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ORIGINAL ARTICLE Table of Contents  
Ahead of print publication
Study on quality markers and action mechanisms of inulae flos on anti-hepatitis through network pharmacology and high-performance liquid chromatography fingerprints


 Chinese Materia Medica Processing Laboratory, College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing 210023, China

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Date of Submission29-Mar-2021
Date of Acceptance21-Jul-2021
Date of Web Publication25-May-2022
 

  Abstract 


Objective: The objective of the study is to combine network pharmacology with high-performance liquid chromatography (HPLC) to screen for quality markers (Q-markers) of Inulae Flos and predict mechanism on anti-hepatitis. Materials and Methods: Active ingredient library of Inulae Flos is structured using databases and the literature. “Compound-target-pathway” network on anti-hepatitis and protein–protein interaction (PPI) network are constructed using network pharmacology. Next, chromatographic fingerprints of Inulae Flos in 7 origins are obtained through HPLC, and chemometric analysis is implemented to identify chemical markers, which is combined with network pharmacology to identify Q-markers and detect content. Results: 1,6-O, O-Diacetylbritannilactone, Ivangustin, and Inulanolide A are key ingredients of Inulae Flos to interact with 82 potential targets related to anti-hepatitis. Furthermore, signal transducer and activator of transcription 3, tumor necrosis factor, interleukin-6, and transcription factor AP-1 are the core targets in the PPI network. Chromatographic fingerprints of the Inulae Flos define 20 common peaks and identify 8 peaks using reference substances. Through partial least square discriminant analysis, 7 compounds including caffeic acid, chlorogenic acid, and 1,6-O, O-Diacetylbritannilactone were main chemical markers for variability. 1,6-O, O-Diacetylbritannilactone is both a key ingredient and exclusive chemical marker. Therefore, 1,6-O, O-diacetylbritannilactone is a Q-marker of Inulae Flos, and the average content is 1.82 mg/g. Conclusion: 1,6-O, O-diacetylbritannilactone is determined to be a Q-marker of Inulae Flos.

Keywords: Hepatitis, high-performance liquid chromatography fingerprint, Inulae Flos, network pharmacology, quality marker


How to cite this URL:
Lin L, Su LL, Li HH, Ma CQ, Ji D, Xie H, Lu TL. Study on quality markers and action mechanisms of inulae flos on anti-hepatitis through network pharmacology and high-performance liquid chromatography fingerprints. World J Tradit Chin Med [Epub ahead of print] [cited 2022 Aug 8]. Available from: https://www.wjtcm.net/preprintarticle.asp?id=345930





  Introduction Top


Natural products are significant sources of new drugs and have advantages in the precaution and therapy of diseases[1] and possess the characteristics of multi-components and multi-targets;[2],[3],[4] however, quality control remains a significant challenge.[5] Therefore, to improve the quality standard system, the concept of quality marker (Q-marker) was proposed to standardize quality control.[5],[6],[7]

Hepatitis is an infection that causes inflammation of the liver,[8] which is a major global health challenge with increasing disease burden.[9] It has a high seasonal incidence in autumn and winter, can be associated with epidemics, and occurs at any age. Recent widespread outbreaks of hepatitis related to foodborne and ongoing person-to-person exposure have resulted in substantial morbidity and mortality rates.[10],[11],[12] The liver plays an essential role in the body and is the main metabolic organ, which has physiological functions such as producing and excreting bile, resisting pathogen, and detoxification. The progression of hepatitis to associated cirrhosis and further progression to hepatocellular carcinoma (HCC) is a natural disease. Therefore, the prevention of cirrhosis and HCC is an important therapeutic objective for hepatitis. Recently, drug treatments are the available interventions for hepatitis.

The dried aerial part extract of Inulae Flos has chemical complexities, such as terpenes, while flavonoids and other active compounds[13],[14],[15] have diverse biological effects on anti-diabetes, anti-tumor,[16] anti-oxidative,[17] and anti-inflammatory activities. It is often used clinically to treat bronchitis, hepatitis, obesity, etc.[18],[19] Modern studies have demonstrated that Inulae Flos is rich in sesquiterpene lactones, which is essential an ingredient of Inulae Flos primarily comprising japonicones and neojaponicones.[13],[20],[21] Sesquiterpene lactones contribute to inflammatory reactions, such as oxidative phosphorylation in neutrophils,[22] migration of lymphocytes, and secretion of histamine, serotonin, and proinflammatory cytokines.[23] Hence, Inulae Flos has a certain research significance in the treatment of hepatitis; however, its mechanism remains unclear.

Network pharmacology is a systematic approach. Based on existing biological data, it builds on an ideal paradigm “disease-gene-target-drug” to identify potential drug targets and achieve comprehensive insights into the therapeutical mechanism of multi-compound herbs.[24] Public availability of pharmacology platforms and other bioinformation databases achieves the combination of absorbable bioactive compounds and network pharmacology and applies the research strategy of pharmacology-based traditional Chinese medicine (TCM). Hence, network pharmacology, high-performance liquid chromatography (HPLC) fingerprints combined with chemometrics, and representative component determination are adopted to identify and validate the Q-marker, to ensure the efficacy of TCM.[7]

This study screened active ingredients of the Inulae Flos, “compound-target-pathway” network and protein–protein interaction network using network pharmacology. The study develops chromatographic fingerprints of Inulae Flos in 7 regions through HPLC and adopts chemometric analysis to identify chemical markers that make significant differences among 35 batches of Inulae Flos. Eventually, by combining chemical markers with the “compound-target-pathway” network, this study preliminarily explores the Q-markers of Inulae Flos in [Figure 1], including the action mechanism in the treatment of hepatitis and provides a theoretical basis for further medicinal materials and experimental research.
Figure 1: Entire framework of quality markers discovery of Inulae Flos

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  Materials and Methods Top


Chemicals, reagents, and materials

Standard compounds of 1,6-O, O-Diacetylbritannilactone and Ivangustin were purchased from Wuhan ChemFaces Biochemical Co., Ltd (Wuhan, China). Standard compounds of 1,5-dicaffeoylqunic acid, Taxifolin, Rutin, and Chlorogenic acid were purchased from Shanghai Source Leaf Biotechnology Co., Ltd (Shanghai, China). Standard compounds of Caffeic acid and Quercetin were purchased from the National Institutes for Food and Drug Control (Beijing, China). The purity of all standards was 98%. Acetonitrile (HPLC grade) and phosphoric acid (HPLC grade) were purchased from Merck Drugs & Biotechnology (Germany), except formic acid, which was purchased from Sinopharm Chemical Reagent Co., Ltd. (Shanghai, China). Ultra-pure water was prepared using an LL-40H purification system (Lead R&D Hi-end Water Treatment Equipment Co., Ltd., Chongqing, China). Inulae Flos were obtained from Tianjin China Medico Technology Co., Ltd (Tianjin, China). The specific information of the 35 batches is presented in [Table 1]. The plants were identified by Professor Jian-wei Chen from the Nanjing University of Chinese Medicine.
Table 1: Informations of Inulae Flos

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Establishment of active ingredient database for Inulae Flos

To holistically understand the characteristics of Inulae Flos, the entire compounds of Inulae Flos were screened out based on the TCM Systems Pharmacology Database and Analysis Platform (TCMSP; http://ibts.hkbu.edu.hk/LSP/tcmsp.php),[25] TCM Integrated Database (TCMID, http://tcm.cmu.edu.tw/),[26] Bioinformatics Analysis Tool for Molecular Mechanism of TCM (BATMAN-TCM, http://bionet.ncpsb.org/batman-tcm/), and wide-scale literature mining. The final database of the active ingredients of Inulae Flos was tentatively screened out, using the parameters related to the pharmacokinetic properties of the compound provided by the TCMSP database.

Target set acquisition of Inulae Flos in treatment of hepatitis

The molecular structure of compounds was obtained from the NCBI PubChem database (http://www.ncbi.nlm.nih.gov/pccompound).[27] The selected structures were saved as the mol format for the target prediction. The targets of all the active ingredients of Inulae Flos were matched from TCMSP, BATMAN-TCM, Swisstargetprediction (http://www.swisstargetprediction.ch/), and the binding database (BindingDB, http://www.bindingdb.org/bind/index.jsp). Nevertheless, according to the target databases of therapeutic target database (TTD),[28] GeneCards (https://www.genecards.org/), and DisGeNet (https://www.disgenet.org/search),[29] targets that could be used to treat hepatitis, were summarized and concluded in this paper. Subsequently, the target set with potential anti-hepatitis Inulae Flos targets was obtained by adopting the above targets to map the targets of active ingredients. In addition, UniProt (https://www.uniprot.org/) was employed to standardize target genes that qualified material species as “Homo sapiens.”

Construction of network based on network pharmacology

The target genes were imported into the Database for Annotation, Visualization and Integrated Discovery (DAVID, https://david.ncifcrf.gov/),[30] which provided gene ontology (GO) term enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG)[31] to account for pathways. The P value was negatively correlated with relevance, and a threshold of P < 0.05 was regarded as an obvious discrepancy. Take P < 0.05 as the filter condition with statistical difference, potential targets that were useful for Inulae Flos to treat hepatitis obtained GO enrichment information from three aspects: biological processes, molecular function, and cellular component. Through the salient analysis of discrete distribution, KEGG obtained the classification of pathways related to experimental purpose. Take P < 0.05 as the parameter for obtaining the KEGG pathways in the treatment of hepatitis. Accordingly, the “compounds-targets-pathways” network was constructed by adopting Cytoscape 3.6.1. STRING database (https://string-db.org/cgi/input.pl) was employed to obtain the protein–protein interaction (PPI) network data of the target set, and a visual PPI network diagram was constructed using the Cytoscape software. PPI network can be used to identify important pharmacodynamic targets of Inulae Flos in the treatment of hepatitis and provide novel research directions for future experimental verification.

Preparation of standard and sample

All the dried Inulae Flos extracts were pulverized and filtered through a 80-mesh sieve. The dried Inulae Flos extract powder (1.0 g) was extracted with 30 mL of a 70% methanol solution using an ultrasonic extraction apparatus (40 kHz, 500 W) for 60 min. The extracts were centrifuged at 12000 rpm for 10 min, and the supernatant was adopted for HPLC analysis.

Appropriate amounts of reference standards for 1,6-O, O-diacetylbritannilactone ivangustin, 1,5-dicaffeoylqunic acid, Taxifolin, Rutin, Chlorogenic acid, Caffeic acid, and Quercetin were weighed, and each of these standards was diluted with 70% methanol solution at a concentration of 1.58 mg/mL for 1,6-O, O-diacetylbritannilactone, 1.43 mg/mL for ivangustin, 99.3 mg/mL for 1,5-dicaffeoylqunic acid, 0.354 mg/mL for Taxifolin, 4.19 mg/mL for Rutin, 1.11 mg/mL for chlorogenic acid, 0.078 mg/mL for Caffeic acid, and 0.776 mg/mL for Quercetin. Subsequently, a mixed solution containing all eight reference compounds was prepared.

Qualitative analysis of Inulae Flos via high-performance liquid chromatography

The HPLC fingerprint of Inulae Flos from 7 regions was built using the Agilent 1260 Infinity L.C. system (Agilent Technologies, USA), comprising an autosampler, a column oven, and a photodiode array detector. Chromatographic separations were performed on the Dubhe C18 column (4.6 mm × 150 mm, 5 μm), and the mobile phase consisted of 0.05% phosphoric acid solution (A) and acetonitrile (B) with the following gradient elution: 0–45 min, 10–25% (B); 45–50 min, 25–30% (B); 50–85 min, 30–40% (B); 85–90 min, 40–10% (B). The detection wavelength of DAD was set at 205 nm, flow rate was 1.0 mL/min, column temperature was maintained at 30°C, and the injection volume was 10 μL. A similarity analysis was performed to obtain common peaks of 35 batches of Inulae Flos, using the similarity evaluation system of chromatographic fingerprint of TCM 2012, and they were identified by comparisons with reference substances. To better observe the differences between 35 batches of Inulae Flos, data of samples were imported into the SIMCA software, and supervised mode was selected to perform partial least squares discriminant analysis (PLS-DA) and observe the natural aggregation of Inulae Flos. Subsequently, based on the variable importance in the projection (VIP), the variable with a larger VIP value has contributes more to the classification. Take VIP > 1 as the parameter to screen out the main chemical markers that triggered difference between the groups. Finally, combined “compounds-targets-pathways” network and chemical markers obtained from HPLC and chemometrics, and Q-markers of Inulae Flos were predicted.

Quantification of Q-markers in Inulae Flos by high-performance liquid chromatography

The detectability of potential Q-markers was tested and the absolute quantified by HPLC. In total, 35 batches of Inulae Flos were copied 3 in parallel to prepare the test solution according to the method under Section 2.5, they were measured according to the chromatographic conditions under Section 2.6. Then, the peak areas of the Q-markers were recorded, and the content was calculated.


  Results and Discussion Top


Construction of “compounds-targets-pathways” network

Active ingredient database of Inulae Flos

Based on TCMSP, ADME-related properties of Inulae Flos were thoroughly investigated. Drug likeness (DLs) is an important drug research parameter used to evaluate whether a compound functions as a drug. In the screening process, DL ≥ 0.14 was defined as the filter condition, combined with BATMAN-TCM, TCMID, and the literature, and we collected 46 compounds considered as pharmacologically active ingredients in [Figure 2]a. In this study, 12 of these active ingredients, which were exclusive compounds of Inulae Flos on TCMSP [Figure 2]a, influenced anti-inflammatory activities, including 1,6-O, O-diacetylbritannilactone and ivangustin.
Figure 2: (a) “Compounds-targets-pathways” network of Inulae Flos; (b) gene ontology analysis of putative target genes; (c) Protein-protein interaction network of Inulae Flos

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Target set prediction related to Inulae Flos in the treatment of hepatitis

Potential targets of active ingredients were obtained from TCMSP, BATMAN-TCM, Swisstargetprediction, and BindingDB, mapped to targets of hepatitis from TTD, GeneCards, and DisGeNet to acquire the target set of Inulae Flos for treating hepatitis. We employed UniProt to identify the gene names and numbers of all targets and standardize target genes as “Homo sapiens.” In total, as illustrated in [Figure 2]a, 82 candidate target genes were identified as targets of active ingredients of Inulae Flos in the treatment of hepatitis.

Gene ontology, Kyoto Encyclopedia of Genes and Genomes analysis and network construction

The obtained 82 target genes were imported into DAVID to conduct GO and KEGG enrichment analyses. Targets were distributed in 24 KEGG pathways (P < 0.05, False Discovery Rate (FDR) < 0.05), thereby exhibiting an impressive functional association with various signal and inflammatory-related pathways, such as inflammatory bowel disease (IBD), which are highly correlated to target genes, influenza A, pathways in cancer, Chagas disease (American trypanosomiasis), and other pathways presented in [Figure 2]a.

GO analysis comprised biological pathways, molecular functions, and cellular components. A total of 68 GO terms (P < 0.05, FDR < 0.05) were obtained, and biological process categories accounted for the largest proportion. This indicated that the targets mainly were associated with the positive regulation of transcription from the RNA polymerase II promoter, response to drugs, enzyme binding, positive regulation of the nitric oxide biosynthetic process, positive regulation of transcription, DNA-templated, etc. In the cellular components, the membrane accounted for the largest proportion. In the molecular function, enzyme binding and RNA polymerase II transcription factor activity and ligand-activated sequence-specific DNA binding were highly correlated, as illustrated in [Figure 2]b. [Figure 2]b is presented with the top ten terms on each category, in order of enrichment score.

A “Compounds-targets-pathways” network with 140 nodes and 1101 edges was constructed using Cytoscape 3.6.1, and it exhibited the integral regulation of Inulae Flos in the treatment of hepatitis [Figure 2]a and provided the theoretical basis for predicting potential targets of Q-markers. The network elucidated the action mechanisms of the active ingredients of Inulae Flos in treating hepatitis, including its related targets and pathways. The more targets contained in the pathway, the more likely Inulae Flos can play a role in this pathway. Among them, there were 3 pathways with more than 13 genes, including pathways in cancer, influenza A, and Chagas disease. After the calculations and analyses, it can be observed that there were 10 compounds with the target number greater than 18, of which ivangustin, 1,6-O, O-diacetylbritannilactone, and inulanolide A, were the exclusive components of Inulae Flos for the treatment of hepatitis. The green hexagons and yellow rectangles correspond to pathways that target genes, the blue, and red ellipses correspond to the active ingredients, and the red ellipses represent exclusive compounds of Inulae Flos.

Protein–protein interaction network construction

The STRING database is a functional protein association network. We uploaded the aforementioned 82 target genes to the STRING platform (score ≥ 0.9) to obtain protein–protein interactive data that comprised 82 nodes and 220 edges. Using the double median of the degree value and closeness centrality, 17 core targets were screened out, and the PPI network was established using Cytoscape 3.6.1 [Figure 2]c. The color of the node represented the size of the degree, the color of the node from yellow to red indicated a higher degree, the combined score was higher, and the line of the edge was thicker. The PPI network demonstrated that the activator of transcription 3 (signal transducer and activator of transcription 3 [STAT3], D = 20) exhibited the highest degree, followed by the tumor necrosis factor (TNF, D = 20), interleukin-6 (Il6, D = 19), and transcription factor AP-1 (JUN, D = 18), which played significant roles in the network among these 82 targets.

High-performance liquid chromatography fingerprint establishment and chemical compounds identification

As illustrated in [Figure 3]a, the chromatographic fingerprints were matched with the similarity evaluation system of chromatographic fingerprint of TCM 2012. In addition, 20 peaks were extracted as characteristic common peaks, and the similarity of 35 batches of Inulae Flos from 7 regions was above 0.95, except Gansu, which was above 0.88 [Table 1] after the similarity computation. Based on a comparison with available standard compounds, Chlorogenic acid (6), Caffeic acid (8), Rutin (9), Taxifolin (10), 1,5-O-dicaffeoylqunic acid (12), 1,6-O, O-diacetylbritannilactone (16), Quercetin (17), and Ivangustin (20), including 8 compounds were identified, and a common pattern feature map was generated for Inulae Flos [Figure 3]b and [Figure 3]c. Different relative peak areas of common peaks indicated that Inuale Flos from different regions had the same ingredients; however, their contents exhibited discrepancies. Combined with PLS-DA, model fitting parameters R2X = 0.876, R2Y = 0.976, and model prediction parameters Q2 = 0.971 were all greater than 0.5, thereby indicating that the established mathematical model was stable and had strong predictive abilities. The PLS-DA score matrix is presented in [Figure 4]a in which 35 samples were clustered into 4 categories. Then, combined with VIP, which achieved main markers that caused differences between the groups, seven peaks with large VIP values (VIP >1) and contribution rates were selected as the chemical markers in [Figure 4]b. In order of VIP size, they were Caffeic acid (peak 8), peak 5, Chlorogenic acid (peak 6), 1,6-O, O-diacetylbritannilactone (peak 16), peaks 3, 15, and 2. These chemical markers played important roles in distinguishing Inulae Flos from different regions.
Figure 3: (a) Fingerprints of 35 Inulae Flos batches; (b) Chromatogram of reference Inulae Flos fingerprints; (c) Chromatogram of reference substances

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Figure 4: (a) Partial least squares discriminant analysis of score plot for 35 Inulae Flos samples; (b) variable importance in the projection value of 20 chromatographic peaks of Inulae Flos samples; Group 1: Gansu; Group 2: Jiangsu; Group 3: Shandong, Hebei; Group 4: Henan, Zhejiang, Anhui

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Combined with the “compound-target-pathway” network, 1,6-O, O-diacetylbritannilactone was one of top 10 active ingredients that had more predictive targets and was an important compound for Inulae Flos's pharmacological effects, as it acted on inflammation-related pathways to exert anti-hepatitis effects. Simultaneously, 1,6-O, O-diacetylbritannilactone was an exclusive, common, and main compound that caused differences between 35 batches of Inulae Flos in 7 regions. Existing literature demonstrated that 1,6-O, O-diacetylbritannilactone was isolated from Inulae Flos, and reduced leukotriene C4 production and degranulation, as well as phospholipase Cγ-mediated Ca2+ influx in bone marrow-derived mast cells for anti-inflammatory activities.[32] 1,6-O, O-diacetylbritannilactone possessed the most anti-inflammatory effect through the suppression of nuclear factor kappa B (NF-κB) nuclear translocation and activity enhancement of cellular penetration.[33] 1,6-O, O-diacetylbritannilactone[34],[35],[36] is valuable for treating various inflammatory diseases; hence, it was chosen as a potential Q-marker for Inulae Flos.

Quantification of Q-marker- 1,6-O, O-diacetylbritannilactone

The content of bioactive compounds in Inulae Flos was significant for its therapeutic effects. To test the practicability and universality of the developed method, the standard reserve solution of 1,6-O, O-diacetylbritannilactone was diluted in five appropriate concentrations, and each concentration was tested thrice. The sample exhibited good linearity (R = 0.9998); in addition, the limit of detection and limit of quantitation values were all below the level of the sample [Table 2]. Relative standard deviation values of intraday and interday precisions, repeatability, and mean recoveries are presented in [Table 3].
Table 2: Calibration Curve, linear range and correlation coefficient of Q-marker

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Table 3: Precision, repeatability, stability, and recovery results of Q-marker

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The 1,6-O, O-diacetylbritannilactone content of 35 samples is shown in [Table 4]. The contents in samples from different regions varied significantly. The average content of 35 batches of Inulae Flos was 1.82 mg/g, the mass fraction of 1,6-O, O-diacetylbritannilactone of Inulae Flos reached 0.120–3.935 mg/g from 7 regions, the region with the highest content was in Hebei, and the lowest was in Anhui. Significant differences were observed for the same Inulae Flos from different regions. Notably, the OB and DL of 1,6-O, O-diacetylbritannilactone were calculated to be 39.03% and 0.31 on TCMSP.
Table 4: Content of 1,6-O, O-Diacetylbritannilactone in 35 batches of Inulae Flos (n=3)

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  Conclusions Top


As a Chinese herbal medicine, Inulae Flos was demonstrated to have therapeutic benefits against chronic diseases, especially inflammation-like hepatitis.[13],[37] Modern studies have established that the active ingredients of Inulae Flos are sesquiterpenoids, which exhibit the potent inhibition of NF-κB activity and oxidative phosphorylation in neutrophils and other reactions to exert anti-inflammatory effects;[17],[38],[39] hence, it was necessary to filter potential active ingredients related to therapeutic effects and evaluate the quality of Inulae Flos. Owing to the numerous and complex chemical constituents of Inulae Flos, quality control has been a major obstacle hindering drug availability. In this study, the Q-marker concept, combined with network pharmacology, was proposed to guide TCM quality investigations, which further elucidated the therapeutic effects and mechanism of Inulae Flos.[40]

As illustrated in [Figure 2]a, 46 bioactive ingredients were screened out, 12 of them were exclusive ingredients of Inulae Flos from databases and the literature and were highlighted in red. In addition, 82 targets related to Inulae Flos in the treatment of hepatitis were successfully screened out. To establish the network and elucidate the mechanism of hepatitis treatment holistically, regulated target genes conducted enrichment analysis. KEGG pathways suggested that these targets were primarily associated with the IBD, influenza A, pathways in cancer, Chagas disease, etc. Therefore, the ingredients and targets of Inulae Flos were mainly related to biological processes, regulated the cell cycle, and responded to drug.

In total, 10 compounds had a degree value of D ≥18 and were called nuclear compounds, thereby implying that most of the compounds regulated multiple targets to exert various therapeutic effects, and these results correspond to those of existing pharmacological studies. Meanwhile, 1,6-O, O-diacetylbritannilactone, ivangustin, and inulanolide A, which were both exclusive, active, and nuclear compounds of Inulae Flos, were the potential Q-markers.

The PPI network indicated that four targets were potential core targets, including STAT3, TNF, interleukin-6, and JUN, which were closely interacted with proteins. As a pleiotropic cytokine, TNF played a critical role in apoptosis, inflammation, and immune responses.[41],[42] Studies revealed that PPAR directly bound the DR10PPRE site of the A2AR gene promoter region to upregulate the expression of A2AR protein and activate the A2AR-PKA pathway; hence, it up-regulated the expression of PPAR protein and further completed its inhibitory effect in the inflammatory response. Studies demonstrated that a reduction of phosphorylation in JAK2 and STAT3 proteins decreased the total levels of JAK2 and STAT3 proteins, inhibited the release of pro-inflammatory factors, and increased the release of anti-inflammatory factors to play an anti-inflammatory role. As presented in the network, 5 key targets were screened by a double median degree value of 10, including prostaglandin G/H synthase 2 (PTGS2, D = 30), which exhibited the highest degree. Androgen receptor (D = 29), cytochrome P450 19A1 (D = 26), ATP-dependent translocase ABCB1 (D = 21), and glycogen synthase kinase-3 beta (D = 20), which highly correlated with active compounds and pathways, were mainly effective targets when the Inulae Flos worked on hepatitis. Furthermore, in combination with the PPI network, PTGS2 was the key and core target.

For further verification of the potential Q-markers predicted by the Network pharmacology, the HPLC method was established to analyze the chemical compounds of Inulae Flos from seven regions. As a means of quality evaluation and control, it exhibits the characteristics of convenience, rapidity, and comprehensiveness. Eight compounds were identified successfully, including 1,6-O, O-diacetylbritannilactone, ivangustin, 1,5-dicaffeoylqunic acid, Taxifolin, Rutin, Chlorogenic acid, Caffeic acid, and Quercetin. Subsequently, based on PLS-DA and VIP, 7 compounds were verified as chemical markers that played important roles in distinguishing discrepancies between 35 batches of Inulae Flos. Three chemical markers were identified, which include 1,6-O, O-diacetylbritannilactone, Caffeic acid, and Chlorogenic acid.

As demonstrated in the results of network pharmacology and VIP, 1,6-O, O-diacetylbritannilactone was one of the three exclusive nuclear compounds in Inulae Flos that exhibited bioactivity in treating hepatitis, which belong to sesquiterpenoids that influenced the mechanisms of chemotaxis, migration of lymphocytes, and secretion of histamine, serotonin, and proinflammatory cytokines.[16],[39],[43] In addition, 1,6-O, O-diacetylbritannilactone was one of the chemical markers that triggered differences between 35 batches of Inulae Flos from 7 regions, and the content of 1,6-O, O-diacetylbritannilactone reached 0.120–3.935 mg/g.

In summary, by combining the Q-marker with network pharmacology, our study determined 1,6-O, O-diacetylbritannilactone to be the Q-marker of Inulae Flos on anti-hepatitis. The integrated network pharmacology was suitable to screen out targets and predict potential Q-markers. Furthermore, 1,6-O, O-diacetylbritannilactone was inferred to be an active compound that influences multi-targets and multi-pathways to anti-hepatitis. This is the basis for further research on Inulae Flos, as an integrated demonstration of the Q-marker still requires intense future investigation.

Acknowledgments

This work was sponsored by National Key Research and Development Program of China (2018YFC1707000) and the Project of the Industry University Research Cooperation and transformation of scientific and technological achievements in Qixia District of Nanjing.

Author contributions

All authors made substantial contributions to the conception and design, analysis, and interpretation of data, including drafting or revising the article, and agree to be accountable for all aspects of the the work.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
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Correspondence Address:
Hui Xie,
College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing 210023
China
Tu-Lin Lu,
College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing 210023
China
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/wjtcm.wjtcm_1_22



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