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Original article
2021
:14;
202106
doi:
10.1016/j.arabjc.2021.103185

Characterization of the bioactive compounds with efficacy against gout in Guizhi Shaoyao Zhimu Decoction by UHPLC-Q-Orbitrap HRMS combined with network pharmacological analysis

Chengdu University of Traditional Chinese Medicine, Sichuan, China
Good Doctor Pharmaceutical Group Co., Ltd., Sichuan, China

⁎Corresponding authors. 406084191@qq.com (Yongxiang Gao), huangqinwan@cdutcm.edu.cn (Qinwan Huang)

Disclaimer:
This article was originally published by Elsevier and was migrated to Scientific Scholar after the change of Publisher.

Abstract

  • It was the first time to combine UHPLC-Q-Orbitrap HRMS with network pharmacology analysis to elucidate the potential underlying mechanisms of GSZD in the treatment of gouty arthritis.

  • A total of 79 chemical components were detected in GSZD.

  • 11 compounds were considered to potentially key active compounds against GA which may be via interacting with multiple inflammatory factors and multiple inflammatory pathways.

Abstract

The current study aimed to explore the mechanism of Guizhi Shaoyao Zhimu Decoction in the treatment of gouty arthritis based on the combination of Vanquish Ultra High Performance Liquid Chromatography Q Exactive IV Pole-electrostatic field orbital trap high resolution mass spectrometer (UHPLC-Q-Orbitrap HRMS) and network pharmacology. Firstly, UHPLC-Q-Orbitrap HRMS was established and applied to separation and identification of the chemical components of GSZD. Then, using network pharmacology analysis to obtain the potential active components and candidate targets underlying the effect of GSZD on gouty arthritis (GA). Through targeted and untargeted analysis, a total of 79 components, including 3 chromones, 26 flavonoids, 10 alkaloids, 10 phenolic acids, 7 nucleosides and nucleobases, and 23 other components, were characterized from GSZD. 11 compounds were considered to potentially key active compounds against GA which may be via interacting with multiple inflammatory factors and multiple inflammatory pathways.

Keywords

Guizhi Shaoyao Zhimu Decoction
Gouty arthritis
UHPLC-Q-Orbitrap HRMS
Network pharmacology
Chemical components analysis

Abbreviations

GA

Gouty arthritis

DMARDs

disease modifying antirheumatic drugs

NSAIDs

non-steroidal anti-inflammatory drugs

GSZD

Guizhi Shaoyao Zhimu decoction

GO

Gene Ontology

TCM

Traditional Chinese Medicine

PGE2

Prostaglandin E2

LTB4

Leukotriene B4

5-HT

5-hydroxytryptamine

TGF- β1

Transforming growth factor-β 1

TGF- β R1

Transforming growth factor-β receptor 1

MyD88

Myeloid differentiation factor 88

NLRP3

NACHT-LRR-PYD-containing proteins 3 inflammasome

NF-кB

Nuclearfactor-kappa B

1

1 Introduction

Gout, one of the most common and treatable inflammatory diseases, is induced by excessive sedimentation of monosodium urate (MSU) crystals in various tissues and joints (Bodofsky et al., 2020; Dalbeth et al., 2016). The incidence of gout accounts for about 2–4% of the entire population, and the incidence has continued to rise in recent years, causing significant damage to public health (Singh et al., 2019). When excessive sodium urate crystals are deposited on the articular cartilage, it stimulates the generation of pro-inflammatory mediators in the cartilage, and increases cartilage degrading enzymes, generating gouty inflammation and joint damage which is called gouty arthritis (GA). The drugs currently used include non-steroidal anti-inflammatory drugs (NSAIDs), urate-lowering drugs-colchicine. Although these drugs have a certain effect, they are often suboptimal due to the low adherence rate and high risk of recurrent gout attacks, even trigger gastrointestinal or cardiovascular adverse effect inevitable (Doherty et al., 2018; Qaseem et al., 2017). Consequently, more new and effective therapy to fight GA are still secured in clinical practice.

Traditional Chinese Medicine(TCM) has made an important contribution to safeguarding the health of people all over the world, especially in Asia. At present, in fighting COVID-2019, we can see that traditional Chinese medicine has unique advantages in safeguarding people's health, such as remarkable effect and little adverse effect, low recurrence rate, and so on (Hu et al., 2021; Tian et al., 2020). In the treatment of gouty arthritis, the prescription of traditional Chinese medicine also shows its unique advantages. among the many prescriptions for the treatment of gouty arthritis, Guizhi Shaoyao Zhimu Decoction (GSZD) is one of the first classic prescriptions issued by the State Administration of Traditional Chinese Medicine, which was first recorded in “The Synopsis of the Golden Chamber” written by Zhongjing Zhang. It is a valuable resource left behind after thousands of years of practice, chemical composition research, efficacy research, pharmacology research is particularly important. At present, the government is stepping up the development of the prescription, hoping to develop it into a commodity and serve the world. However, the pharmacological research on this prescription is mainly focused on rheumatoid arthritis (Zhang et al., 2019), and the research on gouty arthritis is mainly focused on the clinical efficacy. Some studies are analyzing the prescription through meta analysis, and it is concluded that compared with western medicine, this prescription can significantly reduce the clinical symptoms of patients with gouty arthritis (Shi, 2012; Shi et al., 2010; Xinhai et al., 2019; Zhang et al., 2020). At present, the mechanism of GSZD in the treatment of GA is still in its infancy. By giving GSZD to acute gouty arthritis rats, it was found that GSZD could significantly reduce the level of PGE2, LTB4 in serum, reduce the content of peripheral 5-HT, promote the expression of TGF- β 1 and TGF- β R1 in joint tissue, and reduce the expression of Toll-MyD88 and NLRP3 inflammatory signals through inflammatory factors (Wu, 2014; Xiao et al., 2011). Besides, it can also reduce the content of serum uric acid (UA), serum creatinine (Cr) and serum urea nitrogen (BUN) in hyperuricemia model rats, reduce the content of uric acid, protect renal function and accelerate uric acid excretion (Fang, 2016). However, there is a lack of basic research on the material basis of pharmacodynamics. GSZD consists of 9 herbs, including Cinnamomum cassia Presl (also called Gui Zhi), Paeonia lactiflora Pall. (Shao Yao), Anemarrhena asphodeloides Bge. (Zhi Mu), Saposhnikovia divaricate (Turcz.) Schischk. (Fang Feng), Atractylodes Macrocephala Koidz. (Bai Zhu), Ephedrae sinica Stapf (Ma Huang), Glycyrrhiza uralensis Fisch. (Gan Cao), Zingiber officinale Rosc. (Sheng Jiang) and Processed Aconitum carmichaelii Debx. (Pao Fuzi) (Fig. 1). At present, the study on the overall chemical constituents of GSZD is not comprehensive, all of which are the results of our research group (Yi, 2019; Zhang et al., 2019)(). These chemical composition in herbs were associated with GA. Total glucosides of paeony in Paeonia lactiflora Pall. could inhibit the production of IL-1 β and IL-6 and TNF- α induced by MSU (Li et al., 2017). Total glucosides of paeony also suppressed MUS-induced inflammation in THP-1 macrophages via regulating MALAT1/miR-876-5p/NLR4/MyD88/NF-кB pathway (Meng et al., 2021). Gallic acid in Paeonia lactiflora Pall. also alleviated GA by suppressed NLRP3 inflammasome activation as well as pyroptosis dependent on Nrf2 signaling (Lin et al., 2020a). These results are promising for studying the mechanism of GSZD in the treatment of GA. Nevertheless, the active chemical constituents and mechanisms of GSZD acting on GA remains unclear.

The composition of GSZD.
Fig. 1
The composition of GSZD.

It is difficult to elaborate the pharmacological mechanisms of Chinese medicine prescription experimentally owing to it is multi-component and multi-target. Up to now, many modern analytical techniques and methods have been used to explore the chemical components of TCM and mechanism of treating diseases, such as UHPLC-Q-Orbitrap HRMS and network pharmacology. UHPLC-Q-Orbitrap HRMS can not only achieve the purpose of preliminary separation of mixed Chinese herbal medicine with high chromatographic resolution by simple pretreatment, but also identify possible chemical compounds with small mass error through accurate quality value and element. The network pharmacology is a novel, collective, systemic, and meta-analysis approach, which mainly uses the research methods of system biology. It uses mathematical methods such as statistics and complex networks to analyze the relationship between drugs and targets, which changes the original research idea of single drug and single target, opens up new horizons for the research of multi-component medicines, especially herbal medicines and Chinese medicine prescriptions (Hopkins, 2008; Zhang et al., 2019c).

In this experiment, first of all, the UHPLC-Q-Orbitrap HRMS method with rapid and sensitive advantages was used to analyze the components of GSZD, which has more accurate and comprehensive for constituent identification than those online searches. Then, analyzing the mechanism of GSZD in the treatment of GA in combination with network pharmacology more comprehensively helps discover the new potential therapeutic targets and disease treatment pathways. As far as we know, it is the first time to profile the chemical components in GSZD by UHPLC-Q-Orbitrap HRMS and illuminate the mechanism of GSZD against GA with a network pharmacology approach. Moreover, the results can further benefit from illuminating the effective components for GSZD and analysis to discover new, potential therapeutic targets and disease treatment pathways.

2

2 Methods

2.1

2.1 Materials, experiment conditions for GSZD compound identification

2.1.1

2.1.1 Chemicals and reagents

A total of 8 reference standards were purchased from the National Institutes for Food and Drug Control (Beijing, China). They were 5-O-methylvisammioside (111523–201610) with the degree purity is 96.10%, Paeoniflorin (110736–201842) with the degree purity is 97.40%, Mangiferin (111607–201704) with the degree purity is 98.10%, Prim-O-glucosylcimifugin (111522–201712) with the degree purity is 96.20%, Liquiritin (111610–201607) with the degree purity is 93.10%, Gallic acid (110831–201605) with the degree purity is 90.80%, Ephedrine Hydrochloride (171241–201809) and Pseudoephedrine Hydrochloride (171237–201510).

Two reagents, acetonitrile and formic acid, met for HPLC grade. Both were bought from Thermo Fisher Scientific (USA). The Watsons distilled water was applied to preparation for samples and the mobile phase. All other reagents were just met for analytical grade.

2.1.2

2.1.2 Preparation of standard solutions

The eight reference standards mentioned above were dissolved in methanol to 10 ml to acquire 1 μg/ml of each reference substance, kept at 4 °C before analysis.

2.1.3

2.1.3 Preparation of sample solution

The material standard of GSZD according to the best decoction conditions obtained by Yi (2019). At first, Preparation of freeze-dried powder. Weigh Cinnamomum cassia Presl (also called Gui Zhi) 12 g, Paeonia lactiflora Pall. (Shao Yao) 9 g, Anemarrhena asphodeloides Bge. (Zhi Mu) 12 g, Saposhnikovia divaricate (Turcz.) Schischk. (Fang Feng)12 g, Atractylodes Macrocephala Koidz. (Bai Zhu) 15 g, Ephedrae sinica Stapf (Ma Huang) 6 g, Glycyrrhiza uralensis Fisch. (Gan Cao) 6 g, Zingiber officinale Rosc. (Sheng Jiang) 15 g, and Processed Aconitum carmichaelii Debx. (Pao Fuzi) 6 g respectively, added 1400 ml of water, soaked for 30 min, closed the lid of the casserole, boiled over high heat until boiling, opened the lid of the casserole, turned down the firepower to keep the liquid slightly boiling, the boiling time is about 70 min, filtered with 200 mesh filter cloth while hot and squeeze the dregs to cool, then fixed the volume to 400 ml, used vacuum freeze-drying to make freeze-dried powder. Second, accurately weighed 0.5 g of freeze-dried powder, added 25 ml of 75% methanol into a 50 ml Erlenmeyer flask respectively, next weighed by balance scales, then made use of the ultrasonic bath (40 kHz, 150 W) for 30 min, cooled to room temperature, adjusted the weight with methanol again, shaken, finally filtered sample solution with a 0.22 μm microporous membrane before analysis. The sample solution was stored at 4 °C before analysis.

2.1.4

2.1.4 Instrument and analysis conditions

Identification of GSZD compounds was carried out on the Vanquish Ultra High Performance Liquid Chromatography Q Exactive IV Pole-electrostatic field orbital trap high resolution mass spectrometer produced by Thermo Fisher Scientific (USA). Xcalibur software (version 3.0) was applied to command instruments, gather and analyze data.

Thermo Scientific Accucore™ C18 column (100 × 3 mm, 2.6 μm, Thermo Scientific) was employed at column temperature 30 °C. The mobile phase consisted of 0.1% formic acid in water (A) and acetonitrile (B), and the flow rate was 0.3 ml/min. The gradient elution parameters was set as follows: 0–20 min, 5–70%B; 20–25 min, 70–90%B; 25–30 min, 90–5%B; 30–35 min, 5%B. The injection volume was 2 μL.

The positive and negative ion mode detection was performed on Q Exactive Quadrupole-Electrostatic Field Orbital Trap combined with UHPLC through ESI electrospray ion source. The spray voltage of positive mode and negative mode were both set at 3000 V, the probe heater temperature of positive mode and negative mode were both set at 350 °C, the sheath gas of positive mode and negative mode were both set at 35arb, the auxiliary gas of positive mode and negative mode were both set at 10arb, and capillary temperature of positive mode and negative mode were both set at 320 °C. S-Lens RF level was set at 50. The primary resolution of the full scan was 70,000 with the scanning range from m/z = 100 to m/z = 1500. The secondary resolution was 17,500 with the collision energy gradient of 20ev, 40ev, and 60ev.

2.1.5

2.1.5 Data processing

The raw data requirement and processing were carried out by Compound Discoverer 3.0 software, and On the condition of its wizard settings and method templates built the identification process of unknown compounds. Software executed peak alignment and peak extraction on the original data to obtain molecular ion peaks, and possible molecular formulas fitted by isotope. Moreover, the secondary fragments’ measured spectra were matched with databases named the mzCloud, the local Chinese medicine component database OTCML respectively. Preserve the chemical constituents met to peak area threshold is more than 80,000, the mass deviation is less than 5 ppm, and the matching score is more than 85. Finally, further confirming the compound with the reference substance and related literature.

2.2

2.2 Construction and analysis of GSZD compounds-disease target interaction network

2.2.1

2.2.1 Drug-likeness filtering

The identified chemical compounds were imported into the PubChem (https://pubchem.ncbi.nlm.nih.gov/) to acquire Canonical SMILES. The SwissADME (http://www.swissadme.ch/) base Canonical SMILES was utilized to identify “Drug-likeness” property according to the Lipinski’s rule and Gl absorption. The chemical components, meet condition of high Gl absorption, and more than two yes under “Druglikeness”, were filtered out as potential active ingredients.

2.2.2

2.2.2 Targets related to selected constituents or GA

For the putative targets genes of the selected compounds, two approaches were applied. First, the validated targets of potential active compounds were gathered from HERB (http://herb.ac.cn/), CTD (http://ctdbase.org/) with the species is “Homo sapiens”. Second, the possible targets were predicted by SEA (http://sea.bkslab.org/) under the condition with the screening criteria are: Tc>0.7, and the species is “Homo sapiens”.

For the GA-related genes, they were searched with the phrase “gouty arthritis” as key word in the five public databases include CTD (http://ctdbase.org/), GeneCards (https://www.genecards.org/), OMIM (https://www.omim.org/), DisGeNET (https://www.disgenet.org/), GEO (https://www.ncbi.nlm.nih.gov/). All the GA-related targets were collected.

All targets, whether compound targets or disease targets, deleted duplicate values and invalid genes, and then all enter the Uniprot database (https://www.uniprot.org/) to calibrate the target protein and gene information. At last, they were all reviewed human targets.

The Venny 2.1 online tool (https://bioinfogp.cnb.csic.es/tools/venny/index.html) was exploited to draw the Venn diagram of active ingredient targets and GA targets, the existence of overlapping common targets may be the critical target of GSZD in the treatment of GA.

2.2.3

2.2.3 Screening and confirming active components and potential targets

The active ingredients and GA-related target interaction network was built by importing into Cytoscape (Version 3.8.0, Java 11.0.6) for visualization and analysis. The topological properties of the network were calculated using “Network Analyzer”, sort them according to the degree, Betweenness Centrality and Closeness Centrality values, take all the targets higher than the median, take the intersection as core targets. Analyze protein–protein interaction (PPI) of core targets in String database (https://string-db.org/), where the species were limited to “Homo sapiens”, and set the minimum required connection score between the targets is 0.4, and import Cytoscape software for processing and screening.

2.2.4

2.2.4 Enrichment analysis

The ClueGo plug-in was often used for Go enrichment analysis. At first, inputting the selected key targets for biological processes, molecular functions, cellular component, and KEGG pathway enrichment analysis respectively. Second, select “Homo sapiens”. The set the P and advanced term/pathway selection options. Besides, the REACTOME database (https://reactome.org/) was utilized for pathway enrichment and screening. Based on the relationship between GSZD and core active components, and the relationship between core targets and pathway, GSZD-herb-core active component-target-pathway was visualized by Cytoscape 3.8.0 software.

3

3 Results and discussion

3.1

3.1 Identification of components in GSZD by HPLC-Q-Orbitrap HRMS

Fig. 2 stands the total ion chromatogram of GSZD both in positive and negative modes respectively under the optimized UHPLC-Q-Orbitrap HRMS conditions. The Compound Discoverer 3.0 software calculated the molecular formula within the scope of 5 ppm mass deviation, and then matched the available databases named mzCloud and the OTCML (Orbitrap Traditional Chinese Medicine Library), as well as referring to related literature for identifying and elucidating compound structure. Finally, a total of 79 components, including 3 chromones, 26 flavonoids, 10 alkaloids, 10 phenolic acids, 7 nucleosides and nucleobases, and 23 other components, were deciphered from GSZD. Among the 79 compounds identified, eight compounds were confirmed by authentic reference standards. The final result of identification in GSZD was shown in Table 1. Looking up many kinds of literature to elaborate mass spectral data and predict possible fragmentation pathways.

The TIC chromatograms in both ESI modes of GSZD. A presents positive ion. mode, B presents negative ion mode.
Fig. 2
The TIC chromatograms in both ESI modes of GSZD. A presents positive ion. mode, B presents negative ion mode.
Table 1 Identified compounds of GSZD by UHPLC-Q-Orbitrap HRMS.
NO. RT [min] Molecular Formula Identification Measured mass Accuracy mass Error Selective ion Prominent MS2 Fragmentations (m/z) Molecular Weight Type
(m/z) (m/z) (ppm)
1 1.601 C9H20N2O2 N6, N6, N6-Trimethyl-L-lysine 189.15993 189.15975 0.93 [M+H]+ 60.08150, 84.08135, 130.08641 188.15265 f
2 1.655 C6H9N3O2 L-Histidine 154.06175 154.06220 −2.92 [M−H] 93.04499, 110.07165, 137.03508 155.06949 f
3 1.703 C6H13NO5 D-Glucosamine 180.08661 180.08665 −0.22 [M+H]+ 60.04510, 72.04505, 84.04497, 98.06050, 114.05526, 126.05518, 144.06558 179.07941 f
4 1.986 C5H11N3O2 4-Guanidinobutyric acid 146.09259 146.09240 1.28 [M+H]+ 60.05628, 86.06053, 87.04453, 104.07095, 128.08185 145.08526 f
5 2.039 C4H5N3O Cytosine 112.05087 112.05054 2.96 [M+H]+ 70.06571, 95.02435 111.04365 e
6 2.095 C4H8N2O3 Asparagine 133.06105 133.06077 2.11 [M+H]+ 74.02423, 87.05576, 116.03442, 132.05295 f
7 2.128 C5H10N2O3 D- (-)-Glutamine 145.06128 145.06187 −4.04 [M−H] 84.04463, 101.07125, 109.04003, 127.05067, 128.03474 146.06875 f
8# 2.332 C7H7NO2 Trigonelline 138.05505 138.05496 0.69 [M+H]+ 94.06560, 110.06036 137.04772 c
9 2.363 C6H14O6 Dulcitol 181.07140 181.07176 −2.00 [M−H] 59.01288, 71.01292, 89.02358, 101.02363, 113.02368, 119.03424, 163.06085 182.07881 f
10 2.4 C18H32O16 D-Raffinose 503.16257 503.16176 1.61 [M−H] 71.01298, 89.02364, 101.02371, 161.04529, 179.05603, 21.06674, 341.10925, 383.12073 252.08499 f
11 2.631 C6H6O3 5-Hydroxymethyl-2-furaldehyde 127.03909 127.03897 0.94 [M+H]+ 53.03933, 55.01858, 69.03417, 81.03410, 97.02885, 99.04450, 109.02887 126.0318 f
12 2.717 C18H32O16 Manninotriose 503.16293 503.16176 2.33 [M−H] 59.01288, 71.01292, 89.02359, 101.02362, 113.02368, 179.05582, 323.09863 504.16997 f
13 3.014 C6H10O8 D-Saccharic acid 209.03020 209.03029 −0.43 [M−H] 85.02863, 133.01372, 191.01950 210.03749 f
14 3.034 C7H12O6 D- (-)-Quinic acid 191.05608 191.05611 −0.16 [M−H] 85.02864, 93.03379, 127.03932 192.06343 d
15 3.349 C7H10O5 Shikimic acid 173.04544 173.04555 −0.62 [M−H] 73.02864, 93.03384, 111.04452, 137.02388, 155.03461 174.05270 d
16 3.398 C24H42O21 Nystose 711.22162 711.22006 2.19 [M−HCOO] 89.02369, 179.05597, 341.10870, 485.15231 712.22890 f
17 3.788 C4H6O5 DL-Malic acid 133.01379 133.01425 −3.43 [M−H] 71.01298, 72.99225, 89.02362, 115.00304 134.02102 d
18# 3.978 C6H5NO2 Nicotinic acid 124.03958 124.03931 2.22 [M+H]+ 80.05000, 96.04480 123.03233 c
19 4.058 C6H8O7 Isocitric acid 191.01940 191.01973 −1.71 [M−H] 73.02858, 85.02864, 111.00803, 154.99809, 173.00880 192.02691 d
20 4.77 C5H8O5 D-α-Hydroxyglutaric acid 147.02939 147.02990 −3.45 [M−H] 85.02866, 101.02362, 129.01871 148.03675 f
21 4.933 C10H14N5O7P Adenosine 5′-monophosphate 348.07086 348.07036 1.43 [M+H]+ 97.02876, 136.06171 347.06369 e
22 4.977 C6H9NO5 N-Acetylaspartic acid 174.04066 174.04080 −0.78 [M−H] 58.02886, 88.03954, 114.01900, 115.00296, 130.05034 175.04816 f
23 5.491 C9H12N2O6 Uridine 243.06274 243.06226 1.98 [M−H] 66.03403, 80.96436, 82.02901, 110.02412, 140.03494, 152.03497 244.07004 e
24 5.687 C10H13N5O4 Adenosine 268.10410 268.10403 0.26 [M+H]+ 136.06178 267.09703 e
25 5.73 C10H13N5O3 2′-Deoxyadenosine 252.10928 252.10912 0.65 [M+H]+ 136.06174 251.10197 e
26* 5.916 C10H15NO Ephedrine 166.12265 166.12264 0.06 [M+H]+ 91.05464, 117.07005, 133.88620, 148.11197 165.11545 c
27 5.942 C4H6O4 Succinate 117.01866 117.01933 −5.74 [M−H] 73.02865 118.02597 f
28 5.955 C6H8O7 Citric acid 191.01970 191.01973 −0.14 [M−H] 85.02862, 87.00790, 111.00800 192.02703 d
29* 6.324 C10H15NO Pseudoephedrine 166.12283 166.12264 1.14 [M+H]+ 91.05473, 117.07014, 133.08873, 148.11209 165.11549 c
30 7.745 C10H14N5O8P Guanosine monophosphate (GMP) 362.05197 362.05072 3.45 [M−H] 78.95815, 96.96884, 211.00140 363.05888 e
31*# 8.347 C7H6O5 Gallic acid 169.01385 169.01425 −2.35 [M−H] 69.03363, 81.03369, 97.02866, 125.0237 170.02128 d
32 8.729 C9H13N2O9P Uridine monophosphate (UMP) 323.02969 323.02859 3.41 [M−H]- 78.95815, 96.96880, 111.01925, 211.00116, 280.02286 324.03689 e
33 11.238 C24H39NO7 Fuziline 454.28027 454.27993 0.75 [M+H]+ 58.06584, 91.05495, 108.08113, 436.26968 453.27286 c
34 11.396 C15 H14 O7 (-)-Gallocatechin 305.06720 305.06668 1.72 [M−H] 111.01923, 125.02370, 137.02383, 139.03947, 167.03459, 179.03474, 219.06602 306.07451 b
35 11.723 C24 H39 N O6 Neoline/Bullatine B 438.28485 438.28501 −0.38 [M+H]+ 58.06585, 72.08144, 154.12248, 356.22226, 388.24823, 40.27438 437.27785 c
36 11.795 C11 H12 N2 O2 DL-Tryptophan 205.09749 205.09715 1.64 [M+H]+ 118.06528, 144.08078, 146.05997, 188.07050 204.09006 f
37# 11.864 C9 H17 N O5 D-Pantothenic acid 220.11826 220.11795 1.41 [M+H]+ 90.05545, 184.09686, 202.10739 219.11097 f
38 16.79 C15 H14 O7 Epigallocatechin 305.06769 305.06668 3.32 [M−H] 125.02388, 137.02390, 139.03970, 146.96075, 167.03452, 219.06607 306.07458 b
39# 17.344 C15 H14 O6 Catechin 291.08627 291.08631 −0.15 [M+H]+ 123.04415, 139.03891, 165.05458, 207.06520 290.0794 b
40 18.397 C30 H26 O12 Procyanidin B2 577.13727 577.13515 3.67 [M−H] 125.02375, 289.07248, 407.07782, 425.08853, 451.10336 578.14391 b
41# 18.703 C7H6O3 4-Hydroxybenzoic acid 137.02391 137.02442 −3.70 [M−H] 93.03376 138.03111 d
42 19.587 C25H28O16 Neomangiferin 583.13129 583.13046 1.43 [M−H] 259.02521, 271.02524, 301.03583, 331.04657, 463.08945, 493.10025, 565.12091 584.13842 b
43 20.165 C16H18O9 Chlorogenic acid 353.08875 353.08781 2.68 [M−H] 93.03376, 135.04451, 173.04506, 179.03484, 197.08098 354.09586 d
44 21.818 C16H18O9 Neochlorogenic acid 353.08881 353.08781 2.85 [M−H] 93.03374, 135.04454, 137.02403, 155.03439, 161.02374, 173.04518, 179.03462, 191.05589 354.0959 c
45 22.336 C31H43NO10 Benzoylmesaconine 590.29657 590.29597 1.01 [M+H]+ 105.03376, 508.23425, 526.24207, 540.25806, 558.26996, 572.28595 589.28927 c
46 23.267 C32H45NO10 14-Benzoylaconine 604.31140 604.31162 −0.37 [M+H]+ 58.06588, 105.03393, 22.24713, 540.25989, 554.27557, 586.30200 603.30458 c
47* 24.008 C23H28O11 Paeoniflorin 479.15692 479.15588 2.16 [M−H] 121.02881, 165.05524, 327.10901 480.16384 f
48 24.3 C27H30O15 Vicenin II 593.15210 593.15119 1.53 [M−H] 297.07730, 353.06738, 383.07779, 473.10889 594.15905 b
49 24.301 C31H43NO9 Benzoylhypaconine 574.30139 574.30106 0.58 [M+H]+ 105.03392, 510.24741, 542.27515 573.29414 c
50* 24.378 C19H18O11 Mangiferin 421.07886 421.07763 2.91 M−H] 259.02515, 271.02536, 301.03586, 313.03635, 331.03654, 403.06775 422.0856 b
51 25.201 C21H20O9 Daidzin 417.11870 417.11801 1.66 [M+H]+ 255.06503 416.11157 b
52 26.292 C26H28O14 Isoschaftoside 563.14197 563.14010 3.32 [M−H] 297.07761, 325.07236, 353.06760, 383.07837, 473.11179, 503.12341 564.14971 b
53 26.668 C26H28O14 Schaftoside 563.14240 563.14063 3.15 [M−H] 297.07767, 325.07260, 353.06781, 383.07822, 473.10986, 503.12085 564.14936 b
54* 27.251 C22H28O11 Prim-O-glucosylcimifugin 469.17029 469.17044 −0.32 [M+H]+ 159.04407, 189.05478, 235.06035, 259.06036, 261.11224, 289.10660, 307.11780 468.16346 a
55 27.963 C11H10O5 Isofraxidin 223.06027 223.06010 0.76 [M+H]+ 208.03662, 207.02859, 190.02609, 162.03108 222.05307 f
56* 28.336 C21 H22 O9 Liquiritin 417.11996 417.11911 2.05 [M−H] 91.01820, 119.04967, 135.00833, 153.01900, 255.06694 418.12732 b
57# 28.467 C15 H12 O5 Naringenin 273.07587 273.07575 0.44 [M+H]+ 91.05486, 119.04942, 147.04416, 153.01834, 171.02895 272.06865 b
58 29.175 C21 H20 O10 Vitexin 433.11349 433.11292 1.31 [M+H]+ 121.02869, 283.06018, 284.06769, 295.06018, 297.07590, 323.09113, 337.07034, 367.08209, 379.08206, 397.09174, 415.10187 432.10647 b
59 29.885 C13 H14 N2 O3 N-Acetyl-DL-tryptophan 245.09361 245.09317 1.81 [M−H] 58.02889, 74.02384, 98.02391, 116.04982, 142.06566, 203.08252 246.1009 f
60 30.876 C25 H24 O12 4,5-Dicaffeoylquinic acid 515.12067 515.11950 2.27 [M−H] 93.03387, 135.04463, 173.04517, 179.03468, 191.05618, 353.08850 516.12813 d
61 31.018 C27 H30 O16 Rutin 609.14819 609.14611 3.42 [M−H] 151.00348, 163.00388, 243.02928, 255.03018, 271.02524, 300.02795, 301.03589 610.15485 b
62 31.246 C21 H20 O12 Quercetin-3β-D-glucoside 463.08932 463.08820 2.42 [M−H] 301.0358 464.09647 b
63 31.875 C28H32O15 Neodiosmin 609.18201 609.18140 1.01 [M+H]+ 463.12314, 301.07040, 286.04694 608.17468 b
64# 31.929 C14H6O8 Ellagic acid 300.99951 300.99899 1.73 [M−H] 185.02406, 229.01453, 283.99640 302.00671 d
65* 31.95 C22H28O10 5-O-Methylvisammioside 453.17548 453.17552 −0.10 [M+H]+ 203.07022, 216.04190, 219.06546, 231.06529, 243.06525, 273.11206, 291.12265 452.16824 a
66 32.033 C22H22O10 Glycitin 445.11533 445.11402 2.94 [M−H] 268.03809, 283.06165 446.12262 b
67 32.288 C22H22O9 Ononin 431.13351 431.13366 −0.34 [M+H]+ 197.06004, 213.09105, 237.05453, 254.05722, 269.08078 430.12644 b
68# 32.3 C16H12O4 Formononetin 269.08054 269.08084 −1.10 [M+H]+ 213.09065, 237.05464, 253.04924 268.0735 b
69# 32.332 C15H12O4 Isoliquiritigenin 257.08102 257.08084 0.72 [M+H]+ 119.04943, 137.02342, 147.04413, 239.07008 256.07377 b
70 32.333 C21H22O9 Isoliquiritin 419.13419 419.13366 1.27 [M+H]+ 137.02242, 147.04411, 257.08084 418.12693 b
71 32.334 C26H30O13 Liguiritigenin-7-O-β-D-apiosyl-4′-O-β-D-glucoside 549.16272 549.16136 2.47 [M−H]- 91.01807, 119.04951, 135.00814, 153.01881, 255.06662, 417.11978, 549.16260 550.16964 b
72 32.691 C28H32O16 Narcissoside 623.16333 623.16176 2.52 [M−H] 243.03006, 255.03008, 271.02542, 299.02017, 300.02780, 314.04361, 315.05154 624.17026 b
73 33.138 C16H14O5 Sakuranetin 287.09177 287.09140 1.29 [M+H]+ 107.04942, 121.02855, 193.04947, 245.08076 286.08462 b
74 33.929 C21H20O10 Afzelin 431.09949 431.09837 2.60 [M−H] 227.03510, 255.03023, 284.03299, 285.04083 432.10668 b
75 33.996 C16H16O6 Oxypeucedan hydrate 305.10223 305.10196 0.87 [M+H]+ 203.03397, 175.03937, 159.04427, 147.04416, 131.04932 304.09493 f
76# 34.073 C16H12O5 Biochanin A 285.07584 285.07575 0.32 [M+H]+ 137.02325, 213.05457, 225.05464, 253.04947, 270.05225 284.06887 f
77 34.216 C21H26O10 Sec-O-Glucosylhamaudol 439.16016 439.15987 0.65 [M+H]+ 277.10712, 259.09662, 241.08585, 217.04965, 205.04967, 189.05481 438.15352 a
78 34.667 C30H32O12 Benzoylpaeoniflorin 602.22327 602.22320 0.12 [M + NH4]+ 105.03391, 151.07552, 179.07045, 249.07570, 267.08633 601.21626 f
79 35.01 C16H14O4 Retrochalcone 269.08243 269.08193 1.85 [M−H] 108.02102, 133.02901, 161.02402, 209.06093, 237.05600 270.08970 b

*: reference standards, #: key active compounds by network pharmacology method, a: chromone compounds, b: flavonoids compounds, c: alkaloid compounds, d: phenolic acid compounds, e: nucleosides and nucleobases compounds, f:other types of compounds

3.1.1

3.1.1 Identification of chromone compounds

Chromone compounds are unique to Saposhnikovia divaricate (Turcz.) Schischk., which was demonstrated to inhibit arthritis (Kong et al., 2013). It is easy to make a conclusion that the class of components generally displayed [M+H]+ under the first-level mass spectrum. And under the secondary mass spectrometry, it mainly cracks in accordance with Retro-Diels-Alder (RDA) rule or loss of neutral fragment ions contained glucoside (1 6 2), methyl (15), H2O (18), CO (28), CO2 (44). It was just identified 3 chromone compounds from GSZD with databases, related literature, and reference standards. Compound 65 exhibited a [M+H]+ which the quasi-molecular ion at m/z = 453.17575, and the molecular formula was conjectured to C22H28O10. In the MS/MS spectrometry, at first, it became m/z = 291.12265 [M+H-C6H10O5]+ by losing glucose, and then separately decomposed into four fragment products of m/z = 273.11206 [M+H-C6H10O5-H2O]+, m/z = 243.06525 [M+H-C6H10O5-CH4O2]+, m/z = 231.06529 [M+H-C6H10O5-C3H8O]+, m/z = 219.06546 [M+H-C6H10O5-C4H8O]+ by losing some neutral fragment ions such as C3H8O, H2O, C4H80 or generating the RDA cleavage. M/Z = 216.04190 [M+H-C6H10O5-C3H8O-CH3]+, m/z = 203.07022 [M+H-C6H10O5-C3H8O- CO]+ fragment ion may be required by losing CH3, CO under m/z = 231.06529 fragment ion. In accordance with the database and the reference standard, compound 65 was determined to 5-O-methylvisammioside (Chen et al., 2018; Liu et al., 2018; Shao et al., 2018). The possible MS fragmentation pathway of 5-O-methylvisammioside is displayed in Fig. 3 A.

The possible fragmentation pathway of chemical. components. A shows compound 65; B shows compound 56 and.
Fig. 3
The possible fragmentation pathway of chemical. components. A shows compound 65; B shows compound 56 and.

3.1.2

3.1.2 Identification of flavonoids compounds

Flavonoids are comprehensively distributed in Chinese medicinal herbs with enormous pharmacological activities like neuroprotective, anti-inflammatory, anti-oxidant, and anti-tumor after referring to related literature (Duan et al., 2019; Piwowar et al., 2020; Zeng et al., 2020; Zhai et al., 2019). They are often conjugated with pentose, Hexose, and hexuronic acid. In accordance with the structure, they are roughly compartmentalized into flavonoids, flavonols, dihydroflavonoids, isoflavones, chalcones, etc. These compounds have roughly similarity in cleavage patterns, except for isoflavones. Under the circumstance of first-level mass spectrometry, these compounds can be monitored in both positive and negative ion modes. Furthermore, the characteristic fragments of glycosides were generally lost carbohydrate structure contained pentose (1 3 2), Hexose (1 6 2), hexuronic acid (1 7 6), as well as neutral molecular fragments contained CHO (15), H2O (18), CO (28), CO2 (44). Of course, RDA cleavage reaction also arose in the MS2. It was totally identified 26 flavonoids from GSZD, principally from three herbs (Anemarrhena asphodeloides Bge., Ephedrae sinica Stapf, Glycyrrhiza uralensis Fisch.). For instance, compound 56 displayed a [M−H] which the quasi-molecular ion at m/z 417.11996, and the molecular formula was conjectured to C21H22O9. In the MS/MS spectrum, after losing one molecule of glucose, the component became m/z = 255.0664[M-H-C6H10O5] which then decomposed into fragment product ions contained m/z = 153.01900, m/z = 135.00833, m/z = 119.04967, m/z = 91.1820 due to losing some neutral fragment ions include C3H8O, H2O, C4H8O or generating the RDA cleavage reaction. By comparison with chemical databases, literature as well as reference substance (Li, 2015; Zhou et al., 2004), which all demonstrated that compound 56 could be deemed to Liquiritin. Compound 71 bore a resemblance to the cleavage of compound 56, which they both possessed 417, 255, 153, 135, 119, and 91 ion fragments. Moreover, it displayed a [M−H] which the quasi-molecular ion at m/z 549.16272 as well as the predicted molecular formula was C26H30O13. As a consequence, the component was considered to Liguiritigenin-7-O-β-D-apiosyl-4′-O-β-D-glucoside, in accordance with the related literature (Yang et al., 2020b; Zhou et al., 2004). The possible MS fragmentation pathway of component 56 and 71 is displayed in Fig. 3B.

3.1.3

3.1.3 Identification of alkaloid compounds

Alkaloid compounds are comprehensively distributed in Chinese medicinal materials with enormously biological activity, whereas the majority of them may result in inevitably adverse effects. Such compounds manifested significant activities in inflammatory and tumor disease referred to research articles (Chen et al., 2020; Tong et al., 2013; Zheng et al., 2013). The class of components generally exhibited [M+H]+ under the conditions of first-level mass spectrometry. Losing the substituents in the MS/MS spectrum is a hallmark of a class of components, such as hydroxyl, amino, methoxy, acetyl, benzoyl, etc. Another identifying feature of the class of components is losing neutral fragment molecules that contain CO(28), H2O(18), NH2(16), CH3OH(32), CH3COOH(60), C7H6O2 (1 2 2), etc. It was totally identified 10 alkaloid constituents from GSZD, principally from three herbs (Ephedrae sinica Stapf, Processed Aconitum carmichaelii Debx.,and Anemarrhena asphodeloides Bge.). Compound 26 displayed a [M+H]+ which the quasi-molecular ion at m/z 166.12265, and the molecular formula was conjectured to C10H15NO, after losing one molecule of H2O, it became m/z = 148.11197[M+H-H2O]+ which then decomposed into fragment product ions contained m/z = 133.08862, m/z = 117.07005, m/z = 91.05464 due to losing the methyl, NH2, and vinyl. Component 26 was considered to Ephedrine by comparison with databases, related literature as well as reference standards (Meng et al., 2006). Component 29, which exhibited a [M+H]+ (m/z 166.12283), possessed predicted molecular formula (C10H15NO) identical to component 26 in the positive ion mode. Moreover, they both owned homogeneous product ion fragments at 148, 133, 117, and 91, It is not hard to infer that component 29 was Pseudoephedrine by comparison with reference standards. The possible MS/MS fragmentation pathway of Component 26 is manifested in Fig. 3C.

3.1.4

3.1.4 Identification of phenolic acid compounds

There are 10 phenolic acids confirmed from GSZD in total, which mainly from one herb named Paeonia lactiflora Pall. The class of components is generally concentrated in the negative ion mode. Furthermore, neutral fragment molecules contained CO (28), H2O (18), CO2 (44), C7H6O2 (1 2 2) can be deemed to identifying features for major phenolic acids. For example, compound 31, which displayed quasi-molecular [M−H] ion at m/z 169.1385, and the molecular formula was conjectured to C7 H6 O5, was decomposed into m/z = 125.0237[M-H-CO2] after undergoing neutral loss of CO2, then generated the fragmentation product of m/z = 97.02866, m/z = 81.03369, m/z = 69.03363 with losing CO and H2O. In agreement with the standard reference, compound 31 was deemed to gallic acid. Compound 44, with quasi-molecular ion at m/z 353.08881 [M−H] as well as the molecular formula was conjectured to C16 H18 O9, decomposed into four fragment products of m/z 191.05589, m/z 179.03462, m/z 161.02374, and m/z 135.04454. As a consequence, it was considered to Neochlorogenic acid while referring to the previous literature and database (Ouyang et al., 2017). The possible fragmentation pathway of compound 31 and 44 are revealed in Fig. 3D. the quasi-molecular ion and the MS2 information of compound 43 were keeping with compound 44. Consistent with the mzCloud and mzVault database, and it was regarded as Chlorogenic acid potentially.

3.1.5

3.1.5 Identification of nucleosides and nucleobases compounds

Nucleosides and nucleobases are commonly discovered in almost every herb, whereas omitted by scholars. Anyway, they manifest widespread biological activities beneficial to human health. It was identified 7 components from GSZD totally. Loss of ribose and NH3 can be deemed to a cleavage feature of nucleosides and nucleobases compounds. In compound 24, the quasimolecular [M+H]+ ion was at m/ z 268.104 and the molecular formula was conjectured to C10H13N5O4, only with a strong fragment ion at m/z 136.06178. Compound 24 was eventually deemed to be Adenosine, consistent with relevant literature (Yang et al., 2020a). The possible fragmentation pathway is exhibited in Fig. 3E.

3.1.6

3.1.6 Other types of compounds

Besides, sugars, amino acids, coumarins, vitamins, and terpenoids were identified from GSZD as well. carbohydrate constituents like D-Raffinose were decomposed into identical fragment ions of m/z = 59, m/z = 71, m/ z = 89, m/z = 179 on the condition of the negative ion mode. Moreover, such as compound 47, regarded as paeoniflorin in consistent with the reference substance that only discovered in Paeonia lactiflora Pall., possessed cleavage features mainly includes cracking glycosidic bonds, lossing sugar, benzoic acid as well as neutral molecules, result in forming characteristic fragment products with m/z = 121 and m/z = 121.

3.2

3.2 Identification of the key active compounds of GSZD and potential targets in treatment of GA

Through the combined use of multiple databases, after deleting duplicate and invalid targets, a total of 1297 putative compound targets and 12,229 GA-related targets were obtained. The Venn diagram found that there are 956 intersection targets (Fig. 4A), which indicates that GSZD has the effect of treating GA. In the compound-GA related target interaction network (Fig. 4B), there are 981 nodes and 13,577 edges linked to 25 compounds in GSZD and 956 targets related to GA. After topological analysis of the network, the compounds higher than the median degree were regarded as core active components, it was identified 11 in total, which were compounds 39, 64, 57, 31, 76, 69, 18, 68, 8, 41, 37. Among them, compound 39 has the largest degree value, while the Betweenness Centrality and Closeness Centrality values are also the largest, and the Average Shortest Path Length was also very small, indicating that this compound is very important in the whole network.

A stands the Venn of intersection targets; B stands the network of compounds and intersection targets; C stands the PPI network.
Fig. 4
A stands the Venn of intersection targets; B stands the network of compounds and intersection targets; C stands the PPI network.

For intersection targets, sort them according to the degree, Betweenness Centrality and Closeness Centrality values, take all the targets higher than the median, take the intersection, and finally get 88 targets. Import these 88 targets into the String database for analysis. In the String database, Select the species as “Homo sapiens”, set the minimum required connection score between the targets is 0.4, a PPI network was constructed, import the data into Cytoscape for visualization (Fig. 4 C), and perform network topology analysis at the same time, and the final analysis result shows that about the degree value of 29 targets were higher than median degree value, which was 31. In addition, according to the degree value from large to small, it is found that there is a relatively complicated relationship between the first 13 proteins. Except for JUN, CCND1, CXCL8, and MMP9, the other targets, TP53, AKT1, MAPK3, IL6, TNF, CASP3, MAPK1, PTGS2, ESR1, were all ranked high in the Betweenness Centrality and Closeness Centrality values, the Average Shortest Path Length, indicating that these targets played a crucial role.

The 10 targets screened in the component-GA target network analysis and the 13 targets screened in the PPI network analysis were intersected to obtain 4 targets, namely CXCL8, PTGS2, CASP3, and ESR1, implying these 4 targets may play a very critical role.

3.3

3.3 Key targts GO and pathway enrichment analysis

36 targets (list in Table 2), derived from 10 targets of the component-target network and 29 targets in the PPI network, were performed GO and pathway enrichment analysis. There were identified 24 biological processes (Fig. 5A) including the release of cytochrome c from mitochondria, embryonic placenta development, axtrinsic apoptotic signaling pathway in absence of ligand, intrinsic apoptotic signaling pathway in response to DNA damage, regulation of blood vessel endothelial cell migration, and so on, while corrected by a P ≤ 0.01, gene cluster ≥ 6, accounting for more than 5%genes, go tree interval from 7 to 8 level, and kappa score was 0.4. In addition, 14 molecular functions were identified (Fig. 5B) when corrected by a P ≤ 0.01, gene cluster ≥ 4, accounting for more than 4%genes, go tree interval from 4 to 8 level, and kappa score was 0.4. including cysteine-type endopeptidase activity involved in the apoptotic signaling pathway, activation of cysteine-type endopeptidase activity involved in the apoptotic process, hydro-lyase activity, negative regulation of cysteine-type endopeptidase activity involved in the apoptotic process, protein serine/threonine/tyrosine kinase activity, nitric-oxide synthase activity, and so on. Only one cellular component was identified with the default parameters.

Table 2 36 key targets.
Abbreviation Target Name
TP53 Cellular tumor antigen p53
AKT1 RAC-alpha serine/threonine-protein kinase
MAPK3 Mitogen-activated protein kinase
IL6 Interleukin-6
TNF Tumor necrosis factor
CASP3 Caspase-3
MAPK1 Mitogen-activated protein kinase 1
JUN Transcription factor AP-1
CCND1 G1/S-specific cyclin-D1
PTGS2 Prostaglandin G/H synthase 2
CXCL8 Interleukin-8
MMP9 Matrix metalloproteinase-9
ESR1 Estrogen receptor
CYCS Cytochrome c
FOS Proto-oncogene c-Fos
NOTCH1 Neurogenic locus notch homolog protein 1
MMP2 72 kDa type IV collagenase
CCL2 C-C motif chemokine 2
HMOX1 Heme oxygenase 1
CDKN1A Cyclin-dependent kinase inhibitor 1
IL1B Interleukin-1 beta
ICAM1 Intercellular adhesion molecule 1
CASP8 Caspase-8
PECAM1 Platelet endothelial cell adhesion molecule
RELA Transcription factor p65
HIF1A Hypoxia-inducible factor 1-alpha
IL2 Interleukin-2
SERPINE1 Plasminogen activator inhibitor 1
CASP9 Caspase-9
SNAI1 Zinc finger protein SNAI1
MAP2K1 Dual specificity mitogen-activated protein kinase kinase 1
CA4 Carbonic anhydrase 4
CA7 Carbonic anhydrase 7
CYP1B1 Cytochrome P450 1B1
CA12 Carbonic anhydrase 12
BCL2 Apoptosis regulator Bcl-2
A stands GO analysis of Biological processes. Note: PV ≤ 0.01, Cluster 5%, Kappa score is 0.4. B stands GO analysis of molecular functions. Note: PV ≤ 0.01.
Fig. 5
A stands GO analysis of Biological processes. Note: PV ≤ 0.01, Cluster 5%, Kappa score is 0.4. B stands GO analysis of molecular functions. Note: PV ≤ 0.01.

After the KEGG analysis, it was determined that there are a total of 15 pathways (Fig. 5C)(P ≤ 0.01) involved in the treatment of GA, including the HIF-1 signaling pathway, Toll-like receptor signaling pathway, C-type lectin receptor signaling pathway, IL-17 signaling pathway, TNF signaling pathway, etc. In addition, the outcome of Reactome pathway enrichment analysis is shown in (Fig. 5D). A total of 256 pathways have been identified when the P ≤ 0.05. Among them, the 15 most relevant pathways sorted by P contained Interleukin-4 and Interleukin-13 signaling, Signaling by Interleukins, Interleukin-10 signaling, Cytokine Signaling in Immune system, Immune System, Extra-nuclear estrogen signaling, Estrogen-dependent nuclear events downstream of ESR-membrane signaling, ESR-mediated signaling, Intrinsic Pathway for Apoptosis, Senescence-Associated Secretory Phenotype (SASP), Cellular Senescence, Signaling by Nuclear Receptors, CLEC7A/inflammasome pathway, Transcriptional Regulation by VENTX, Cytochrome c-mediated apoptotic response. By analyzing the data obtained in the above two ways, it is not difficult to find that GSZD may be acted on the immune system and inflammatory pathways like TNF signaling pathway, HIF-1 signaling pathway, IL-17 signaling pathway, IL-4 and IL-13 signaling, IL-10 signaling, Cytokine signaling in the immune system, and so on for treating GA. In hence, GSZD was mainly used for GA through the anti-inflammatory immune mechanism.

In order to better display the relationship of prescriptions, herbs, main active ingredients, targets and pathways, we use Cytoscape to build GSZD-herb-key active component-pathway network diagram for visualization (in Fig. 6).

The “GSZD-herb-key active component-pathway” pharmacological network. diagram.
Fig. 6
The “GSZD-herb-key active component-pathway” pharmacological network. diagram.

4

4 Discussion

Clinical cases have certificated that patients with GA could significantly mitigate symptoms, including reducing the level of uric acid, erythrocyte sedimentation rate, and IL-6, after taking GSZD, meanwhile, without any bothersome adverse effects (Zhang et al., 2020). The GSZD, as mentioned above, is a mix of water- extract and how to improve the symptoms of patients is still unclear. Therefore, exploring the active ingredients of GSZD in the treatment of GA and confirming their underlying mechanism is a promising approach for open up the clinical applications of GSZD.

In the study, we utilized UHPLC-Q-Orbitrap HRMS technology, relying on databases, relevant literature, and reference materials, a total of 79 compounds, including 3 chromones, 26 flavonoids, 10 alkaloids, 10 phenolic acids, 7 nucleosides and nucleobases, and 23 other components, were identified. Moreover, some new components like Afzelin, Sakuranetin, Narcissoside were never reported, Besides, the reason why we used, in the early development of GSZD, to explored the HPLC method, we investigated different extraction methods (ultrasound, shaking, reflux), different ultrasonic time (10 min, 20 min, 30 min, 40 min, 50 min), different extraction solvents (25% methanol, 50% methanol, 75% methanol, methanol, ethanol), and the multiple of solvent (0.5 g → 5 ml, 15 ml, 25 ml, 35 ml, 50 ml)with mangiferin, paeoniflorin, cinnamic acid and glycyrrhizic acid as indexes, it was found 50 fold 75% methanol and ultrasonic extraction 30 min was more helpful to the dissolution of selected index components. Although there is a certain difference from the water extract taken by clinical patients, according to the principle of similar compatibility, the most active ingredients also can be obtained to a certain extent. Via network pharmacology analysis, 11 active components were regarded to be effective on GA, and 36 targets, especially CXCL8, PTGS2, CASP3, ESR1, were screened to be beneficial to GA.

4.1

4.1 Active components

Through network pharmacological analysis, 11 main active ingredients were finally obtained. Through a literature search, these 11 compounds were found to treat GA’s clinical symptoms in terms of inhibiting inflammatory factors, inflammatory pathways, and reducing uric acid (Fikry et al., 2019; Gershon and Fox, 1974; Kole et al., 2011; Mansouri et al., 2013; Owona et al., 2020; Scalabrino and Pasquariello, 1964). For example, compound 39(Catechin) was confirmed to inhibit MSU-induced IL-1β secretion and NLRP3 inflammasome activation against the gout attack. Meanwhile, it also demonstrated that gallic acid (compound 31) suppressed the release of IL-1β secretion in vivo (Jhang et al., 2015). Besides, gallic acid also alleviated GA by suppressed NLRP3 inflammasome activation as well as pyroptosis dependent on Nrf2 signaling (Lin et al., 2020a). Naringenin not only suppressed MSU-induced histopathological changes, but also inhibited cytokine production, leukocyte recruitment, oxidative stress, NFκB activation, NLRP3 inflammasome components mRNA expression, and IL-1β maturation in cultured macrophages to ameliorate gout-induced joint and inflammation, moreover, without any inducing liver and kidney toxicity (Ruiz-Miyazawa et al., 2018). Although not relevant references about Ellagic acid treat GA, Ellagic acid not only has an obvious effect on the central and peripheral antinociceptive in different animal models of pain (Mansouri et al., 2013), but also showed inhibition of neutrophil infiltration and TNF-α and IL-1β production mightily (Mo et al., 2013), as well as inhibited inflammatory conditions in IL-1β induced human chondrocytes (Lin et al., 2020b), these predicted that Ellagic acid may also have treatment in GA.

4.2

4.2 Potential therapeutic targets

GA, mainly induced by excessive deposition of MSU crystals in the joint space, triggers inflammatory cycle response including massive recruitment of infiltrating neutrophils, synovial cells, and tissue macrophages, eventually appeared to symptoms of joint pain, swelling, and stiffness. We discovered 36 key targets through PPI networks analysis, especially CXCL8, PTGS2, CASP3, ESR1, which are more or less considered to affect GA. Among these targets, IL-1B has been considered to be crucial to gouty inflammation (Indramohan et al., 2018; So et al., 2018), MAPK1 is one of the indicators of inflammation evaluation, and TNF is mainly produced by activated mononuclear macrophages, which is important of inflammatory mediators. PTGS2, also called COX-2, has been confirmed to be involved in MSU-induced inflammation in human monocytes (Pouliot et al., 1998). Moreover, COX-2 inhibitors have been developed clinically to treat GA (Qaseem et al., 2017) CXL8, also named IL-8, promoted apoptosis and suppressed the proliferation of chondrocytes (Yang et al., 2016). ESR1, one type of estrogen receptor, is expressed in skeleton cells, including stromal cells, osteoblasts, and chondrocytes (Syed and Khosla, 2005). And relevant references had demonstrated that ESR1 targeted with the binding of E2 could promote the proliferation of human chondrocytes in vitro by suppressing the activation of the ERK signaling pathway to stimulate cell autophagy and induce cell apoptosis possibly (Liu et al., 2019). Caspases, a member of cysteine proteases, play a vital role in apoptotic cell death. Although there is no related literature on Caspases-3 and GA, Caspases-3 was confirmed to induce chondrocyte apoptosis in osteoarthritis (Matsuo et al., 2001).

4.3

4.3 Pathway analysis

Through KEGG and Reatome pathway analysis, it is found that GSZD treats GA mainly through the immune system, inhibiting multiple inflammatory pathways and related inflammatory factors, including HIF-1signaling pathway, Toll-like recepotor signaling pathway, IL-17 signaling pathway, Interleukin-4 and Interleukin-13 signaling, signaling by Interleukins, Interleukin-10 singnaling, Cytokine signaling in immune system. By consulting the relevant literature, it is found that these pathways are the most researched pathways that induce GA.

4.4

4.4 The value of our study

In this study, the advantage of this experiment is that we used the method of UHPLC-Q-Orbitrap HRMS to increase the total number of chemical constituents of GSZD. Secondly, we obtained the bioactive compounds by the method of network pharmacology, and found that GSZD in the treatment of GA is mainly by acting on multiple inflammatory pathways, changing the existing studies proved to inhibit Toll-MyD88 and NLRP3 inflammatory pathways. In addition, through the method of UHPLC-Q-Orbitrap HRMS combined with network pharmacology, starting from the ingredients, the mechanism of action of drugs in the treatment of diseases was clarified, taking the GSZD as an example. However, we have to admit that our experimental research has some limitations. First of all, based on the previous pharmaceutical research of the research group, we chose 75% methanol as the solvent to analyze the effective components of GSZD, which is far from enough, for some macromolecular substances such as polysaccharides, our experiments are not involved. Secondly, this study is only based on our existing chemical components to study the efficacy and predict the active components and action mechanism, although some new possible compounds have been found, but lack of experimental verification. Therefore, in the next step, a comprehensive study of the mechanism of GSZD in the treatment of GA provides some references and suggestions, which is more conducive to experimental research.

5

5 Conclusions

All in all, Using UHPLC-Q-Orbitrap HRMS, it was identified 79 components totally, which contained 3 chromones, 26 flavonoids, 10 alkaloids, 10 phenolic acids, 7 nucleosides and nucleobases, and 23 other components. Through network pharmacology analysis, 11 potential key active ingredients and 36 potential targets were identified, these 11 core active components may be mainly ameliorated the symptoms of GA by acting on multiple inflammatory pathways. In the previous work, the research is mainly aimed at the pharmaceutical part of GSZD, hoping to develop the prescription into a commodity through research, and the pharmacological research is mainly aimed at the study of rheumatoid arthritis. In order to better expand the application scope of the commercial GSZD, we refer to the relevant literature to turn the treatment of GSZD to GA. Secondly, in the part of the previous pharmaceutical research, we found that the dosage of the prescription was relatively large. We hope that through the study on the basis of pharmacodynamics, we can find out the mechanism of GSZD in the treatment of GA, and through the study of active ingredients, extract the relevant active ingredients, which can not only reduce the dosage of GSZD, but also effectively play a role in the treatment of diseases. This study lays a solid foundation for further research on GSZD in the treatment of GA.

6

6 Ethics approval and consent to participate

Not applicable.

Acknowledgements

Not applicable.

Funding

Availability of data and materials.

The research data generated from this study is included within the article.

The study was funded by the National Science and Technology Major Project for 'Significant New Drugs Creation'. It comed from the project of 'Research and Development of New Drugs of Classical Famous Prescription Guizhi-Shaoyao-Zhimu Decoction Based on Consistency Evaluation' (No.: 2018ZX09721004-009).

Consent for publication

Not applicable.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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