronulatol-2’,5’-di-O-glucoside, 7-O-methylisomucronulatol, 9,10-dimethoxypterocarpan-3-O-β-D-glucoside, -9,10-dimethoxy-6a,11a-dihydro-6H-benzofuranochromen-3-ol, bifendate, formononetin, isoflavanone, calycosin, kaempferol, FA, (3R)-3-chroman-7-ol, isomucronulatol-7,2’-di-O-glucosiole, 1,7-dihydroxy-3,9-dimethoxy pterocarpene, and quercetin), and 2 active ingredients in AS (beta-sitosterol and stigmasterol). The network diagram is shown in Figure The eligible active ingredients were retrieved from the TCMSP database, and the targets corresponding to the relevant active components were collected in this database. Finally, 213 targets were obtained. When “Atherosclerosis” was used as the keyword, 4717 and 39 targets were obtained using the GeneCards and DrugBank databases, respectively. The above targets were entered into the online site of venny 2.1 to obtain the common targets, as shown in Figure The 174 common targets identified for active ingredients from 18 drugs were imported into Cytoscape 3.8.2 software for visualization and analysis. As shown in Figure Homo sapiens.” The data from the preliminary analysis were exported in “tsv” format for further study using Cytoscape 3.8.2, as shown in Figure R 4.1.0, and the top 20 proteins with the highest number of associations in this network were selected to plot the histogram, as shown in Figure The 213 common genes collected through Venn diagram analysis were entered into the STRING online database, with the species selected as “P-value < 1.0 e-16. In the resulting graph, the darkness of the node depicts its importance in the network .The 54 proteins related to the core network obtained from the previous MCODE plug-in analysis were entered into the STRING database for PPI network analysis, and the results are shown in Figure Homo sapiens” was used to analyze the relevant genes. GO analysis involves biological processes (BP), cell composition (CC), and molecular function (MF). The analysis results of the top 20 most significant relevant BP terms are presented as bar charts, as shown in Figure GO and KEGG analyses were performed using the HIPLOT online analysis website. The KEGG database (public/db/kegg/hsa_kegg_20210326.rds) with the species selected as “The enrichment results for the signaling pathways were selected to be further analyzed for 3 significant pathways, IL-17, TNF, and TLR signaling pathways. The genes related to these 3 pathways were imported into Cytoscape 3.8.2 software for visualization and analysis. Figure The 7 active ingredients were docked to their relevant target proteins using molecular docking techniques. The docking results are shown in Table In the combination of CHUK-quercetin, quercetin formed hydrophobic interactions with Ile164, Pi-Sigma interactions with Val29, Val151, and Leu21, and hydrogen bonds with Glu61, Lys44, Thr23, and Cys98 of CHUK. This combination exhibited the best binding effect among the 6 groups, with a binding energy of -9.4 kcal/mol. During IKBKB-kaempferol docking, kaempferol formed hydrophobic interactions with Val152, Leu21, Val29, Ile165, and Lys44, Pi-sigma interactions with Val152 and Ile165, and hydrogen bonding interactions with Cys99, Leu21, and Asp166 of IKBKB. On the other hand, quercetin connected to MMP3 by forming hydrophobic interactions with Val698 and Leu664, Pi-cation interactions with His701, Pi-sigma interactions with Tyr723 and Leu664, and hydrogen bonding interactions with Leu718, Tyr723, and Ala665 of MMP3. The RELA protein could link to most molecules, including isorhamnetin, kaempferol, and quercetin, all being stably docked. Isorhamnetin formed hydrophobic interactions with Ala73 and Val72 of RELA, hydrogen bonding interactions with His252, Asn251, Tyr223, and Ala73, and a Pi-Pi stacking effect with Phe299. Kaempferol formed hydrophobic interactions with Ala73 and Val72, hydrogen bonding interactions with His252, Asn251, Tyr223, and Ala73, and a Pi-Pi stacking effect with Phe299. RELA docking with quercetin showed that quercetin would form hydrophobic interactions with Val72 and Ala73, hydrogen bonding interactions with Tyr285, His252, and Asn251, a Pi-Pi T-shaped effect with Tyr223, and a Pi-Pi stacking effect with Phe299. Network pharmacology is widely used to study the mechanisms of action of Chinese medicine in treating diseases,–26 by systematic elaboration of relevant targets and active ingredients, in line with the holistic philosophy of Chinese medicine. The initial network of interaction was obtained, followed by the computerized molecular docking techniques to simulate the docking of the most representative active ingredients with their associated targets. This step can verify the feasibility of the selected drugs for disease treatment.TCM is a complex system encompassing small molecules with complex pharmacological activities (synergistic or antagonistic), their targets, and the pathways of action.This study was based on a network pharmacology approach to investigate the active ingredients and potential targets of A&A in the treatment of atherosclerosis. Twenty-two active ingredients were included in the screening criteria using TCMSP database analysis, of which 20 were from Astragalus and 2 were from Angelica. The DrugBank and GeneCards databases were used to identify 174 effective targets of A&A for treating atherosclerosis. For the analysis of the key mechanisms of action of the drug, the MCODE plug-in in STRING was used to extract the core network having the top score according to computer calculation, which can be seen in Figure –30 IL-17 is the main cytokine produced by Th17 and tcrγδ + t cells. IL-17 inhibits fungal infections to a certain extent and exhibits pro-inflammatory properties.,32 Therefore, high levels of IL-17 in the blood lead to heightened inflammatory responses, promoting plaque growth in the blood vessels or making the plaque unstable and aggravating atherosclerosis.,34 TNF and TLR signaling pathways are associated with the NF-кB signaling pathway. The most crucial factor of the TNF signaling pathways is TNF-α. Upregulation of TNF-α can activate NF-кB,–37 causing p65 in the NF-кB to enter the nucleus and trigger inflammatory gene expression.,39 Similarly, TLR acts as a signal receiver and transmitter and contributes to the signal transduction and activation of the NF-кB signaling pathway in response to external inflammatory factors, resulting in an increased inflammatory response in the vasculature.,41GO enriched and demonstrated the most critical 20 BP in this study. KEGG also enriched the related pathways. For further research, we selected 3 crucial signaling pathways, IL-17, TNF, and TLR signaling pathways. The development and progression of atherosclerosis are reported to be strongly related to the cellular factors and inflammatory response in the body, and the associated treatment can focus on controlling inflammation.The 3 signaling pathways mentioned above have essential research implications in the treatment of atherosclerosis. Therefore, we used molecular docking techniques to dock all the active components related to these 3 pathways and obtained the binding energy magnitude between the active small molecule substances and the target proteins, as detailed in Table The present study predicted the active ingredients, targets, and signaling pathways involved in the treatment of atherosclerosis through network pharmacology. It also validated the feasibility of related small molecules that showed promising results in the molecular docking analysis. The feasibility and scientific validity of the combination of the 2 drugs (A&A) in the treatment of atherosclerosis were revealed. The core network and related targets highlighted in this study could serve as a guideline for other drugs used to treat atherosclerosis. However, our study also has some limitations. The accuracy of information in the database involved in collecting relevant data might have affected our conclusions. More experimental verification of the effects of the active ingredients in both drugs is also needed to obtain more reliable evidence for the efficacy of A&A in the treatment of atherosclerosis.The treatment of atherosclerosis by A&A involved multiple compounds, targets, and pathways. The use of network pharmacology revealed the potential action mechanisms and targets for A&A in the treatment of atherosclerosis. This study also found that the positive effects of A&A in atherosclerosis are, at least in part, due to the antiinflammatory effects of this combination.Conceptualization: Tianyue Wang, Yaqiong Zhou, Jingbo Wang, Jing ChenData curation: Kaina Wang, Xinyu JiangFunding acquisition: Jing ChenMethodology: Tianyue Wang, Yaqiong Zhou, Kaina Wang, Xinyu JiangProject administration: Jingbo Wang, Jing ChenSoftware: Tianyue Wang, Yaqiong ZhouSupervision: Kaina Wang, Xinyu JiangVisualization: Tianyue Wang, Yaqiong Zhou, Kaina Wang, Xinyu Jiang, Jingbo Wang, Jing ChenWriting – original draft: Tianyue Wang, Yaqiong ZhouWriting – review & editing: Tianyue Wang, Yaqiong Zhouwww.topeditsci.com) for its linguistic assistance during the preparation of this manuscript.The authors are indebted to the editor and reviewers for their constructive comments. We also thank TopEdit (


Bungarus multicinctus is one of the top ten venomous snakes in China. Its venom is mainly neurotoxin-based. Novel antivenom drugs need to be further researched and developed. Material and methods. The potential active ingredients of Cynanchum paniculatum were screened and their SDF structures were obtained using the PubChem database and imported into the SwissTargetPrediction database, and targets were obtained for the antitoxin effects of Cynanchum paniculatum in the treatment of Bungarus multicinctus bites. The Cynanchum paniculatum-active compound-potential target network and protein-protein interaction network were constructed by using Cytoscape software, and then biological function analysis and KEGG pathway enrichment analysis were performed using the DAVID.  This study aimed to explore the molecular mechanism of Cynanchum paniculatum in treating Bungarus multicinctus bites based on network pharmacology.  Seven potential active components  and 286 drug targets were obtained, including 30 key targets for the treatment of bungarotoxin toxicity. The active components mainly acted on PIK3CA, MAPK1, MAP2K1, JAK2, FYN, ACHE, CHRNA7, CHRNA4, and CHRNB2, and they antagonized the inhibitory effect of bungarotoxin on the nervous system through cholinergic synapses and the neurotrophin signaling pathway.  Cynanchum paniculatum exerts a therapeutic effect on Bungarus multicinctus bites through multiple active components, multiple targets, and multiple pathways. The findings provide a theoretical basis for the extraction of active components of Cynanchum paniculatum and for related antivenom experiments. It is es (BGTs) , 5. Bungs (BGTs) , 7. Thers (BGTs) . In Chins (BGTs) . TherefoNetwork pharmacology is an emerging discipline based on systems biology , 11. It It is also applicable for the research methods of network pharmacology to the study of toxicology. Xiaohui Fan et al. have proposed the concepts of network toxicology and network toxicology of traditional Chinese medicine . And firModern pharmacology shows that the various active ingredients of Cynanchum paniculatum can treat various diseases . ExtensiChinese medicines have been used to treat venomous snake bites for thousands of years, many of them with good clinical efficacy. Among them is Cynanchum paniculatum, also known as the “snake dysentery herb,” which is particularly effective against Bungarus multicinctus bites. Modern pharmacology has confirmed that Cynanchum paniculatum extract contains active antisnake venom ingredients , 31. Inthttp://lsp.nwu.edu.cn/tcmsp.php/), which contains 499 herbal medicines registered in the Chinese Pharmacopoeia and their 29,384 ingredients, 3311 targets, and 837 related diseases, was used to predict the chemical composition of Cynanchum paniculatum [https://pubchem.ncbi.nlm.nih.gov/) and then imported into the SwissTargetPrediction [http://www.swisstargetprediction.ch/) database. Based on the 2D and 3D similarities of the chemical components with human as the selected species of “human,” the potential targets of the compounds were predicted, and the potential targets of Cynanchum paniculatum were ultimately obtained by collating the results and removing duplicates.The Traditional Chinese Medicine Systemic Pharmacology Database and Analysis Platform (TCMSP)  and GeneCards [https://www.genecards.org/) databases were searched with “bungarotoxin” as the keyword to obtain the targets of BGT.The Online Mendelian Inheritance in Man (OMIM)   to draw a Cynanchum paniculatum-active compound-potential target network. In this network, the different types of nodes represent Cynanchum paniculatum, its active compounds, and its potential targets, and the relationships among them are shown as edges. The Network Analyzer [The potential targets of Cynanchum paniculatum were mapped to the targets of BGT to obtain the potential targets of Cynanchum paniculatum in the treatment of BGT toxicity. The active compounds and potential targets obtained above were introduced into Cytoscape , 43 softAnalyzer  plug-in A PPI network was constructed by inputting the common targets of Cynanchum paniculatum and BGT into the STRING database  with thehttp://org.Hs.eg.db/)” was installed in R software and run to convert Cynanchum paniculatum/BGT targets and common targets into entrezIDs. The “ClusterProfiler” package was installed in R software, and GO and KEGG functional enrichment analyses of the key target genes were performed with thresholds of a P < 0.05 and a Q < 0.05 based on the converted entrezIDs. The results were output in the form of bar graphs.The Bioconductor  package The active ingredients of Cynanchum paniculatum in the TCMSP database were screened with the settings OB ≥30% and DL ≥0.18, and paeonol was included according to the literature , 48 to oA total of 186 disease targets of BGT were obtained after deduplication using the OMIM and GeneCards databases. A total of 286 drug targets and 186 disease targets were entered into the Venny2.1 online mapping tool to create a Venn diagram, and 30 common targets were obtained after the intersection of the drug and disease targets . The 30 The seven potential active ingredients and 30 common drug-disease targets for Cynanchum paniculatum were entered into Cytoscape software to construct a drug-ingredient-target-disease interaction network  Figure . In FiguThe common targets of Cynanchum paniculatum/BGT were inputted into the STRING database to obtain the target network relationship data, which were then imported into Cytoscape 3.7.2 to draw the protein interaction network diagram . MAPK1, The PPI network was imported into Cytoscape 3.7.2, and the topology analysis was carried out with Network Analyzer. The four parameters of degree, betweenness centrality, and average shortest path length and closeness centrality were used as reference standards, and the genes with scores greater than the average score were selected as the core targets. The top 30 targets were plotted in a bar graph using R3.6.0 .The constructed PPI network was introduced into Cytoscape 3.7.2, and the MCODE module was used to analyze gene clusters and screen core targets. Two gene clusters  and two The 30 common targets were subjected to GO analysis for the biological process, cellular component, and molecular function categories. GO analysis showed that the intersecting genes were enriched for a total of 868 biological process terms, mainly including the hypoxic response, regulation of chemical synaptic transmission, glucose metabolism, drug metabolism, antimicrobial action, regulation of trans-synaptic signaling, and neurotransmitter metabolic process terms . The intP value representing the significance of the enrichment and a redder color indicating greater significance. The ERbB signaling, Alzheimer's disease, endocrine resistance, Fc epsilon RI signaling, prolactin signaling, and cholinergic synapse pathways had the highest relevance; the cholinergic synapse signaling pathway is the most clinically relevant pathway and may play key roles in many of the other signaling pathways. The red dots in the cholinergic synaptic signaling pathway are important links of the common targets involved in the process. The main targets involved are PIK3CA, MAPK1, MAP2K1, JAK2, FYN, ACHE, CHRNA7, CHRNA4, and CHRNB2.A total of 133 KEGG pathways were obtained by running the 30 common targets through R software. The top 20 pathways were used to create a bubble plot of KEGG functional enrichment , with thChinese herbs consist of multiple compounds with complex mechanisms of action that may affect multiple targets and pathways in humans . CynanchκB [PPI analysis and topology analysis revealed that MAPK1, SRC, and MAPK8 were the most important core targets, while cynapanoside C and cynatratoside B were the active ingredients corresponding to the three core targets. MAPK is an important transmitter of signals from the surface of the cell to the inside of the nucleus and can regulate a variety of important cellular physiological and pathological processes, such as the stress response and inflammatory response. Studies have suggested that MAPK1 is an important anti-inflammatory and antivenom target . Hossen κB . AnotherκB . AdditioκB . In summα-BGT and β-BGT) [α-BGT binds to motor endplate acetylcholine receptors and then dissociates very slowly from the receptors. In contrast, β-BGT acts on the presynaptic membrane, first inhibiting the release of neurotransmitters and then promoting the release of neurotransmitters, both of which act together to cause persistent muscle paralysis [GO analysis showed that the main cellular components involved in the biological processes of chemical synaptic transmission modulation, trans-synaptic signaling regulation, and neurotransmitter metabolism are the presynaptic membranes and posterior membranes of nerve cells. The corresponding molecules that perform these biological functions include receptors on the presynaptic membranes and posterior membranes of nerve cells and various excitatory or inhibitory neurotransmitters, among which MAP kinase and acetylcholine are the main ones. BGT contains very potent neurotoxins  and is ad β-BGT) . α-BGT baralysis , 58. Cli2O2-induced oxidative stress through an Nrf2-mediated antioxidant pathway [KEGG pathway enrichment analysis and clinical studies have shown that the cholinergic synaptic pathway plays key roles in many signaling pathways. ACHE, the most important target in the signaling pathway, plays important roles in the release and transmission of neurotransmitters.  pathway . These eAt present, the main drug for the treatment of Bungarus multicinctus bites is anti-Bungarus multicinctus bites venom serum. Xu Changqing, as an important adjuvant therapy drug, also plays an important role in clinical treatment. However, the compounds contained in Xu Changqing are much more complex, and until now, it has not been confirmed which chemical components play the key role of antitoxin. Therefore, this study analyzes its possible mechanism of action through the analysis method of network pharmacology. However, the data of the article through network pharmacology analysis is theoretically credible, which still needs to be confirmed by further animal experiments.Until now, there have been many research reports in vivo and in vitro that have confirmed that Cynanchum paniculatum has extensive antivenom effects , 30. Andα-BGT to motor endplate acetylcholine receptors or interference with the action of β-BGT on the presynaptic membranes of motor nerves. This study reveals, for the first time, the molecular mechanism of the treatment of snakebite with Cynanchum paniculatum. The focus of this study is to emphasize the role and contribution of network pharmacology in the field of snakebite research. The analysis results and clinical observations of network pharmacology support that the cholinergic synaptic signaling pathway and the ACHE target are the main therapeutic action points of Cynanchum paniculatum, which is an important pathway and target for the treatment of Bungalow snake bites. The results of this study can be used as an important direction and target for the development of new drugs against cobra toxins; however, this is only the starting step in the research and development of new drugs, and then our research group will conduct in-depth research on molecular mechanisms in vitro and in vivo. The ultimate goal is to successfully screen out high-titer antivenoms from Cynanchum paniculatum's compounds for the development of new drugs; however, this process not only takes a long time to complete but also requires a lot of financial support. Therefore, more researchers are required to work together, which can advance the research process faster. Therefore, the publication of this study may provide a direction for scientific researchers engaged in the research field of snake bite, and provide certain clues for the development of new anti-Bungarus toxin drugs.In conclusion, network pharmacology revealed that the anti-bungarotoxin effects of Cynanchum paniculatum may occur through multiple components, multiple targets, and multiple signaling pathways. Among the components, paeonol is the most important and mainly acts on ACHE in the cholinergic synaptic signaling pathway. The mechanism of the anti-bungarotoxin effects of paeonol may involve blockade of the binding of


HSP90AA1, ATP2A1, NOS1 and CRAT, as well as their three related pathways , were closely related to the therapeutic effects of HSYA. A gene and protein expression analysis revealed that HSYA significantly inhibited the expressions of HSP90AA1, ATP2A1 and NOS1 in the liver tissue of aging mice. The molecular docking results showed that HSYA had high affinities with the HSP90AA1, ATP2A1 and NOS1 targets. Our data demonstrate that HSYA may delay LA in mice by inhibiting the expressions of HSP90AA1, ATP2A1 and NOS1 and regulating the calcium signaling pathway, the estrogen signaling pathway, and the cGMP–PKG signaling pathway.Aging affects the structure and function of the liver. Hydroxysafflor yellow A (HSYA) effectively improves liver aging (LA) in mice, but the potential mechanisms require further exploration. In this study, an integrated approach combining network pharmacology and transcriptomics was used to elucidate the potential mechanisms of HSYA delay of LA. The targets of HSYA were predicted using the PharmMapper, SwissTargetPrediction, and CTD databases, and the targets of LA were collected from the GeneCards database. An ontology (GO) analysis and a Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation of genes related to HSYA delay of LA were performed using the DAVID database, and Cytoscape software was used to construct an HSYA target pathway network. The BMKCloud platform was used to sequence mRNA from mouse liver tissue, screen differentially expressed genes (DEGs) that were altered by HSYA, and enrich their biological functions and signaling pathways through the OmicShare database. The results of the network pharmacology and transcriptomic analyses were combined. Then, quantitative real-time PCR (qRT-PCR) and Western blot experiments were used to further verify the prediction results. Finally, the interactions between HSYA and key targets were assessed by molecular docking. The results showed that 199 potentially targeted genes according to network pharmacology and 480 DEGs according to transcriptomics were involved in the effects of HSYA against LA. An integrated analysis revealed that four key targets, including  Aging is inevitable in biological organisms, and it is a multidimensional process of organismal decline . AlthougCarthamus tinctorius L.) belongs to the Compositae family of herbs, which is a versatile economic crop and one of the most widely used traditional Chinese medicines [27H32O16, and a molecular weight of 612 kDa. It is the main active ingredient in safflower [Safflower , mainly including the calcium signaling pathway (hsa04020), the MAPK signaling pathway (hsa04010), and cardiac muscle contraction (hsa04260) (p < 0.05), including metabolic pathways (hsa01100), circadian rhythm (hsa04710), and biosynthesis of antibiotics (hsa01130)  C. A totasa01130) D.SLC8A3, RYR1, MYLK2, PHKG1, TNNC1, TNNC2, ATP2A2, ATP2A1, NOS1, ADCY1, CACNA1S and SLC25A4 genes in the calcium signaling pathway were all upregulated in D-gal-induced aging mice, but HSYA could inhibit the expressions of these genes , the glucagon signaling pathway (hsa04922), and protein processing in the endoplasmic reticulum (hsa04141). The se genes A. Seven 1B genes B. HSYA cHSP90AA1, CRAT, ATP2A1 and NOS1 . After HSYA treatment, compared with the D-gal group, HSYA could significantly inhibit the expressions of HSP90AA1, ATP2A1 and NOS1 (p < 0.05), but the change in the expression of the CRAT gene was not significant . The cGMP and PKG protein expression levels were increased in the D-gal group with HSYA compared to the D-gal group (p < 0.05). This indicated that the mechanism of HSYA delay of liver aging may be related to the above targets and signaling pathways.The common targets identified by network pharmacology and transcriptomic analysis of HSP90AA1, ATP2A1 and NOS1, acted on the estrogen signaling pathway (hsa04915), the calcium signaling pathway (hsa04020), and the cGMP-PKG signaling pathway (hsa04022) through 12 common pathways . We valiTo further verify the reliability of the target prediction results, the main relevant targets were subjected to molecular docking verification. The interaction energy results obtained using Autodock vina 1.1.2 software for semiflexible docking are shown in HSYA is one of the most important effective monomer molecules in safflower, with multitarget and multipathway pharmacological characteristics . CombiniIn network pharmacology studies, two important signaling pathways of HSYA for delaying LA were also uncovered, namely, the regulation of TRP channels by inflammatory mediators and the PI3K-Akt signaling pathway. The TRP ion channel family is implicated in a variety of physiological and pathological processes, including calcium influx, regulation of the intracellular microenvironment, and maintenance of vascular function . HSYA coGYS1, PYGL and PHKG1 genes play crucial roles in the glycogenolysis step of the glucagon signaling pathway, and their overexpression destabilizes glycogenolysis and predisposes one to glycogen storage disease [In the data from the transcriptome sequencing, two pathways related to HSYA delay of aging were likewise identified: the glucagon signaling pathway and protein processing in the endoplasmic reticulum. Glucagon raises blood glucose, exerting the opposite effect of insulin, and is a counter-regulatory hormone for insulin . The scr disease ,43, whic disease . The resDNAJB1, HSP90AA1 and HSPH1 were present in the liver tissue of aging mice, indicating an increased level of endoplasmic reticulum stress in the livers of aging mice. HSYA could regulate the expression of HSP family genes, indicating that HSYA may alleviate the endoplasmic reticulum stress level in aging mice and ensure the normal processing of proteins in the endoplasmic reticulum, thereby exerting an anti-aging effect.The endoplasmic reticulum is an important site for protein synthesis in the body, and with the onset of aging, the function of the endoplasmic reticulum gradually declines and abnormal protein accumulates, which can cause the onset of endoplasmic-reticulum-mediated responses . The heaHSP90AA1, ATP2A1 and NOS1 genes were inhibited by HSYA to delay LA, but the CRAT1 gene only showed a decreasing trend. It has been suggested that HSYA may inhibit the high expression of messenger molecules, such as HSP90AA1, ATP2A1 and NOS1, in the liver, thereby protecting the balance of the pathway mediated by messenger molecules and maintaining the structural stability of specific target proteins [CRAT1 needs further investigation.By combining network pharmacology and a transcriptomic analysis, we finally identified four key targets  and twelve signaling pathways. The target genes were mainly involved in the estrogen signaling pathway, the calcium signaling pathway, and the cGMP-PKG signaling pathway. In the present study, the proteins ,49,50, wHSP90AA1 gene can interfere with the nuclear pathway and affect the binding of ERβ to estrogen, which in turn affects downstream transcription factors. In severe cases, it can also cause diseases such as estrogen resistance syndrome [The estrogen signaling pathway has two signaling pathways that function in different ways, nucleus- and membrane-initiated steroid signaling. In the nuclear pathway, estrogen binds to the receptors ERα and ERβ to form an ER–ligand complex, which exerts biological effects . Li et asyndrome  and fattsyndrome . In thisATP2A1 and NOS1 genes could regulate the calcium signaling pathway, and the high expression of ATP2A1 caused by aging could lead to interference with internal pathways so that the IP3R receptor or RYR receptor located in the endoplasmic reticulum and sarcoplasmic reticulum were in a state of regulation [ATP2A1 and NOS1 genes in the livers of aging mice increased according to both predicted and experimental means, and HSYA significantly inhibited the expression levels of ATP2A1 and NOS1, suggesting that HSYA could delay liver aging by inhibiting the ATP2A1 and NOS1 genes.When the results of network pharmacology and the transcriptome were analyzed separately, the calcium signaling pathway was significantly enriched in both, suggesting that it may be the main regulatory pathway for LA treatment by HSYA. The calcium signaling pathway maintains the balance of intracellular calcium ions through both internal and external pathways, and it regulates the homeostasis of calcium ions through voltage-gated channels . A studygulation . Additiogulation , which ugulation . In thisThe cGMP-PKG signaling pathway is an important target pathway for cell signaling in the body and one of the pathways affected by the calcium signaling pathway. It is well-known that aging is a risk factor for the development of cardiovascular diseases, such as hypertension, coronary artery disease, and heart failure. The high expression of calcium transport subunits, such as ATP2A1, restores the decrease in cytoplasmic calcium concentration and myofilament sensitivity to calcium ions triggered by the specific activation of PKG1 isoforms, which leads to smooth muscle tension and an increased incidence of coronary artery disease . cGMP, PIn conclusion, this study systematically elucidated the potential mechanism of HSYA delay of LA by combining network pharmacology and transcriptomic techniques. It was speculated that HSYA may delay LA in mice by inhibiting the expressions of HSP90AA1, ATP2A1 and NOS1 and by regulating the calcium signaling pathway, the estrogen signaling pathway, and the cGMP-PKG signaling pathway. This study provides a theoretical basis for the research and application of HSYA in the field of anti-aging.HSYA was purchased from Dalian Meilun Biotechnology Co., Ltd. . HSYA powder was dissolved in sodium chloride as a working solution. D-gal was provided by Sigma-Aldrich . Trizol reagent, Prime Script Master Mix, and SYBR-qRT-PCR Kits were obtained from TaKaRa Biotechnology Co., Ltd. . BCA Protein Assay Kits were ordered from Bytec Biotech Co., Ltd. . Anti-HAP90AA1 antibody, anti-ATP2A1 antibody, anti-NOS1 antibody, anti-PKG and anti-β-actin antibody were purchased from Wanlei Biological Technology Co., Ltd. . HRP-conjugated goat anti-rabbit IgG/HRP was obtained from Bioss Biotechnology Co., Ltd. .https://www.chemicalbook.com/ (accessed on 15 December 2021)) platform to obtain the English name, chemical formula, structural formula, mol format, and SDF format of HSYA. We uploaded the information to the SwissTargetPrediction (http://www.swisstargetprediction.ch/ (accessed on 15 December 2021)), PharmMapper (http://lilabecust.cn/pharmmapper/ (accessed on 15 December 2021)) [https://ctdbase.org/ (accessed on 15 December 2021)) [https://www.genecards.org/ (accessed on 15 December 2021)) human gene database was used to annotate human genes and provide annotated prediction-related information [https://bioinfogp.cnb.csic.es/tools/venny/index.html/ (accessed on 16 December 2021)) [We used the Chemical Book (r 2021)) , and CTDr 2021))  databaseormation . We enter 2021))  softwarehttp://www.uniprot.org/ (accessed on 16 December 2021)) to standardize gene and protein names. We used the Search Tool for the Retrieval of Interacting Genes/Proteins 11.0 database ) to build a protein–protein interaction (PPI) network diagram [https://david.ncifcrf.gov/ (accessed on 16 December 2021)), the candidate targets were analyzed for the enrichment of the GO and KEGG analyses. The condition was FDR < 0.01. The NIM molecular network tool database ) was used to analyze the possible indications of HSYA targets for delaying LA [The predicted targets were imported into UniProtKB : the control group, D-gal group, and D-gal group with HSYA. The mice in the control group were intraperitoneally injected with 0.1 mL/kg/d normal saline, the mice in the D-gal group were intraperitoneally injected with for modeling, and the mice in the D-gal group with HSYA were injected with 200 mg/kg/d D-galactose and 25 mg/kg/d HSYA. After 8 weeks, the mice were anesthetized with 2% sodium pentobarbital  and then euthanized. The liver tissues of the three groups of mice were collected and immediately stored in liquid nitrogen.http://www.biocloud.net/ (accessed on 20 April 2020)); the p-value was adjusted by the false discovery rate (FDR), and p < 0.05 and fold change ≥ 2 were set to be statistically significant. GO functional enrichment and KEGG pathway analyses were performed on the OmicShare platform (https://www.omicshare.com/tools/ (accessed on 6 February 2021)) [The kidney tissues were randomly selected from mice in the control, D-gal, and D-gal with HSYA groups (n = 3), and total RNA was isolated from the kidney tissues using Trizol Reagent . The integrity and purity of the total RNA were analyzed with NanoDrop 2000 . cDNA libraries were constructed, purified, and clustered using approximately 1 μg total RNA per sample. After cluster generation, the library preparations were sequenced on the Illumina HiSeq2500 platform . The whole RNA-Seq analysis was performed by Biomarker Technologies (Beijing). The raw data (in fastq format) were processed by removing reads that contained adapters and reads with low quality based on Q20  to obtain clean, high-quality data. The DEGs were screened with the BMKCloud platform (y 2021)) .−ΔΔCT method  was performed using a reverse transcriptase kit . SYBR Green Mix  was used for two-step real-time polymerase chain reactions. The analysis was performed on a StrataGene Mx3000P thermal cycler . The GADPH gene expression in each sample was used as an internal control. The fold change in the relative expression level was calculated by the 2g for 30 min at 4 °C, and the supernatants were collected. Protein concentrations were determined with a bicinchoninic acid (BCA) protein assay. Extracted proteins were separated on precast 12% sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) by electrophoresis and were transferred onto polyvinylidene fluoride (PVDF) membranes. The membranes were incubated with the designated primary antibodies overnight at 4 °C. Next, they were incubated with horse radish peroxidase (HRP)-conjugated goat anti-rabbit antibody  for 1 h at room temperature. Signals were detected by enhanced chemiluminescence .Total protein was extracted from the liver tissues of the control, D-gal, and D-gal with HSYA groups of mice (n = 3) using a total protein extraction kit . Each mixture was centrifuged at 12,000× Commercial ELISA kits  were used to determine the cGMP levels in the liver tissue of each group of mice in accordance with the manufacturer’s instructions.https://www.ncbi.nlm.nih.gov/pccompound (accessed on 28 December 2021)) and then imported them into Chemdraw 3D. We used the MM2 module for energy minimization and used the lowest energy advantage concept and saved the results for the mol2 file. We searched the Protein data bank ) to find the protein structures of the downloaded targets, where the numbers of NOS1 and HSP90AA1 were 5uo2 and 6gr5, respectively. The structure of the ATP2A1 protein was not resolved in the PDB database, and the model was created by the AphaFold system  and visualized with PyMOL 2.5 software . After dehydration, hydrogenation, charge calculation, and non-polar hydrogen incorporation with Mgtools 1.5.6 software, the ligands and receptors were saved in pdbqt format. Molecular docking studies were performed using Autodock vina 1.1.2 software [We downloaded HSYA data in SDF format from the Pubchem database . *


The last 20 years have witnessed an explosion in publicly available gene expression and proteomic data and new tools to help researchers analyze these data. Tools typically include statistical approaches to identify differential expression, integrate prior knowledge, visualize results, and suggest how differential expression relates to changes in phenotype. Here, we provide a simple web-based tool that bridges some of the gaps between the functionality available to those studying eukaryotes and those studying prokaryotes. Specifically, our Shiny web application ESKAPE Act PLUS allows researchers to upload results of high-throughput bacterial gene or protein expression experiments from 13 species, including the six ESKAPE pathogens, to our system and receive (i) an analysis of which KEGG pathways or GO terms are significantly activated or repressed, (ii) visual representations of the magnitude of activation or repression in each category, and (iii) detailed diagrams showing known relationships between genes in each regulated KEGG pathway and fold changes of individual genes. Importantly, our statistical approach does not require users to identify which genes or proteins are differentially expressed. ESKAPE Act PLUS provides high-quality statistics and graphical representations not available using other web-based systems to assess whether prokaryotic biological functions are activated or repressed by experimental conditions. To our knowledge, ESKAPE Act PLUS is the first application that provides pathway activation analysis and pathway-level visualization of gene or protein expression for prokaryotes.IMPORTANCE ESKAPE pathogens are bacteria of concern because they develop antibiotic resistance and can cause life-threatening infections, particularly in more susceptible immunocompromised people. ESKAPE Act PLUS is a user-friendly web application that will advance research on ESKAPE and other pathogens commonly studied by the biomedical community by allowing scientists to infer biological phenotypes from the results from high-throughput bacterial gene or protein expression experiments. ESKAPE Act PLUS currently supports analysis of 23 strains of bacteria from 13 species and can also be used to re-analyze publicly available data to generate new findings and hypotheses for follow-up experiments. Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosaandEnterobacter sp.) pathogens are of high medical concern due to their virulence and ability to develop antibiotic resistance  and thus does not predict the biological effect associated with the induction or repression of a given pathway or GO term. By contrast, ESKAPE Act PLUS uses all genes or proteins that were detected in a high-throughput experiment and their associated fold changes to predict overall activation or repression at the level of a biological pathway or GO term based on the fold changes of all genes within a given pathway or GO term. While there are tools such as the commercially available Ingenuity Pathway Analysis that perform pathway activation analysis for humans and other eukaryotic model organisms  format with their input data in two columns without headers. The first column of the csv file must contain UniProt identifiers, and the second column must contain log2 fold changes for the UniProt identifiers specified in Column 1 for the comparison of interest. Column 2 must contain numeric values only, no text, and may not contain any missing values. The application provides diagnostic error messages if an input file does not meet these specifications. An example input data file for Pseudomonas aeruginosa strain PA14 can be downloaded via the application interface to illustrate the correct data format and serve as an input file for users who would like to try the application but are lacking a suitable input file. Step-by-step instructions on how to convert gene identifiers to UniProt identifiers using the UniProt ID conversion tool are provided in the User Manual that is downloadable from the application interface. ESKAPE Act PLUS generates two kinds of output – in-application output and downloadable output. Following an activation analysis, the in-app output appears in tabs in the main panel of the application, while downloadable output becomes available via the “Download results” button that appears in the left control panel of the app. In-app output includes the number of user-provided UniProt identifiers that mapped to the internal KEGG and GO database, the number of significant KEGG pathways and GO terms, as well as box plots and tables for all significant (FDR < 0.05) KEGG pathways and GO terms. Downloadable output is comprised of box plots for all significant KEGG pathways and GO terms, tables with statistical results for all KEGG pathways and GO terms that were tested, and optional KEGG Mapper . This choice corrects for a potential bias that would be introduced by any experimental design that tends to only detect certain kinds of genes or proteins. Only KEGG pathways or GO terms with an FDR-corrected Enterococcus faecium strain DO during the exponential growth phase compared to extracellular vesicles secreted during stationary phase. The authors of the original publication performed functional enrichment analysis and identified 10 functional annotation clusters in vesicle associated proteins from exponential growth conditions  and antimicrobial compounds (C. difficile that overexpresses sigma B compared to a control strain) with ESKAPE Act PLUS confirmed the KEGG pathway “Flagellar Assembly” (−5) with a median log2 fold change of -1.41 across all genes on the path. In addition, ESKAPE Act Plus extends the previously published findings by identifying Bacterial Chemotaxis (2 fold change = -1.12). This is a new insight, as the original publication did not mention that bacterial chemotaxis may be affected by overexpression of sigma B. In summary, ESKAPE Act PLUS is a user-friendly web application that not only confirms previous findings but extends beyond known observations to generate new knowledge and hypotheses that can be validated in wet-lab experiments.Previous work by Boekhoud et al. describes the role of alternative sigma factor sigma B in protecting ompounds . The autssembly”  as the memotaxis  as the sTo identify the largest possible number of significantly activated or repressed pathways and GO terms, an ESKAPE Act PLUS user would need to provide fold change information for all genes or proteins that have functional annotations. While this might be possible in the case of RNA-seq studies, proteomics experiments only detect more abundant proteins, typically accounting for 20–40% of all proteins. ESKAPE Act PLUS may fail to identify significant KEGG pathways or GO terms if fold change information is available for fewer than a few hundred genes or proteins. Another limitation is that the application cannot interpret changes in genes of unknown function that are not associated with a KEGG pathway or GO term. Finally, ESKAPE Act PLUS uses a simplified view of a pathway such that a pathway is considered significantly activated or repressed if more genes on the path are activated or repressed than would be expected by chance. This simplified view assumes that when a pathway is activated, all genes or proteins on the pathway will be induced. However, this is not always the case, for example when a pathway is turned on, upstream regulators that act as repressors are often turned off. Unlike Ingenuity Pathway Analysis, a commercial tool that is human-curated, ESKAPE Act PLUS does not account for more complicated pathway relationships such as negative regulators. Nonetheless, in practice the simplifying assumption used by ESKAPE Act PLUS has minimal impact on its sensitivity, because a small number of negative regulators with an inverse fold change from the rest of the genes or proteins on a pathway won’t prevent the pathway from reaching statistical significance.A final limitation of our system is that visualizations may not perfectly represent the results of the binomial test because the statistical analysis uses species specific annotations, but the pathway level visualization uses canonical KEGG pathways.ESKAPE Act PLUS provides high-quality statistics and graphical representations not available using other web-based systems to assess whether prokaryotic biological functions are activated or repressed by experimental conditions. While there are tools such as the commercially available Ingenuity Pathway Analysis that perform pathway activation analysis for humans and other eukaryotic model organisms, to our knowledge ESKAPE Act PLUS is the first application that extends this functionality to prokaryotes.ESKAPE Act PLUS uses biological pathway information from the Kyoto Encyclopedia of Genes and Genomes (KEGG) , obtaineP-values from the binomial test are FDR-corrected to account for the total number of KEGG pathways or GO terms that were tested. Only KEGG pathways or GO terms with an FDR-corrected P-value < 0.05 are considered significantly induced or repressed and displayed in figures and tables of the in-app results output. Results tables also contain estimates for activation or repression  as well as median fold changes and uncorrected P-values. While the in-app output only displays results for significant KEGG pathways and GO terms, downloadable csv files contain the results for all tested KEGG pathways and GO terms to allow users to identify borderline cases with uncorrected P-values < 0.05 that just barely missed the significance cutoff of FDR < 0.05.ESKAPE Act PLUS uses a binomial test to assess whether there is a significant number of upregulated or downregulated genes or proteins among all genes or proteins detected for a given KEGG pathway or GO term. KEGG pathway and GO term activation analysis were performed as previously described –28. The –KEGG Mapper , 15 provPrevotella melaninogenica, for which there was no publicly available gene or protein expression data. A summary table of the strain validation is provided as Proper function of ESKAPE Act PLUS for all supported bacterial strains was validated using existing data, except for Enterococcus faecium strain DO during the exponential and stationary growth phase. Log2 fold changes for the comparison between vesicles from the exponential and stationary growth phase were calculated using the unique peptide counts provided as a supplementary table in the original study. These log2 fold changes as well as the matching Uniprot identifiers were used to generate an input file for ESKAPE Act PLUS for Case Study 1. For Case Study 2, transcriptomic data from Clostridioides difficile strain 630 overexpressing alternative sigma factor sigma B compared to a control, originally published by Boekhoud et al. (GSE152515_Ptet-sigB_vs_Ptet-slucopt_hyb2_induced_with_thiamphenicol.xls.gz) was downloaded from NCBI GEO Series GSE152515. Gene identifiers were converted to Uniprot Entry IDs using the Uniprot ID conversion tool, as explained in detail in the ESKAPE Act PLUS User Guide.To demonstrate that ESKAPE Act PLUS confirms and extends prior knowledge, we re-analyzed existing data from two publications , 18. Thehttps://github.com/StantonLabDartmouth/ESKAPE_Act). ESKAPE Act PLUS is implemented as an R Shiny web application (http://scangeo.dartmouth.edu/ESKAPE/.The source code for ESKAPE Act PLUS is written in the R software environment for statistical computing and graphics version 4.1.1 . The codlication  using thlication  version lication  version


Noncommunicable diseases (NCDs) impose a significant burden on the health care systems in developed and developing countries. Indeed, the incidence of NCDs  has increased in epidemic proportions worldwide . AccordiDrug discovery for medicinal plant provides important leads against various pharmacological targets. A large number of plants used in the traditional medicine have now become a part of the modern world health care system. Natural novel drugs are now more achievable due to modern techniques for separation, structure elucidation, screening, and bio- and chemo-informatics , 5.Over the last decades, the amount of biological and chemical information has escalated drastically. Thus, the need for new scientific branches that handle big data has arisen. Computational chemistry and bioinformatics are now well-established scientific fields that offer the scientific community the opportunity to study drug-disease relationship. One such way to study this relationship is via understanding the connection of the disease to the target, and the consequent mechanism of interaction between the target and the drug , 7.in silico methods in drug discovery.The heterogeneity and lacking of enough data can be an obstacle that hinders the mechanistic comprehension of drug-disease relationship. In this regard, predictive computational approaches in the field of computational chemistry, e.g., network pharmacology approaches, predictive ADMET , and pharmacophore modeling, can be used to build scientific algorithms, which are developed to overcome this barrier , 9. SuchNetwork pharmacology has emerged as an important tool to understand the mechanism of action of a drug/drug candidate. It uses computational power to systematically catalogue the molecular interactions of a drug molecule in a living cell. Hu et al. exploited network pharmacology and data mining to elucidate the role of traditional Chinese medicine (TCM) in relieving epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR–TKI)-associated diarrhea. Using various approaches, they obtained 23 potential therapeutic TCM targets for the treatment of EGFR-TKI-related diarrhea. Based on the findings, they proposed that TCMs can provide data to support experimental and clinical studies on the relief of EGFR-TKI-associated diarrhea. Concomitantly, Xu et al. presented a pioneer report on the use of TCM to treat summer fever, especially in children.Yun et al. aimed to provide the basis for understanding the mechanisms of action for active ingredients of TCM against angiogenesis. GeneCards was used to explore angiogenesis-related targets. The TCM system pharmacology platform was used to uncover natural compounds. Target-compound, compound-medicine, and target-compound-medicine networks were constructed using Cytoscape. To predict the target-compound binding, molecular docking was used. Of 79 targets for angiogenesis, 41 targets were matched to 3839 compounds. 110 compounds from the dataset were found to have high correlation with angiogenesis. As a result of molecular docking, fifty-five combinations were constructed. Top combinations were for PTGS2-astragalin , KDR-astragalin , PTGS2-quercetin , and PTGS2-myricetin . Using the network, eighty other combinations were obtained and classified according to their affinities. Top combinations were KDR-beta-carotene , MMP9-beta-sitosterol , MMP9-astragalin , and MMP9-diosgenin .in vitro cellular model, they predicted two hundred and nineteen potential targets of allicin PharmMapper. Out of those, 44 potential targets related to lipid metabolism were screened out as protein targets of allicin. In the same line, Ni et al. determined pharmacological mechanisms of Chinese incompatible herbs Fuzi and Banxia (FB) in chronic obstructive pulmonary disease (COPD) using network pharmacology. From the identified targets, they proposed that effect of FB against COPD may involve the regulation of immunological function. This study provides an excellent example of the application of network pharmacology in evaluating mechanisms of action and molecular targets of an herb. Another study by Dan et al. explored the material basis and the rule of TCM against antineoplastic drug-induced cardiotoxicity (ADIC) using network pharmacology and data mining. They identified 21 potential targets, 332 candidate compounds, and 400 kinds of herbs for the management of ADIC.Cheng et al. described use of network pharmacology to investigate the mechanism of action of allicin to modulate lipid metabolism for the management of NAFLD. Using an Streblus ilicifolius were reported by Nguyen et al. One molecule possesses strong tyrosinase inhibitory activity with an IC50 value of 0.01 µM. Docking studies showed different binding affinity of the two molecules for oxy-tyrosinase. An independent study by Bader et al. presented the design and synthesis of 4-O-podophyllotoxin sulfamate derivatives and their evaluation in various cancer cell lines as potential cytotoxic agents.Two new tyrosinase inhibitors from the stems of Yu et al. conducted network pharmacology to uncover the possible mechanisms in Fuxin mixture or FXHJ for the treatment of heart failure. Ingredients of FXHJ were analysed, and 39 active ingredients were explored. 47 action targets were found to bind to these compounds. The network was constructed and enrichment analysis undertaken. The treatment of heart failure by FXHJ mixture was predicted to be via regulating several cascades, including the MAPK signaling pathway, PI3K/Akt signaling pathway, cAMP signaling pathway, TNF signaling pathway, toll-like receptor signaling pathway, VEGF signaling pathway, NF-kappa B signaling pathway, and the apoptotic signaling molecule BCL2.Ocimum basilicum extract and its major constituents on α-amylase and α-glucosidase using in vitro and in silico techniques and proposed Ocimum basilicum as a potential source to identify antidiabetic leads [3-soluble extract of the stems of Semecarpus caudata (Anacardiaceae), and their structures were resolved using NMR. These compounds were analysed for their inhibitory activity against tyrosinase inhibitory activity, and the IC50 values were 0.033 and 0.11 μM, respectively. In silico docking studies of the two compounds against oxy-tyrosinase were carried out to analyze their interactions. Of the two compounds, semedienone showed decent interactions with the amino acid and peroxide group residues of the target enzyme.The manuscript by Shanak et al. presented the inhibitory effect of the ic leads . Similarin silico study to evaluate the efficacy of an alkaloid class of phytochemicals against POP. Chemical Entities of Biological Interest (ChEBI), a publicly available database was used to retrieve the chemicals. Discovery Studio was used to predict the ADMET properties of the alkaloids to calculate their drug likeness using the Lipinski's rule of 5 and to filter the parameters based on their feasibility for the central nervous system and to cross the blood-brain barrier (BBB). To scan the strength of compound-target binding, molecular docking was performed followed by molecular dynamic (MD) simulations that enable checking the stability of alkaloid-protein complexes. The following alkaloids were selected as plausible lead compounds against POP: metergoline, pipercallosine, celacinnine, lobeline, cystodytin G, lycoperine A, hookerianamide J and martefragin A. Among these, metergoline, pipercallosine, hookerianamide J, and lobeline showed the most promising results comparable docking scores to three POP inhibitors that had reached clinical trials, i.e., Z-321, S-17092, and JTP-4819. MD simulations showed high stability of the plausible lead compounds in the active site when compared to the binding modes of the known inhibitors.Protein alpha synuclein is a protein that shows high accumulation during Parkinson's disease. Prolyl oligopeptidase (POP) is a serine protease that was shown to affect the accumulation of alpha synuclein and is a key target for the treatment of Parkinson's disease. Kulkarni et al. carried out an Myelin and lymphocyte and T cell differentiation protein 2 (MAL2) are expressed in several forms of cancer, including breast cancer. Zhong et al. studied the relationship between the expression of MAL2 and breast cancer using the Oncomine database and the Cancer Genome Atlas database. Quantitative real-time polymerase chain reaction (RT-qPCR) was used to measure MAL2 expression experimentally. Gene set enrichment analysis (GSEA) was used to identify the biological pathways correlated with MAL2 expression in breast cancer, e.g., the relationship between the level of immune infiltration and MAL2 in breast cancer. Experimental and computational techniques showed that MAL2 was expressed at high levels in breast cancer tissues compared with the surrounding tissues. As a result, high MAL2 expression can be used as an independent biomarker for breast cancer. MAL2 expression level was also found to correlate with lower immune infiltrating levels in breast cancer.


Novel treatments for autoimmune hepatitis (AIH) are highly demanded due to the limitations of existing therapeutic agents. Costunolide is a promising candidate due to its anti-inflammatory and hepatoprotective function, but its effect in AIH remains obscure. In this study, we integrated network pharmacology and experimental validation to reveal the effect and mechanism of costunolide in AIH. A total of 73 common targets of costunolide and AIH were obtained from databases. Pathway enrichment analysis indicated that PI3K-AKT pathway was the core pathway of costunolide in AIH. Protein–protein interaction network analysis and molecular docking revealed that SRC and IGF1R might play critical roles. In two murine AIH models, costunolide significantly attenuated liver injury, inflammation, and fibrosis reflected by the liver gross appearance, serum transaminases, necrosis area, spleen index, immune cell infiltration, and collagen deposition. Western blot and immunohistochemistry confirmed that phosphorylated AKT, SRC, and IGF1R were upregulated in AIH models, and costunolide administration could inhibit the phosphorylation of these proteins. In summary, costunolide significantly ameliorates murine AIH. The therapeutic effect might work by suppressing the activation of PI3K-AKT pathway and inhibiting the phosphorylation of SRC and IGF1R. Our research reveals the potent therapeutic effect of costunolide in AIH and the potential role of SRC and IGF1R in AIH for the first time, which may further contribute to the novel drug development for AIH and other autoimmune diseases. Autoimmune hepatitis (AIH) is a chronic inflammatory liver disease due to immune-mediated destruction of hepatocytes. The etiology of AIH involves the interaction of both genetic background and environmental triggers, which is not entirely understood. Its pathophysiological processes are believed to involve specific genetic traits, molecular mimicry, impaired immunoregulatory mechanisms, etc. . AIH is Traditional Chinese medicine (TCM) and natural products may provide some new options for the drug discovery of AIH . CostunoNetwork pharmacology was proposed by integrating network biology and polypharmacology . It is cCostunolide is a lactone compound isolated from Aucklandiae Radix. The two-dimensional (2D) structure of costunolide is shown in From SwissTargetPrediction, we got 33 potential targets, and we retrieved 174 targets from PharmMapper. After merging data, removing duplicates, and confirming in UniProt, we got 200 potential targets of costunolide. Using the search word “autoimmune hepatitis”, we obtained 190 related genes in DisGeNET and 1183 genes which score >5 in GeneCards. After merging and removing duplicates, we obtained 1252 genes related to AIH. Via intersecting targets of costunolide and AIH-related genes, we obtained 73 potential targets of costunolide in AIH b. p-value and were presented in the bubble chart (The Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was performed using The Database for Annotation, Visualization and Integrated Discovery (DAVID). The top 20 clusters were selected based on the le chart . The potp-value of Gene Ontology (GO) enrichment analysis, the top 10 significantly enriched terms in Biological Process (BP), Cellular Component (CC), and Molecular Function (MF) categories were selected  to construct the protein–protein interaction (PPI) network. After removing disconnected nodes, the network contained 61 nodes and 156 edges a. The avBased on the pathway enrichment analysis and literature review, SRC and IGF1R ranked high in the PPI network analysis and were reported to regulate the PI3K-AKT pathway in inflammation-related diseases. However, their roles in AIH were not elucidated yet. Thus, we chose SRC and IGF1R as our interested targets of costunolide in AIH. Using PyMol and Autodock, molecular docking visually showed the interaction between costunolide and SRC, IGF1R. The diagrams of drug-target binding mode were shown left and the details right . The dotFirstly, we administered costunolide in the ConA-induced acute hepatitis model. The liver gross appearance of ConA+Solvent mice showed hepatic congestion and suppuration on the surface, while ConA+COS liver showed a milder change a. In hemIn our chronic murine AIH model, the spleens of AIH mice were enlarged significantly, while costunolide suppressed it a. There + T cells and macrophages in AIH+Solvent mice, while costunolide suppressed this trend substantially  of CD4 and F4/80 in liver sections. The IHC result revealed the increased infiltration of CD4antially a,b. Based on the pathway enrichment analysis, PPI network analysis and literature review, we investigated the protein level change of phosphorylated AKT, SRC, and IGF1R in liver tissue of two AIH models. The phosphorylation of AKT, SRC, and IGF1R were significantly increased in the ConA model, whilst costunolide dramatically inhibited it . SimilarTo further confirm this trend, we conducted IHC of phospho-AKT in liver sections. The phosphorylated AKT was mainly expressed in nuclei of hepatocytes in Solvent and COS mice, and its expression level was higher in two murine AIH models, mostly in hepatocytes nuclei and cytoplasm as well as infiltrating immune cells. The phospho-AKT expression level in ConA/AIH+COS groups were lower than that in the ConA/AIH+Solvent groups c,d.Autoimmune hepatitis (AIH) is a chronic liver disease related to immunological tolerance disorders targeting hepatocytes. Although AIH has long been considered a rare disease, several studies have indicated that the incidence and prevalence of AIH were increasing worldwide . Althoug+ T cell responses, respectively [In the current study, we identified 73 targets that might participate in the effect of costunolide on AIH. Based on the KEGG enrichment pathway analysis and literature review, we speculated that costunolide might mainly restrain the disease progress of AIH through PI3K-AKT pathway. Generally, the PI3K-AKT pathway is an important intracellular signaling pathway for cell cycle progression, cell survival, and metabolism . It is rectively ,29. Simiectively . Howeverectively . Activatectively ,33,34,35ectively ,37. Seveectively ,26,38. Tectively . Interesectively . Whether+ T cell function in RA and GD [Based on the PPI network analysis using STRING and CytoHubba, we further identified 10 important targets in the therapeutic effect of costunolide in AIH, namely MAPK1, SRC, GRB2, EGFR, LCK, ESR1, JAK2, IGF1, HSP90AA1, and IGF1R, ranked by MCC. After comprehensive consideration of KEGG pathway analysis, GO enrichment analysis, molecular docking, and literature review, we selected SRC and IGF1R as our candidate targets for further research. SRC belongs to the non-receptor protein-tyrosine kinases family, playing key roles in cell growth, division, migration, and survival signaling pathways . MultiplA and GD ,48. AlthA and GD . Our res+ T cells and macrophage infiltration in liver as is shown in IHC. Based on the present literature, costunolide inhibits the production of pro-inflammatory factors in macrophages and influences the differentiation of CD4+ T cells in vitro [In this study, we found costunolide possessed a strong therapeutic effect in two AIH models. Transaminase is the sensitive indicator of the liver injury. In our research, we observed that the administration of costunolide could lower the elevated transaminase level in two murine AIH models. The change of AST level was not statistically significant in our chronic AIH model, which might be due to the relatively overall lower degree of liver inflammation. As is shown in H&E staining, the necrosis area was also diminished by costunolide in the ConA model. The spleen index (spleen weight/ body weight) could roughly reflect the degree of chronic inflammation . We founin vitro ,51. Sincin vitro . It alsoin vitro . It is win vitro . AdoptinThis study has some limitations. The binding affinity of costunolide with potential targets awaits further verification using surface plasmon resonance (SPR) or bio-layer interferometry (BLI) assays. The specific cell types in which those phosphorylated protein level increased are not identified. Since in different cell types those signaling pathways might exert distinct roles, we plan to perform immunofluorescence to reveal it. The specific molecular mechanism is not clear due to no rescue experiment being conducted. In addition, the CYP2D6 model reflects type 2 AIH. The conclusion of our study remains to be confirmed in more AIH models. https://pubchem.ncbi.nlm.nih.gov/compound/5281437#section=2D-Structure (accessed on 26 February 2022)) [The molecular and pharmacological properties data of costunolide were obtained from TCMSP  and Swisy 2022)) . SwissTay 2022))  and Phary 2022))  were utiy 2022)) .https://www.genecards.org/ (accessed on 21 June 2022)) [https://bioinformatics.psb.ugent.be/webtools/Venn/ (accessed on 13 September 2022)). AIH-related targets were collected from DisGeNET  and Genee 2022)) . In GeneHomo sapiens. Threshold and EASE were set as 2 and 0.1, respectively. GO enrichment analysis was performed using Metascape [Homo sapiens and all genes in the genome were used as the enrichment background. Min overlap, p value cutoff, and min enrichment were set as 3, 0.01, and 1.5, respectively. Bubble chart and bar graph were plotted by http://www.bioinformatics.com.cn (accessed on 14 September 2022), an online platform for data analysis and visualization. KEGG enrichment analysis was conducted using DAVID ,61. Specetascape . Specieshttps://cn.string-db.org/ (accessed on 14 September 2022)) was utilized to construct a PPI network [Homo sapiens. The minimum required interaction score was set as 0.900 (highest confidence), and disconnected nodes in the network were hidden. STRING database ( network . The orghttps://apps.cytoscape.org/apps/cytohubba (accessed on 14 September 2022)) was used to find the core subnetwork. The node’s scores were calculated and top 10 hub genes ranked by MCC were selected, then the network graph was constructed. Network visualization and analysis were performed using Cytoscape version 3.9.1 . The TSVhttps://www.rcsb.org/ (accessed on 20 September 2022)). Open-Source PyMol was used to pre-process the structure, including removing the ligand and water molecules, adding hydrogen [The crystal structures of candidate targets were obtained from the PDB database . The specific animal model establishment procedure and treatment scheme was depicted in n = 6), costunolide group , ConA group , and ConA+costunolide group . A single dose of ConA (15 mg/kg) dissolved in normal saline was injected via tail vein of mice, and the same volume of normal saline injection was used as control. Based on the existing literature, costunolide (10 mg/kg) was injected intraperitoneally once daily for three days, the first dose was given two days before giving ConA [Concanavalin A (ConA) was used to establish the acute immune-mediated liver injury model. ConA  was purchased from Sigma-Aldrich. Costunolide  was purchased from Shanghai YuanYe Bio-Technology Co., Ltd. Twenty-four male mice  were randomly divided into solvent group , costunolide group , AIH group , and AIH+costunolide group . In the COS group and AIH+COS group, costunolide (10 mg/kg) was injected intraperitoneally once daily from day 14 after the adenovirus injection continuously for 20 days. Mice were sacrificed at day 34 after adenovirus injection. The sacrifice and specimen taking procedure was similar to the ConA model described above. In addition, spleens were harvested to measure the spleen weight, and spleen index was calculated using spleen weight (mg) divided by mice weight (g). As described in our previous publication, a single dose of empty adenovirus and multiple high-pressure tail vein injections of human CYP2D6 plasmid were administered to establish the chronic AIH model . Empty aThe fixed liver tissue was embedded in paraffine and sliced at a thickness of 4 µm. H&E staining was performed to evaluate liver injury and inflammation. Afterward, all sections were graded of whole sections blindly under optical microscope (Olympus IX71) and representative pictures were imaged. Necrosis scores and inflammation scores were calculated as below: 0, no area of necrosis/immune cells infiltration; 1, very mild, few interspersed necrosis/ infiltration; 2, mild, necrosis/infiltration area ≤30%; 3, moderate, 30% < necrosis/infiltration area ≤60%; 4, severe, necrosis/infiltration area >60%. Plus, Sirius-red staining was performed to evaluate the degree of liver fibrosis in chronic AIH model. Immunohistochemistry (IHC) was performed to detect the expression of CD4, F4/80, and phospho-AKT expression in liver tissue according to protocol using SP9000 IHC kit . Primary antibodies: anti-CD4 ), anti-F4/80 ), and anti-phospho-AKT (Ser473) ) were used. Blood samples collected were centrifuged at 3000 rpm for 15 min to obtain the serum. The liver enzyme ALT and AST in serum were measured using the Rayto automatic biochemistry analyzer Chemray 420 by Wuhan ServiceBio Company .Liver tissue specimens were preserved in a −80 °C refrigerator before use. After being cut to an appropriate size, liver tissue was lysed in RIPA lysis buffer (harsh) containing protease inhibitor cocktail and phosphatase inhibitor cocktail ). Homogenizer was used to grind tissue into homogenate and sonication was performed using ultrasonic processor. After 40 min lysis, all samples were centrifuged at 12,000 rpm for 10 min. Protein concentration was measured using BCA kit ). Tissue protein (40 µg) was separated in an SDS-PAGE and was transferred to PVDF membranes. The blotted PVDF membranes were blocked with TBST containing 5% BSA at room temperature for 1 h. Then the primary antibodies were incubated overnight at 4 °C including: anti-phospho-AKT (Ser473) , anti-AKT, anti-phospho-SRC (Tyr416) , anti-SRC ), anti-phospho-IGF1Rβ (Tyr1135/1136) , anti-IGF1Rβ , anti-GAPDH ). On the next day, secondary antibodies were incubated for 1 h at room temperature. After being washed 3 times in TBST for 10 min, membranes were exposed to hypersensitive electrochemiluminescence (ECL) kit ). Protein bands were visualized on the Tanon 5200 Multi System ).t-test was performed to analyze the comparison between two groups. Welch’s correction was used if variances were not equal based on the F test. The discontinuous data were analyzed using the Mann–Whitney test. p < 0.05 was considered statistically significant. GraphPad Prism software (version 9.0.0) was utilized to analyze data. The continuous data was presented as mean ± standard deviation (SD), and the Student’s In our present study, network pharmacology and experimental validation were integrated to investigate the effect and mechanism of costunolide in AIH. According to the results, costunolide could relieve the inflammation and fibrosis in two murine AIH models, and the therapeutic effect might work by suppressing the activation of PI3K-AKT pathway and inhibiting the phosphorylation of SRC and IGF1R. Our research reveals the effect and possible mechanism of costunolide in AIH and may further contribute to novel drug development for AIH and other autoimmune diseases.


Long non-coding RNAs (lncRNAs) play an essential role in biological processes. However, the expression patterns of lncRNAs that regulate the non-Mendelian inheritance feather phenotypes remain unknown.This study aimed to compare the expression profiles of lncRNAs in the follicles of the late-feathering cocks (LC) and late-feathering hens (LH) that followed genetic rules and the early-feathering hen (EH) and early-feathering cock (EC) that did not conform to the genetic laws.We performed RNA sequencing and investigated the differentially expressed lncRNAs (DElncRNAs) between the early- and late-feathering chickens, which function by cis-acting or participate in the competing endogenous RNA (ceRNA) network.A total of 53 upregulated and 43 downregulated lncRNAs were identified in EC vs. LC, and 58 upregulated and 109 downregulated lncRNAs were identified in EH vs. LH. The target mRNAs regulated by lncRNAs in cis were enriched in the pentose phosphate pathway, TGF-β signaling pathway and Jak-STAT signaling pathway in EC vs. LC and were associated with the TGF-β signaling pathway, Wnt signaling pathway, p53 signaling pathway and Jak-STAT signaling pathway in EH vs. LH. In addition, the lncRNA-mediated ceRNA regulatory pathways of hair follicle formation were mainly enriched in the TGF-β signaling pathway, Wnt signaling pathway, melanogenesis, and calcium signaling pathways. The levels of ENSGALG00000047626 were significantly higher in the late-feathering chickens than in the early-feathering chickens, which regulated the expression of SSTR2 by gga-miR-1649-5p.This study provides a novel molecular mechanism of lncRNA’s response to the feather rate that does not conform to the genetic laws in chickens.The online version contains supplementary material available at 10.1007/s13258-022-01304-2. Moreover, the target genes of DElncRNAs were predicted, and the function and pathways were analyzed. The DElncRNAs and target genes were verified by real-time quantitative PCR (qRT-PCR). This study aimed to provide the expression profiles and underlying mechanisms of these lncRNAs affecting early and late feathers of non-Mendelian inheritance in chickens.One-day-old chicks were procured from the Sichuan Dahen Animal breeding company. As shown in Fig. The total RNA was isolated from the hair follicle samples using TRIzol reagent (Invitrogen) following the manufacturer’s instructions. The RNA integrity was detected by 1% agarose gel electrophoresis. NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific) was used to check RNA purity and concentration. First, ribosomal RNA (rRNA) was removed using an EpicentreRibo-Zero™ rRNA Removal Kit . Second, RNA-sequencing libraries were generated under the instructions provided by the NEB Next Ultra™ Directional RNA Library Prep kit for Illumina  Subsequently, the pooled libraries were sequenced on Hiseq X , using a chain-specific library construction strategy to count the number and types of lncRNAs.After discarding adapters and low-quality reads, the remaining high-quality clean reads were used for subsequent analyses. Thereafter, the clean read alignment was performed by tophat2  were identified as cis-acting target genes. The analysis of gene ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were performed by the KOBAS 2.0 server . qRT-PCR was performed using the SYBR® Green PCR Master Mix with the SYBR Green PCR Reagent Kit . In the qRT-PCR assay, each sample set three repetitions. The expression of each sample was normalized against that of GAPDH via the 2 Escherichia coli DH5α, and the transformed cells were grown on an LB plate containing kanamycin and cultured at 37 °C overnight. Single colonies were picked for PCR confirmation and sequenced using universal primers to screen for positive clones. Following this, the plasmid was extracted, and positive clones were sequenced. The cell transfection was performed using Lipofectamine™ 2000 (Invitrogen) according to the manufacturer’s instructions. The grouping was as follows: gga-miR-1649-5p/miR-NC + psiCHECK-SSTR2/psiCHECK-SSTR2-mut (Group I) and gga-miR-1649-5p/miR-NC + psiCHECK-ENSGALG00000047626/psiCHECK-ENSGALG00000047626-mut (Group II). Three parallel holes were used for each group of cells. Promega Dual-Luciferase Reporter System  was used to perform dual-luciferase assays.The potential targets were predicted by StarBase v3.0 and TargetScan and verified by a dual-luciferase reporter assay. The sequence of SSTR2 3′UTR, ENSGALG00000047626 3′UTR were obtained by complete gene synthesis . The specific restriction sites (XhoI and NotI) were added at both ends of the sequence, and the fragment was cloned into the pUC57 vector. The PCR products were then analyzed by 1% gel agarose electrophoresis and purified by the QIAquick PCR Purification Kit . The purified product and vector were digested with XhoI and NotI. In addition, the target gene fragments were inserted into a psiCHECK-2 vector . Subsequently, the ligated PCR products were transformed into 100 µL of The SPSS 20.0 statistical software  was used for statistical analysis. The data were obtained from at least three independent samples and expressed as mean ± standard deviation (SD). Student’s t-test was used for statistical comparison. The p-value < 0.05 was considered statistically significant.To study the molecular mechanisms of the non-Mendelian inheritance of feather rate phenotype, we analyzed DElncRNAs between the LC and LH that follow genetic rules vs. the EC and EH that were from the same generation and should be also late-feathered but were actually early-feathered , by RNA sequencing. The three EC samples were marked as EC-1, EC-2, and EC-3. The LC, EH, and LH groups were labeled similarly. Twelve samples were used for subsequent sequencing. A total of 1,269,214,694 raw reads and 1,225,536,374 clean reads were generated from 12 samples. Subsequently, these data were mapped to the chicken genome; the mapping ratio for EC-1, EC-2, EC-3, EH-1, EH-2, EH-3, LC-1, LC-2, LC-3, LH-1, LH-2, and LH-3 were 91.16%, 91.33%, 91.10%, 91.30%, 90.50%, 91.16%, 91.08%, 90.92%, 91.48%, 91.52%, 90.57%, and 51.54%, respectively (Supplementary Table 2).To identify the potential DElncRNAs that were involved in early- and late-feathering chickens, a comparative analysis of the expression profiles of lncRNAs in chickens was performed. A total of 96 DElncRNAs were detected in EC vs. LC, and the up- and downregulated lncRNAs were 53 and 43, respectively . The results suggested that compared with the same generation of late-feathering chickens that followed the genetic law, there were abnormal expression lncRNAs in early-feathering chickens that did not follow the genetic law. These lncRNAs might control the feather rate independently of the genetic law.To explore the function of these DElncRNAs, the cis-acting target mRNAs were analyzed with a threshold distance of 100 kb between mRNAs and lncRNAs, and 28 and 36 target mRNAs were screened in EH vs. LH and EC vs. LC, respectively. The GO term analysis revealed that these target mRNAs were implicated in the cardiac muscle tissue morphogenesis, and positive regulation of activation of JAK2 kinase activity in EC vs. LC  networks in the modulation of feather rate phenotype, we constructed the lncRNA-miRNA-mRNA ceRNA regulatory network Fig. . In the We performed GO and KEGG analyses to investigate the function and pathway of DElncRNAs. GO enrichment analysis showed target mRNAs focused on cell fate commitment and adenylate cyclase-inhibiting G-protein-coupled receptor signaling pathway in EC vs. LC , and participated in G-protein-coupled receptor signaling pathway, oligopeptide transmembrane transport, and cell adhesion in EH vs. LH . KEGG analysis revealed that the mRNAs in the ceRNA networks were associated with the calcium signaling pathway, TGF-β signaling pathway, and Wnt signaling pathway in EC vs. LC , and participated in steroid biosynthesis, histidine metabolism and adipocytokine signaling pathway in EH vs. LH . Interestingly, the KEGG pathway enrichment analysis showed that both groups were enriched in neuroactive ligand-receptor interaction, SNARE interactions in vesicular transport and melanogenesis pathway.To screen for lncRNAs regulating feather rate phenotype, we performed qRT-PCR in potential DElncRNAs. We selected three DElncRNAs , which were differently expressed in EH vs. LH and EC vs. LC. Results showed that the level of ENSGALG00000047626 was significantly higher in LC than in EC, and was remarkably increased in LH relative to EH (Fig. The prediction results of the TargetScan showed that gga-miR-1649-5p was likely to bind to ENSGALG00000047626 and SSTR2. To verify this, we carried out a dual-luciferase reporter assay. The results demonstrated that gga-miR-1649-5p significantly suppressed the luciferase activity of psiCHECK-SSTR2, whereas it did not affect the luciferase activity of psiCHECK-SSTR2-mut (Fig. Sex identification is a feasible and vital strategy for breeding chickens commercially (Kreuzer et al. Among the ceRNA regulatory pathways, we found a series of mRNAs that play crucial roles in the feather rate phenotype. KEGG enrichment analysis demonstrated that target mRNAs participating in the ceRNA network were mainly enriched in the Wnt signaling pathway, TGF-β signaling pathway and calcium signaling pathway. The Wnt/β-catenin pathway regulates pluripotent stem cell differentiation, organ development, and regeneration (Pang et al. This study revealed the differential expression pattern of lncRNAs between the early-feathering chickens that followed the genetic rules and the late-feathering chickens that did not follow the genetic rules. Multiple cis-target mRNAs of the DElncRNAs were enriched in the TGF-β signaling pathway and Jak-STAT signaling pathway. Moreover, we established the lncRNA-miRNA-mRNA ceRNA regulatory network. Our results provide novel insights into feather rate phenotype in chickens.Below is the link to the electronic supplementary material.Supplementary Material 1Supplementary Material 2Supplementary Material 3Supplementary Material 4Supplementary Material 5Supplementary Material 6