Potential Molecular Mechanisms and Metabolic Networks in Red Ginseng-induced “ Shanghuo ” (上火)

Abstract

Objective: To comprehensively uncover potential molecular mechanisms and metabolic networks in RG-induced “Shanghuo”. Red ginseng (RG) could bring out the manifestations of “Shanghuo”, which mostly presents as redness, swelling, fever, and pain. Methods: The compounds of RG were obtained from the TCMSP and SymMap databases. The putative targets of RG were determined based on the obtained compounds by STITCH. The potential targets of “Shanghuo” were retrieved from the literature. Those interacted targets of RG and “Shanghuo” were screened by STRING and conducted networks of RG and “Shanghuo”. The RG-influenced “Shanghuo” targets were further analyzed by the STRING and proved by molecular docking. Afterwards, water extract of RG was given to 6 weeks-old rats for 15 days. Observations were carried out to confirm the establishment of “Shanghuo” model. Gas chromatography-mass spectrometry (GC-MS) were utilized to identify the differential metabolites. Results: Apolipoprotein B and Serum albumin (ALB) were the co-acting targets, while Transient Receptor Potential Channel Vanilloid 1 was a vital target of RG jointing “Shanghuo” and RG together through the connection via ALB. Ginsenoside Rb1 was the most influential compound of RG to induce “Shanghuo” by molecular docking. Our study indicated that fat digestion and absorption and cholesterol metabolism the potential mechanism of RG-induced “Shanghuo”. An acceleration of energy expenditure in the “Shanghuo” group was additionally verified by conducting the GC-MS method. Conclusion: The disorders in heat dissipation along with the accelerated fat metabolism and overactive energy expenditure might contribute to RG-induced “Shanghuo”.

Introduction

From the Chinese medicine point of view, “Shanghuo” (上火) could be induced by heat natured food and herbs, manifesting as “redness, swelling, fever, and pain” as well as ulcer in the skin and mucosa of the head and facial part, like mouth, tongue, gum gingiva, throat, nose and eyes. ¹ “Shanghuo” becomes increasingly concerned because some “Shanghuo” related diseases like recurrent aphthous stomatitis might be a precursor or risk factor for specific cancers. ² As a health supplement, red ginseng (RG), the steamed root and rhizome of Panax ginseng C. A. Meyer, is continuously popular among Asians even worldwide. Prior research demonstrated that RG could give rise to “Shanghuo”.^3–5 However, a pharmacological network of “Shanghuo” and RG remains to be clarified. Network pharmacology has been applied to Chinese medicine to analyze multi-target compounds acting in biological networks to probe multiple molecular mechanisms. ⁶

Even though some serum biomarkers in “Shanghuo” have been identified by our research team,^7,8 the network of “Shanghuo” and RG has not been established before. The method of systems pharmacology characterized with the systemic network targets provides a new perspective for the analysis of complex diseases such as “Shanghuo”. Data from our study of the systems pharmacology strongly suggest that RG-induced “Shanghuo” is closely related to an overactive fat metabolism but this was not investigated in our previous study. ⁹ The gas chromatography-mass spectrometry (GC-MS) metabolomic approach is particularly well-suited for the study of fat metabolism. Therefore, we again utilized GC-MS to analyze serum metabolite changes in the animal model to confirm the results from the systems pharmacology and further validating our conclusions from the prior clinical trial, as displayed in Figure 1. The current study aims to combine systems pharmacology with in vivo experiments to analyze the potential mechanisms of RG-induced “Shanghuo”.

Figure 1.

Work-flow diagram of the study.

Materials and Methods

Active Compounds Screening and Putative Targets Prediction of RG

The compounds of RG were retrieved from TCM Systems Pharmacology Database and Analysis Platform (TCMSP, http://tcmspw.com/tcmsp.php) ¹⁰ and SymMap (https://www.p.org/). ¹¹ Based on the compounds with the species limited as “Homo sapiens”, all of the putative targets were obtained from STITCH database (http://stitch.embl.de/). ¹² The STITCH database currently covers 9′643′763 proteins from 2′031 organisms. The predicted targets of RG with medium confidence were preserved for further analysis. Both of the duplications and unified names were removed. The top 6 compounds with the most number of connected targets in the RG network were regarded as central compounds in RG.

Collection of the “Shanghuo” Targets

A comprehensive search was conducted in “Web of Science”, “CNKI” (www.cnki.net/), “WANFANG DATA” (www.wanfangdata.com.cn/index.html) and “VIP” (www.cqvip.com/) for all literature with the keyword “Shanghuo”. Those targets with human Uniprot ID were considered “Shanghuo” targets.

Network Construction and Pathway Enrichment Analysis

To investigate the associations between “Shanghuo” and RG, we acquired the protein associations network from STRING (https://string-db.org/) with a combined score ≥ 0.4. ¹³ Then we maintained those associations that only linked proteins from “Shanghuo” targets with those from RG targets and displayed the network by Cytoscape 3.7.1. ¹⁴ Lastly, we used STRING to perform the pathway enrichment analysis for explaining the biological meaning of the “Shanghuo” targets influenced by RG and the RG targets that have impact on “Shanghuo”.

Molecular Docking

The common targets of “Shanghuo” and RG were imported into the Research Collaboratory for Structural Bioinformatics Protein Data Bank (RSCB PDB) (https://www.omicshare.com) database to obtain the protein composition in PDB format. Crystal of proteins was forwarded to Autodock vina (version 1.2.0) and MglTools (version 1.5.6) software to conduct the molecular docking. The high-quality 3D structures of small molecules in RG and the common proteins were exhibited by LIGPLOT + (version 2.2) software and PyMOL (version 2.5).

Preparation of RG Water Extract

RG (Brand: Korean Red Ginseng, Origin: Korea, NO: JY20150235) was purchased from Zhejiang INT’L group, which has been certified as the qualified RG by high-performance liquid chromatography in the earlier trial. The 450g RG was immersed with a 10-fold volume of the distilled water for 0.5 h and decocted twice for 1.5 h, each followed by filtration. The filtrates were combined and concentrated by a rotary evaporator as RG water extract (RG-WE).

Animals

Twenty female Wistar rats in 6 weeks, weighing 160 ± 20 g, were provided by Shanghai Sippr-BK Laboratory Animal Co. Ltd (Shanghai, China; certification number: SCXK-HU2013-0016) and housed in the animal experimental center of Zhejiang Chinese Medical University (Hangzhou, China; certification number: SYSK-ZHE 2018-0012). The rats were kept in individual cages at a constant temperate (20°C), relative humidity (40%-60%), a 12 h light/dark circle and with free access to food and water. All rats were acclimated for 7 days before the establishment of the model. All experimental procedures were conducted in accordance with the Regulations of Experimental Animal Administration, published by the State Committee of Science and Technology of China and were approved by the Animal Ethics Committee of Zhejiang Chinese Medical University (approval number: ZSLL-2016-140).

Grouping and Drug Administration

The rats were randomly divided into 2 groups (n = 10 per group): control group and “Shanghuo” group (0.27g mL-1). The dose of the “Shanghuo” group was calculated through the equivalent dose ratio of human to rat according to body surface area. ¹⁵ The RG dose was 10 times the dose of our previous clinical trial, 3 g. The “Shanghuo” group was administrated with 2 mL RG-WE for 15 days. The control group was administrated with the same volume of saline solution for 15 days.

Observation of the Weight, Rectal Temperature, Volumes of Water, Diets, Urine and Feces

The weight and the rectal temperature were measured at 4:00 PM on the first, third, seventh, eleventh and fifteenth day. The volumes of water, diets, urine and feces for 24 h were calculated by placing the rats into metabolic cages on the fourteenth day.

Serum Samples Collection

Two hours after the last drug administration, we collected the blood from the abdominal aorta and centrifuged it at 2500 rpm/min for 10 min. The separated serum samples were stored at −80°C for further analysis.

Sample Preparation for Metabolic Profiling Analysis

After being thawed at room temperature, fifty microliters of serum from each sample were pipetted into 1.5 mL microcentrifuge tubes, followed by the addition of 200 μL of cold methanol with 20 μg/mL tridecanoic acid as the internal standard. All analytic samples were vortex-mixed thoroughly for 30 s. After centrifugation at 12 000 g, 4 °C for 10 min, the supernatant was transferred for vacuum drying in CentriVap Centrifugal Vacuum Concentrators (Labconco, USA). Then, 50 μL of methoxyamine pyridine solution (20 mg/mL) was added to the dried sample, oximating for 90 min in a 40°C water bath. Afterwards, a silylation reaction was conducted by adding 40 μL of MSTFA for 60 min. The metabolic profiling of quality control (QC) samples was analyzed using the same method as the prepared serum. The QC samples were injected at every ten serum samples throughout the analytical run to provide a set of data from, which repeatability and reliability could be assessed.

GC-MS Analysis

GC-MS analysis was conducted by an Agilent 7890/5975CGC–MS (Agilent Technologies, USA). Metabolites were separated by using a 30 m × 0.25 mm × 0.25 μm DB-5 fused silica capillary column (J&W Scientific, USA). The injection volume and split ratio were respectively set to 1 μL and 10:1. The event time was adjusted to 0.2 s. The high-purity Helium (99.9996%) was used as the carrier gas and the flow rate was 1.2 mL/min. The oven temperature was initially set to 70 °C, kept for 3 min, and then rose to 300 °C at a rate of 5 °C/min, and finally kept for 5 min. Temperatures of inlet, interface, and ion source were manipulated at 300, 280, and 230 °C. Mass signal acquisition was from m/z 33 to 600.

Data Processing and Statistical Analysis

AMDIS 2.62 software (NIST, USA) was utilized to perform the peak detection and the resolution of co-eluting peaks. The peak alignment was conducted in GC/MSD ChemStation software (Agilent Technologies, USA) for generating a multivariate data matrix. The normalized data were put into SIMCA-P 11.0 version software (Umetrics AB, Umea, Sweden) to carry out the principal component analysis (PCA), supervised partial least-squares discriminant analysis (PLS-DA), and orthogonal partial least-squares discriminant analysis (OPLS-DA). The differential metabolites between the control group and RG-WE treated groups were screened by the variable importance in the projection (VIP) values and Student's t-test by using SPSS 21(International Business Machines Corp., USA). The VIP parameter of the changed metabolites exceeding 1.0 from the OPLS-DA model combined with a p-value threshold set at 0.05 from Student's t-test was selected as the significantly changed metabolites. Based on the retention time and mass charge ratio, differential metabolites were identified by searching their similar structures in the NIST05 mass spectral library (National Institute of Standards and Technology, Gaithersburg, MD, USA). The accurate molecular structures of the identified metabolites were matched by NIST Mass Spectral Search Program Version 2.0 (www.nist.gov/srd/mslist.htm) with a NIST match factor ≥700.

Results

The Associations Between “Shanghuo” and RG Based on Biological Network Analysis

A total of 74 human targets related to “Shanghuo” were retrieved from the references (Supplementary Table 1). There were 129 putative targets corresponding to 30 compounds in RG (Supplementary Table 2). To build a biological network of “Shanghuo” and RG, we obtained 1386 protein associations from the STRING database (Supplementary Table 3). There were two overlapped genes in the datasets of “Shanghuo” and RG, Apolipoprotein (APO) B and Serum albumin (ALB). To precisely focus on the correlation of “Shanghuo” and RG, we removed those internal interactions from each dataset and established a new biological network to present those mutual influenced associations, as visualized in Figure 2. As the common targets, APOB and ALB played a major part in this network. On the other hand, Transient Receptor Potential Channel Vanilloid 1 (TRPV1) (degree = 20) and ALB (degree = 19), as the nodes with the highest degree in the network, tied “Shanghuo” and RG all together, suggesting their important role in the mechanism of RG-induced “Shanghuo”. Additionally, the top six central compounds of RG acting in “Shanghuo” are menthol, ginsenoside Rb1, pentadecylic acid, palmitic acid, zoomaric acid and myristic acid.

Figure 2.

Compound-target network of RG compounds, RG targets and RG-influenced “Shanghuo” targets. Diamond represents disease. Hexagon represents herb. Round rectangles represent compounds: the colors from blue, dark green to light green reflect the connected number of targets. Rounds represent targets: orange rounds are “Shanghuo” targets; red rounds are RG targets; purple rounds are the common targets of “Shanghuo” and RG.

To better understand the mechanism of RG induced “Shanghuo” and “Shanghuo” related RG targets, KEGG pathway enrichment analysis was performed in STRING database. Three pathways were found to be significantly enriched with the “Shanghuo” targets affected by RG, including fat digestion and absorption, cholesterol metabolism and thyroid hormone synthesis. The top ten KEGG pathways of “Shanghuo” related RG targets were pentose and glucuronate interconversions, AMPK signaling pathway, biosynthesis of unsaturated fatty acids, metabolic pathways, PPAR signaling pathway, cholesterol metabolism, TNF signaling pathway, inflammatory mediator regulation of TRP channel, glucagon signaling pathway and adipocytokine signaling pathway. As illustrated in Figure 3, cholesterol metabolism was found as the overlapped pathway of the two datasets.

Figure 3.

Overlaps between the “Shanghuo” and RG pathway datasets. The “Shanghuo” dataset presents the KEGG pathways of those RG-influenced “Shanghuo” targets. The RG dataset presents the KEGG pathways of those RG targets that have impact on “Shanghuo”.

Molecular Docking Results

Molecular docking between the key active components of RG (ginsenoside Rb1, menthol, myristic acid, palmitic acid, pentadecylic acid and zoomaric acid) and the common targets of “Shanghuo” and RG (ALB and APOB) was carried out using AutoDock Vina and MglTools. Due to the strongest affinity with core targets illustrated in Figure 4, the prediction for the ligand binding domains acted by ginsenoside Rb1 was particularly visualised with PyMOL.

Figure 4.

Results of molecular docking. (A) Heatmap of the docking scores for the active compounds of RG and the target proteins. (B) Molecular docking results of ginsenoside Rb1 to APOB (6I7S). (C) Molecular docking results of ginsenoside Rb1 to ALB (6M4R).

The Establishment of the “Shanghuo” Model by RG-WE

Compared with the control group, “Shanghuo” group had tousled hair, irritable temper, dark urine and dry stool. Animals had a series of tests to validate the establishment of the “Shanghuo” model by RG-WE. As can be seen in Figure 5 and Table 1, the “Shanghuo” group had significantly lowered weight and rising volumes of food intake, drinking, feces and urine in comparison with the control group; the difference in the renal temperature between the control group and “Shanghuo” group was not significant, while the rectal temperature on the 15th day of “Shanghuo” group was significantly increased compared with the first day.

Figure 5.

Effects of RG water extracts on the weight and temperature in rats. Weight data (A) are presented as the means ± standard deviation; Temperature data (B) are presented as the means. (n = 10) * presents p < .05 versus control group; ** presents p < .01 versus control group.

Table 1.

the Effects of red ginseng Water Extracts on the Volumes of Diet, Drink, Feces and Urine in Rats.

Group	Diet (g)	Drink (ml)	Feces (g)	Urine (ml)
Control group	12.05 ± 1.75	22.22 ± 7.30	8.38 ± 1.40	6.53 ± 3.33
Shanghuo group	16.93 ± 1.87*	29.43 ± 3.99*	10.65 ± 2.36*	11.12 ± 3.91*

Note: *presents p < 0.05 versus control group.

Multivariate Statistical Analysis of Differential Metabolites in “Shanghuo” Group

The major sources of metabolic differences between the serum samples were displayed in PCA analysis. The PCA model suggested distinct differences between the “Shanghuo” group and control group (R2X = 0.645), as displayed in Figure 6A. Then, PLS-DA modeling and a permutation test (permutation number: 200) were performed to clarify the metabolic information behind the alteration of principal components. As illustrated in Figure 6B, the parameters of R2Y and Q2 value of 0.979 and 0.771 were considered to have excellent explanatory and predictive ability of the PLS-DA model. The permutation test was further conducted to validate the model and avoid over-fitting, as presented in Figure 6C. To screen differential metabolites between the groups, the OPLS-DA model was performed eventually. The OPLS-DA score plot illustrated that the cumulative R2Y and Q2 were 1 and 0.714, respectively, as shown in Figure 6D. The results above indicated that the validation plots could ensure the reliability and great predictability of the established OPLS-DA model.

Figure 6.

Multivariate statistical analysis for GC-MS based on metabolic profiling. (A) a PCA score plot data from the control group (five-point star) versus the “Shanghuo” group (four-point star); (B) a PLS-DA scores plot data from the control group (five-point star) versus the “Shanghuo” group (four-point star); (C) internal cross-validation plot with a permutation test repeated 200 times; (D) an OPLS-DA scores plot data from the control group (five-point star) versus the “Shanghuo” group (four-point star).

22 differential metabolites were identified in the “Shanghuo” group using the criteria of VIP > 1 and p < 0.05 from the OPLS-DA model. These differential metabolites were mainly associated with carbohydrates, fatty acids, amino acids and their products, as illustrated in Figure 7A. Compared with the control group, the content of most metabolites in the “Shanghuo” group decreased including fatty acids, cholesterol, lactic acid and pyruvic acid, while a part of the metabolites increased, like glucose and most of amino acids. A majority of differential metabolites in the “Shanghuo” group were down regulated, especially oleic acid, octadecanoic acid and hexadecanoic acid. As shown in Figure 7B and C, the down-regulated metabolites in the “Shanghuo” group were associated with 7 pathways, while the up-regulated metabolites were enriched in 3 pathways. Interestingly, the down-regulated pathway of biosynthesis of unsaturated fatty acids explained the most enriched pathway based on network pharmacology analysis, fat digestion and absorption.

Figure 7.

Metabolites in the “Shanghuo” group. (A) Volcano plot of the significantly changed metabolites in the “Shanghuo” group. The size of the dots represents the variable importance in the projection value; the x-axis represents log2 (fold change); the y-axis represents –log10 (p value); (B) Pathways of down-regulated metabolites; (C) Pathways of up-regulated metabolites.

Discussion

“Shanghuo” is a complex and broad concept, ranging from a state of sub-health to some inflammation of skin and mucosa, mostly occurring on the head and face. ¹⁶ Our research team found that some warm-natured herbs like Cinnamomum cassia Presl could boost yang qi and generate “Shanghuo”. ¹⁷ Prepared by a heating process, RG, a popular healthcare product, is considered to have warm functional characters as well. ¹⁸

To fully understand the molecular and metabolic mechanism of RG-induced “Shanghuo”, we began with performing an analysis of systems pharmacology of the two in this study. Based on the network analysis, APOB and ALB were found as the co-acting targets of RG and “Shanghuo”. As a central role in cholesterol metabolism, APOB is considered as an essential structural component of VLDL, ¹⁹ and the predominant trait that accounts for the risk of coronary heart disease, ²⁰ both suggesting that the level of APOB can be a good response to the circulating fatty acids. A significantly decreased APOB was reported in “Shanghuo” people, indicating that lower cholesterol and fatty acids were related to “Shanghuo”. ²¹ Meanwhile, RG could reverse the VLDL accumulation and decrease cholesterol as well. ²² As for the other common target, ALB may not have specific functions but it has a good binding capacity for cations like Ca²⁺, Na⁺ and K ⁺. Na ⁺-K ⁺-ATPase activity was regarded as the main index to reflect the “Shanghuo” influenced by RG. ³ As a channel modulating intracellular calcium level, TRPV1 was a vital target joining “Shanghuo” and RG together through the connection via ALB. As a drug delivery carrier, ALB has been proved to be an ideal carrier for a better function of those ginsenosides derived from Red Ginseng within human body. ²³ Study shows that some modified rat ALB could increase the expression of TRPV1. ²⁴ Interestingly, the activation of the TRPV1 channel which plays a key role in inflammatory signaling pathways, could contribute to the incidence of “Shanghuo” related diseases, ⁹ like pulpitis, ²⁵ xerostomia ²⁶ and oral ulcer, ²⁷ etc. Several reports have shown that the activation of TRPV1 ion channels could enhance the thermal sensitivity or burning sensation, which suggests a strong relationship with the manifestations of “Shanghuo”. ²⁸ The TRPV channel is a nonselective cation channel that mediates the transient influx of Ca²⁺ into cells. ²⁹ The disorder in calcium-dependent mitochondrial metabolism can not only trigger inflammation, but also break the lipid homeostasis. ³⁰ There is also evidence that calcium enhances oxidative respiration and ATP production by regulating the activity of tricarboxylic acid (TCA) cycle rate-limiting enzymes. ³¹ Moreover, AMP-activated protein kinase (AMPK) can be activated by TRPV1-mediated transient Ca²⁺ influx, ³² which might explain the increased AMPK activity in “Shanghuo” resulted from our previous study. ⁹ Molecular docking proved that ginsenoside Rb1 exerted the dominant impact on “Shanghuo”. Ginsenoside Rb1, the major active constituent of RG, has been found to be involved in energy homeostasis and weight loss. ³³ It was also reported that Ginsenoside Rb1 could regulate mitochondrial energy metabolism and promote the activation of AMPK phosphorylation. ³⁴

The KEGG pathway analysis in this study found that RG-induced “Shanghuo” targets were mostly enriched in the pathways of fat digestion and absorption and cholesterol metabolism. In order to validate those mechanisms, we built the “Shanghuo” model in rats and performed GC-MS based metabolomics approach. Levels of fatty acids including octadecanoic acid, hexadecanoic acid and oleic acid were markedly lower in the “Shanghuo” group of the current study. Those differential metabolites derived from fats decreased as well. The falling circulating concentrations of glycerol are associated with the reduction of fat mass. 3-hydroxybutyric acid, also referred to as β-hydroxybutyric acid, is one of the ketone bodies, which are small molecules synthesized primarily from fats. Those down-regulated metabolites were mostly enriched in the biosynthesis of unsaturated fatty acids, which was strongly associated with the most enriched pathway based on network pharmacology analysis, fat digestion and absorption. In the meantime, RG has been reported to effectively improve obesity by promoting the fat metabolism and lipolysis of triglycerides. ³⁵ Additionally, reduced cholesterol was observed in both the previous and present study, while RG is proven to lower total cholesterol and lipid accumulation.

Aside from the increased fat metabolism, the major differential metabolites, such as illustrated in Figure 8, suggested an acceleration of energy expenditure in the “Shanghuo” group, which is in consistent to the data obtained by our previous research. As a supplier of energy, pyruvate was oxidized to acetyl-CoA and participated in the TCA to serve fuel mitochondrial respiration and ATP, which decreased the pyruvic acid content significantly. ³⁶ The increased alanine could provide a positive signal to activate AMPK signaling pathway as a distinct amino acid energy sensor, ³⁷ which was in line with the increased AMPK activity in our previous work. Our prior study also indicated that the RG-induced “Shanghuo” animal model might have activated AMPK regulation which acted on its downstream including Nuclear Respiratory Factor 1 (NRF1), promoting mitochondrial biosynthesis and ATP production. ⁵ Additionally, the analysis of the AMPK signaling pathway in the RG-induced “Shanghuo” model has been carried out in our clinical study, ⁹ which provides strong evidence for fat metabolism and energy expenditure revealed in the current study. However, AMPK still need to be tested for protein level in the clinical trial furthermore. The up-regulated creatinine, suggesting the faster breakdown of creatine, which is a key participant in the generation of ATP also implied the increased ATP synthesis. ³⁸ The increased threonine significantly contributes to the biosynthesis of glycine and acetyl-CoA, thus promoting TCA, ³⁹ while the supplements of threonine decrease the requirement for aspartic acid. ⁴⁰ The elevated proline could be oxidized to glutamate which can enter the TCA cycle and make contributions to ATP. ⁴¹ The rising ryroglutamic acid (also referred to 5-oxoproline) could generate glutamic acid with the energy from ATP, ⁴² while the depletion of ATP could reduce the level of tyrosine by activating tyrosine phosphorylation. ⁴³

Figure 8.

The metabolic network of “Shanghuo” related differential metabolites. The red represents increased metabolites in “Shanghuo” group. The blue represents decreased metabolites in “Shanghuo” group.

On the one hand, this study again proved that RG could give rise to “Shanghuo” from the perspectives of systems pharmacology and metabonomics. On the other hand, the current study demonstrated for the first time that fat metabolism and energy expenditure were closely related to “Shanghuo” induced by RG. A recent study has proved that thermogenesis in adipose tissue could be triggered via AMPK signaling axis to lose weight. ⁴⁴ Moreover, weight loss with the increased energy expenditure could bring with it additional heat. ⁴⁵ Given that the proper expansion of adipose tissue is critically important for maintaining body energy homeostasis, ⁴⁶ the altered intracellular lipid levels can lead to metabolic and inflammatory dysfunction. ⁴⁷ Therefore, we assume that the disorders in heat dissipation along with the accelerated fat metabolism and overactive energy expenditure could bring about the manifestations of “Shanghuo” like ulcer, pharyngitis and gingivitis, etc ¹⁶ A recent study showed that RG could exhibit a warm nature by elevating the level of adrenaline and enhancing the activity of hypothalamus-pituitary-adrenal axis. Our study also found that RG is liable to increase energy metabolism, while over-consumption of RG might cause some unexpected reactions such as “Shanghuo”. However, subsequent experiments in vitro should be conducted to confirm the roles of the relevant targets in accelerated fat metabolism and determine whether these targets are affected by RG.

Conclusion

Through the comprehensive analysis of systems pharmacology approach and GC-MS based metabolomics, our study indicated that the disorders in the heat dissipation along with the accelerated fat metabolism and overactive energy expenditure might contribute to RG-induced “Shanghuo”.

Supplemental Material

sj-xls-1-npx-10.1177_1934578X241291396 - Supplemental material for Potential Molecular Mechanisms and Metabolic Networks in Red Ginseng-induced “Shanghuo” (上火)

Supplemental material, sj-xls-1-npx-10.1177_1934578X241291396 for Potential Molecular Mechanisms and Metabolic Networks in Red Ginseng-induced “Shanghuo” (上火) by Zi Yang, Yi Zhang, Ruifei Xie, Zhijun Xie, Kai Zhao, Yongsheng Fan and Ting Zhao in Natural Product Communications

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sj-xlsx-2-npx-10.1177_1934578X241291396 - Supplemental material for Potential Molecular Mechanisms and Metabolic Networks in Red Ginseng-induced “Shanghuo” (上火)

Supplemental material, sj-xlsx-2-npx-10.1177_1934578X241291396 for Potential Molecular Mechanisms and Metabolic Networks in Red Ginseng-induced “Shanghuo” (上火) by Zi Yang, Yi Zhang, Ruifei Xie, Zhijun Xie, Kai Zhao, Yongsheng Fan and Ting Zhao in Natural Product Communications

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sj-xlsx-3-npx-10.1177_1934578X241291396 - Supplemental material for Potential Molecular Mechanisms and Metabolic Networks in Red Ginseng-induced “Shanghuo” (上火)

Supplemental material, sj-xlsx-3-npx-10.1177_1934578X241291396 for Potential Molecular Mechanisms and Metabolic Networks in Red Ginseng-induced “Shanghuo” (上火) by Zi Yang, Yi Zhang, Ruifei Xie, Zhijun Xie, Kai Zhao, Yongsheng Fan and Ting Zhao in Natural Product Communications