1Department of Integrated Traditional Chinese and Western Medicine, Anhui University of Chinese Medicine, Hefei 230012, China;
2Research Institute of Integrated Traditional Chinese and Western Medicine, Anhui Academy of Chinese Medicine, Hefei 230012, China
Liquiritin is beneficial to cardiovascular diseases, including myocardial hypoxia/reoxygenation (H/R) injury, myocardial hypertrophy, and acute myocardial infarction (AMI). However, the mechanism of liquiritin on AMI is unknown. This study is of great significance for elucidating the mechanism of liquiritin in preventing and treating AMI and developing cardiovascular protective drugs. Network pharmacology and molecular docking were used to screen the targets of liquiritin. AMI rats were built by coronary left anterior descending ligation. Echocardiography was used to monitor cardiac function; HE staining was used to detect pathological changes, and cardiac enzymes were detected. The expressions of COX-2, NLRP3, Caspase-1, ASC, and GSDMD were detected by RT-PCR and Western Blot. ELISA was used for the detection of IL-1β and IL-18 expression. COX-2 was detected as the most considerable protein in the PPI network. Molecular docking predicted that liquiritin has a high binding affinity with COX-2. AMI model rats showed significantly lower EF and FS (P<0.01) and increased LVIDd and LVIDs (P<0.01), which were improved by liquiritin. Liquiritin significantly reduced cardiac pathological changes and decreased LDH, CK, cTn-I, and BNP levels. Liquiritin reduced the mRNA and protein expressions of COX-2, NLRP3, Caspase-1, ASC, and GSDMD. Liquiritin inhibited IL-1β and IL-18 overexpression. Liquiritin has a better effect against AMI, and its mechanism is related to inhibiting the COX-2/NLRP3 signaling pathway.
Key words: acute myocardial infarction, COX-2/NLRP3 signaling pathway, liquiritin, molecular docking, network pharmacology
*Corresponding Authors: Jing-ya Li, Department of Integrated Traditional Chinese and Western Medicine, Anhui University of Chinese Medicine, Hefei 230012, China. Email: [email protected]; Liang Wang, Department of Integrated Traditional Chinese and Western Medicine, Anhui University of Chinese Medicine, Hefei, 230012, China. Email: [email protected]; Peng Zhou, Research Institute of Integrated Traditional Chinese and Western Medicine, Anhui Academy of Chinese Medicine, Hefei 230012, China. Email: [email protected]
Received: 24 January 2024; Accepted: 28 February 2024; Published: 1 April 2024
© 2024 Codon Publications
This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0). License (http://creativecommons.org/licenses/by-nc-sa/4.0/)
Acute myocardial infarction (AMI) can cause irreversible damage to functional myocardial cells, negative remodeling of the myocardium, and progressive deterioration of cardiac function (Zhou et al., 2023). Despite the progress made in the treatment of myocardial infarction, many patients with AMI still die prematurely, and those who survive are still at risk of developing heart failure, suggesting that current AMI therapy still lacks key pathophysiologic mechanisms and effective drugs (Gong et al., 2021). Ventricular remodeling (VR) after AMI plays a very important role in the development of chronic heart failure (CHF) (Frantz et al., 2022). In particular, VR after AMI can further lead to the onset and progression of CHF. Therefore, the curtailment of VR after AMI can significantly reduce the incidence of CHF.
Network pharmacology is a research field based on the disciplines of systems biology, genomics, and proteomics, which combines computational analysis with in vivo and in vitro experiments and integrates a large amount of information to discover new drug targets and molecular mechanisms, which is particularly applicable to multi-component and multi-targeted traditional Chinese medicine (TCM) combinations for the treatment of chronic diseases (Yang et al., 2022; Zhao et al., 2023). Network pharmacology can be used to predict the mechanism of natural products for treating diseases, which can help to quickly find the target of natural products (Li et al., 2017).
During the last two decades, natural products have been recognized as ideal candidates for preventing and treating diseases due to their lack of apparent toxicity and versatile biological properties (Rao et al., 2019). The efficacy and mechanism of natural products in treating AMI have major advantages. Licorice is an important traditional Chinese herb derived from the dried roots and rhizomes of the Glycyrrhiza plants, which is used worldwide in food and medicine (Wahab et al., 2021; Yang et al., 2017). Because of its sweet taste, licorice is an essential ingredient in foods such as candy, chewing gum, and beverages (Liu et al., 2022). Liquiritin is a flavonoid derived from licorice, a widely used traditional Chinese medicine with the effects of anti-oxidative stress, anti-inflammation, and anti-apoptosis (Qin et al., 2022). Liquiritin has good effects against septic cardiomyopathy, myocardial hypoxia/reoxygenation (H/R) injury, myocardial hypertrophy, diabetic cardiomyopathy, and AMI, and therefore, it is more often used in CVDs (Zhang et al., 2016; Mou et al., 2021; Thu et al., 2021; Aiyasiding et al., 2022). Previous studies have found that the effect of liquiritin against AMI was associated with its inhibition of the TLR4/MyD88/NF-κB signaling pathway (Zhou et al., 2022). However, the mechanism of liquiritin in the preventing and treating AMI is not clear.
This study utilized network pharmacology and molecular docking o predict the most likely targets of liquiritin on AMI. Finally, the predicted targets of liquiritin against AMI were experimentally validated using in vivo experiments to illustrate the mechanism of liquiritin fully.
Liquiritin was collected in the PubChem database and saved the structure in the SDF format. Swiss Target Prediction database was used for the target prediction of liquiritin (the screening condition: Probability>0) (Gfeller et al., 2014).
The “Acute myocardial infarction (AMI)” keyword is used to obtain human genes from the GeneCards, NCBI, and DisGeNET databases. The targets obtained from the GeneCards database were screened by median values according to scores to obtain more relevant targets (Gfeller et al., 2014).
Common targets for liquiritin and AMI were collected by Venny (version 2.1). Cytoscape software (version 3.7.2) was used to construct and visualize the “component-disease-target” network.
The potential targets of liquiritin in treating AMI were imported into the STRING database (https://string-db.org/cgi/input.pl). The protein type was set to “Homo sapiens” and PPI network data was obtained. The results were visualized using Cytoscape software, the topological properties were analyzed by a network analyzer, and the core targets of liquiritin in treating AMI were screened.
GO enrichment analysis focuses on three areas, including biological processes (BP), cellular components (CC), and molecular functions (MF), with corrected P < 0.05 were selected as screening indexes. KEGG pathway enrichment analysis was performed on the common targets of drugs and diseases, and the corrected P < 0.05 was screened using the String database. R software (version R 4.0.3), clusterProfiler, enrichplot, and ggplot2 were used to draw the histogram and bubble diagram.
CB-dock website was used to predict the binding affinity of liquiritin and COX-2. (1) Cyclooxygenase-2 (COX-2) (PDB ID: 5KIR) was downloaded from RCSB (Orlando & Malkowski, 2016). We optimized the COX-2 with a focus on water molecules and hetatoms. One hundred fifty-four water molecules and 454 other hetatoms were deleted from the uploaded COX-2. (2) The structure of liquiritin was downloaded from Pubchem and then optimized for the lowest energy. (3) COX-2 and liquiritin were input to CB-Dock for molecular docking (Liu et al., 2020). NS-398, a specific inhibitor of COX-2, was used as a control. The VINA score represents the binding affinity between liquiritin and COX-2, with higher scores indicating better binding affinity.
Liquiritin (551-15-5) was purchased from Nanjing Spring & Autumn Biological Engineering Co.Ltd. Trizol (G3013) and SYBR (G3326-15) were purchased from Servicevbio Biotechnology Co.Ltd. (Wuhan, China). Interleukin (IL)-1β (MM-0047R1), IL-18 (MM-0194R1), and brain natriuretic peptides (BNP, MM-0067R1) were bought from Meimian (Jiangsu, China). Lactate dehydrogenase (LDH, A020-2-2) and creatine kinase (CK, A032-1-1) were purchased from Nanjing Jiancheng Bioengineering Insitute (China). Rat cardiac troponin I (cTn-I, Cat.# RX302234R) was bought from Quanzhou Ruixin Biotechnology Co., Ltd (China). Anti-Cleaved-caspase-1 (AF4005), anti-ASC (DF6304), anti-tubulin(AF7011), and anti-COX-2 (AF7003) were purchased from Affinity Biosciences. Anti-NLRP3 AB263899) and anti-GSDMD (ab219800) were purchased from Abcam. Anti-GAPDH (380626) was purchased from ZEN-BIO Science (Chengdu, China).
As previously described, AMI model rats were constructed by ligating the left anterior descending (LAD) coronary artery. Briefly, Sprague-Dawley rats (male, 180 ± 20g, provided by Liaoning Changsheng Biotechnology Co., Ltd, with manufacturing license SCXK (Liao) 2020-0001 were anesthetized with isoflurane (Pilz et al., 2020). The left thoracic cavity of the rats was opened and ligated with 6-0 silk thread 2 mm below the left atrial appendage. The rats in the sham group only underwent thoracotomy with perforation and no ligature. This study was approved by the Animal Ethics Review Committee of Anhui University of Chinese Medicine (No. AHUCM-2023012).
Two weeks later, rats with AMI were randomly assigned to three groups: model (i.g. normal saline), liquiritin (i.g. 20 mg/kg) (Han et al., 2022), captopril (i.g. 4.375 mg/kg) groups. All interventions were conducted for four weeks.
All rats were anesthetized with 1% sodium pentobarbital by intraperitoneal injection. Two-dimensional M-mode echocardiography was applied to examine cardiac function in all groups of rats, and after locating the ventricles, the LV motion curves were recorded. The parameters of ejection fraction (EF), fractional shortening (FS), left ventricular internal diameter diastolic (LVIDd), left ventricular internal diameter systolic (LVIDs), left ventricular end-diastolic volume (LVEDV), and left ventricular end-systolic volume (LVESV) were measured.
HE staining was used to observe the pathological changes.
After blood collection, the rats were left for 2 h, centrifuged for 10 min (3000 rpm/min), and the supernatant was collected and frozen at -20 °C. The contents of IL-1β, IL-18, BNP, and cTnI in the serum of rats were detected according to the kit instructions.
Rat serum LDH and CK activities were assayed according to the kit instructions. Fluorescence was measured on a SpectraMax i3x microplate reader.
Rat myocardial tissue was taken, total RNA was extracted by Trizol reagent, then Eppendorf BioPhotometer Plus quantified RNA, and RNA purity was determined by absorbance at 260 and 280 nm. RNA was reverse transcribed into cDNA using a Mastercycler® nexus gradient (Germany). The cDNA was then subjected to real-time fluorescence quantification using a LightCycler® 96 PCR instrument (Roche, Switzerland). The amplification procedure consisted of pre-denaturation at 95 °C for 5 min, denaturation at 95 °C for 15 s, annealing at 60 °C for 60 s, and PCR at 40 cycles. The melting curve is from 60 °C to 95 °C. The mRNA expression levels of the genes were analyzed by the 2-ΔΔCq method using β-actin as a control. The primer sequence for COX-2 (Forward: 5'-CACATTTGATTGACAGCCCACCAAC-3', Reverse: 5'-AGTCATCAGCCACAGGAGGAAGG-3'), NLRP3 (Forward: 5'-GAGCTGGACCTCAGTGACAATGC-3', Reverse: 5'-AGAACCAATGCGAGATCCTGACAAC-3'), ASC (Forward: 5'-ATGGTTTGCTGGATGCTCTGTAT-3', Reverse: 5'-CAGCAACATCCTGGCAGTCATCC-3'), Caspase-1 (Forward: 5'-GCACAAGACTTCTGACAGTACCTTCC-3', Reverse: 5'-GCTTGGGCACTTCAATGTGTTCATC-3'), GSDMD (Forward: 5'- CAGCAGGCAGCATCCTTGAGTG-3', Reverse: 5'-CCTCCAGAGCCTTAGTAGCCAGTAG-3'), and β-actin (Forward: 5'-CCCATCTATGAGGGTTACGC-3', Reverse: 5'-TTTAATGTCACGCACGATTTC-3') were used in the study.
Total protein was extracted after the cardiac tissue had been dissolved in lysate. Lysates were separated on 10% to 15% polyacrylamide gels and then transferred to PVDF membranes. The PVDF membrane was blocked with 5% skim milk and then incubated with COX-2 (1:1000), NLRP3 (1:1000), ASC (1:1000), Cleaved-Caspase-1 (1:500), GSDMD (1:1000), Tubulin (1:5000) and GAPDH(1:5000) at 4 °C overnight. The secondary antibody was incubated overnight at 4 °C and then treated with the primary antibody for 2 h at room temperature. The ECL chemical substrate luminescence kit was used to determine the protein band density, and the Tanon5200 imaging system (Tanon, China) was used to photograph the protein bands.
The data were presented as mean±standard deviation (SD), and SPSS 26.0 was used for statistical analysis. One-way ANOVA was used to determine the difference. P<0.05 was considered statistically significant.
Seventy-four potential targets of liquiritin were obtained. Disease targets were then searched in the GeneCards, NCBI, and DisGeNET databases, and a total of 2200 genes associated with AMI were obtained. Finally, the common targets of liquiritin and AMI were obtained and plotted by Venn diagrams, that is, 40 targets were the potential targets of liquiritin for the treatment of AMI (Figure 1).
Figure 1. The Venn diagram of the common targets of liquiritin and AMI The 40 common targets for liquiritin in the treatment of AMI.
Protein interaction information obtained from the String database was put into Cytoscape to generate a PPI network (Figure 2). The network has 40 nodes and 94 edges with an average degree of 4.7. PTGS2 (COX-2), ESR1, and PPARG were the top 3 targets. COX-2 was considered the most important target in the PPI network for relevance to AMI.
Figure 2. PPI network diagram. The graph shows the interrelationships among 40 common targets.
GO enrichment analysis revealed 473 BP terms, 22 CC terms, and 39 MF terms. The top 10 entries in each section were shown according to the number of enriched genes (Figure 3).
Figure 3. GO enrichment analysis. BP diagram, CC diagram, and MF diagram. BP, CC, and MF column colors indicate enrichment significance based on adjusted P-value.
According to the KEGG analysis, a total of eight enrichment pathways were screened (Figure 4). The color corresponds to the size of the adjusted P-value. This suggests that liquiritin can be used to treat AMI through chemical carcinogenesis-receptor activation, and peroxisome. Peroxisome is closely related to inflammatory response, which may be the main mechanism.
Figure 4. KEGG enrichment analysis. The horizontal axis represents importance according to the corrected P-value.
VINA score of liquiritin was higher than that of the COX-2 inhibitor (NS-398) (Table 1 and Figure 5), which showed that liquiritin has a high binding affinity. The results indicated that liquiritin may act on COX-2.
Table 1. Docking of liquiritin with COX-2
Chemicals | Vina score | Cavity score | Center (x, y, z) |
Size (x, y, z) |
---|---|---|---|---|
Liquiritin | –9.2 | 17137 | 20, 15, 29 | 35, 35, 35 |
NS-398 | –7.6 | 17137 | 20, 15, 29 | 35, 35, 35 |
Figure 5. The 3D pictures of liquiritin with COX-2. (A) Liquiritin-COX-2 complex, (B) NS-398- COX-2 complex.
The results showed that EF and FS were decreased (P<0.01), LVIDd, LVIDs, LVEDV, and LVESV were increased in the model group (P<0.01). Compared with the model group, the levels of the EF, FS LVIDd, LVIDs, LVEDV, and LVESV were reversed in the liquiritin group (P<0.01) (Figure 6). Liquiritin could significantly improve cardiac impairment in AMI rats.
Figure 6. Effect of liquiritin on cardiac function in AMI rats. (A) Echocardiogram of each group. (B) EF. (C) FS. (D) LVIDs. (F) LVIDd. (F) LVEDV. (G) LVESV. Compared with the sham group, **P<0.01, Compared with the model group, ##P<0.01.
HE staining results showed that the myocardium of rats in the sham group was structurally intact, with myofibrils aligned neatly. Meanwhile, rats in the model group had more disorganized myocardial fibers, myocardial fiber breaks, and inflammatory cell infiltration. Liquiritin resulted in aligned myocardium and less inflammatory cell infiltration in AMI model rats, improving myocardial injury caused by AMI (Figure 7).
Figure 7. Effect of liquiritin on pathological changes of AMI rats.
Serum levels of BNP, CK, cTn-I, and LDH were significantly higher in the model group (P<0.01), which was significantly ameliorated in the liquiritin and Captopril groups (P<0.01) (Figure 8). The results indicated that liquiritin was able to significantly reduce the serum levels of cardiac enzymes in AMI rats.
Figure 8. Effect of liquiritin on serum myocardial enzyme level in AMI rats. (A) BNP. (B) CK. (C) cTnI. (D) LDH. Compared with the sham group, **P<0.01, Compared with the model group, ##P<0.01.
As shown in Figure 9, COX-2, NLRP3, Caspase-1, ASC, and GSDMD mRNA expressions were increased in the model group (P<0.01). Liquiritin could significantly reverse the mRNA expressions (P<0.01).
Figure 9. Effect of liquiritin on the expression of key genes in the COX-2/NLRP3 pathway (A) COX-2 mRNA. (B) NLRP3 mRNA. (C) Caspase-1 mRNA. (D) ASC mRNA. (E) GSDMD mRNA. Compared with the sham group, **P<0.01, Compared with the model group, ##P<0.01.
The protein expression of COX-2, NLRP3, ASC, Cleaved-Caspase-1, GSDMD, and GSDMD-N were increased in the model group (P<0.05, P<0.01). After administration of liquiritin or Captopril, the protein expression was significantly reduced (P<0.05, P<0.01) (Figure 10). Liquiritin could reduce the inflammatory response occurring in the heart of AMI rats by modulating the COX-2/NLRP3 pathway.
Figure 10. Effect of liquiritin on the protein expression of COX-2 and NLRP3. (A) COX-2. (B) NLRP3. (C) ASC. (D) Cleaved-Caspase-1. (E) GSDMD. (F) GSDMD-N. Compared with the sham group, *P<0.05, **P<0.01. Compared with the model group, #P<0.05, ##P<0.01.
The level of IL-1β and IL-18 were significantly elevated in the model group (P<0.01), whereas the expressions were significantly inhibited in the liquiritin or Captopril groups (P<0.05, P<0.01) (Figure 11). Therefore, liquiritin could inhibit inflammatory injury in AMI rats.
Figure 11. Effect of liquiritin on the release of inflammatory factors in AMI rats. (A) IL-1β. (B) IL-18. Compared with the sham group, **P<0.01, Compared with the model group, #P<0.05, ##P<0.01.
AMI is a common CVDs that occurs when circulation to an area of the heart is blocked, and myocardial tissue is necrotic. Accompanied by increasing risk factors such as hypertension, dyslipidemia, and diabetes mellitus, the incidence of AMI has shown a rising trend, thus posing a serious threat to the health and quality of life of patients with AMI (Lee et al., 2018). Currently, AMI is usually treated by reperfusion of the ischemic myocardium to save the dying myocardium, and clinical drugs used to treat AMI include thrombolytic and antiplatelet agents, anticoagulants, nitrates, and calcium receptor blockers (Xiao et al., 2022). However, the use of these drugs can produce certain side effects such as headaches, decreased blood pressure, gastrointestinal disorders, impaired liver and kidney function, and electrolyte disorders (Rubinfeld et al., 2022). Despite tremendous progress in modern medical diagnostic and therapeutic techniques and the development of AMI drugs, there is a lack of safe and effective drugs due to the complexity of their pathogenesis.
Network pharmacology has been widely used to guide the treatment of coronary heart disease by analyzing the synergistic relationship of multiple components, targets, and pathways among drugs, diseases, and targets (Wang et al., 2022). This study predicted liquiritin in treating AMI was associated with COX-2 and its inflammatory cascade response by network pharmacology. Molecular docking is a powerful computational tool for predicting binding modes and binding free energies of proteins and natural products, which can be used to screen possible targets of natural products and provide a theoretical basis for elucidating the mechanism (Pinzi and Rastelli, 2019.). Liquiritin has a high binding affinity with COX-2, which suggests that liquiritin may act on COX-2. Therefore, COX-2 can be the focus of this paper to study liquiritin against AMI.
COX-2 is a key enzyme that catalyzes the conversion of arachidonic acid to prostaglandins, and the upregulation of COX-2 levels is related to the pathogenesis of many inflammatory processes (Alhouayek and Muccioli, 2014). COX-2 has also been shown to positively regulate the expression of NLRP3 and IL-1β in macrophages (Yang et al., 2020). Silencing the COX-2 gene or using COX-2 inhibitors significantly reduced the activation of NLRP3 inflammasome, which ameliorated cystatinase-1-dependent pyroptosis (Zhuang et al., 2017). In addition, inhibition of the COX-2/NLRP3 signaling pathway was able to attenuate the inflammatory response induced by myocardial fibroblast pyroptosis, resulting in attenuation of myocardial ischemia/reperfusion injury in mice (Zhang et al., 2021). These evidences suggested that COX-2/NLRP3 signaling pathway-mediated pyroptosis was closely related to the development of VR after AMI and is one of the important signaling pathways. The specific pathological process is that COX-2 expression was increased under pathological stimuli, followed by activation of the NLRP3 inflammasome (including NLRP3, ASC, and caspase-1). Caspase-1 activation cleaves the GSDMD into C-terminal (GSDMD-C) and N-terminal (GSDMD-N) ends, the latter of which mediates pyroptosis. Activated caspase-1 also cleaves inactive pro-IL-1β and pro-IL -18 cleavage into mature IL-1β and IL-18, which were released into the extracellular space through the GSDMD-N pore in the cell membrane, inducing an inflammatory cascade response (Zhang et al., 2018).
Liquiritin has a good advantage in cardioprotection, including reducing ROS in H9c2 cells, attenuating mitochondrial Ca2+ overload, decreasing H9c2 cell death, and protecting cardiac mitochondria from hypoxia/reoxygenation (HR) injury (Thu et al., 2021). In addition, Liquiritin regulated the ATE1/TAK1-JNK1/2 pathway to exert a protective effect against Ang II-induced cardiomyocyte hypertrophy (Mo et al., 2022). However, the mechanism of liquiritin in preventing and treating AMI is unclear. Therefore, this paper combines prediction and experimental validation to elucidate the mechanism of liquiritin comprehensively.
Based on the network pharmacology and molecular docking results, COX-2 and its associated inflammatory pathways are the key targets and pathways for liquiritin against AMI. In the AMI model rats, echocardiography was used to assess the cardiac function of the rats. AMI model rats showed significant cardiac function abnormalities, such as a significant decrease in EF and FS and an increase in LVIDd, LVIDs, LVEDV, and LVESV, which appeared to improve significantly after administration of liquiritin or captopril. LDH is a well-known marker to assess cellular activity and indicate cardiomyocyte injury. CK and cTn-I as preferred markers for the diagnosis of AMI. As a quantitative marker of heart failure, BNP reflects left ventricular systolic dysfunction, left ventricular diastolic dysfunction, valvular dysfunction and right ventricular dysfunction. LDH, CK, cTn-I, and BNP were significantly up-regulated in AMI model rats. Intervention of liquiritin or captopril reversed myocardial injury. mRNA levels of COX-2 NLRP3, Caspase-1, ASC, and GSDMD were significantly elevated in the model group, liquiritin could reduce the mRNA level. The key protein levels of COX-2 and NLRP3 were significantly elevated in the model group, liquiritin could reverse the results. Serum level of IL-1β and IL-18 were also significantly elevated, and liquiritin significantly reduced the expression of IL-1β and IL-18. These results indicated that liquiritin significantly attenuates inflammation in VR after AMI.
We confirmed that liquiritin significantly exerted cardioprotective effects by inhibiting cardiac inflammation in AMI model rats. The mechanism may be related to the COX-2/NLRP3 signaling pathway. However, in vivo, experiments were used to study liquiritin against VR after AMI in this study, and further study will focus on the in vitro experiments and elucidation of the mechanism using silencing of the COX-2 gene or COX-2 inhibitors.
The authors declare no conflict of interest.
These works were supported by the Key Project Foundation of Natural Science Research in Universities of Anhui Province in China (2022AH050479) and the Anhui Natural Science Foundation project (2208085MH277).
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