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Table of Contents
ORIGINAL ARTICLE
Year : 2022  |  Volume : 8  |  Issue : 1  |  Page : 131-140

Mechanism exploration of the classical traditional chinese medicine formula huoluo xiaoling pill in clinical treatment and the traditional chinese medicine theory “treating different diseases with the same method”: A network pharmacology study and molecular docking verification


School of Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China

Date of Submission04-Jun-2021
Date of Acceptance26-Jul-2021
Date of Web Publication29-Jan-2022

Correspondence Address:
Dr. Xin-Lou Chai
Beijing University of Chinese Medicine, Beijing 100029
China
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/wjtcm.wjtcm_58_21

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  Abstract 


Objective: To analyze the possible mechanism of the Huoluo Xiaoling Pill in the treatment of three diseases, hyperglycemia, hyperlipidemia, and metabolic syndrome, and to provide ideas for learning the mechanism of “Treating different diseases with the same method” in Traditional Chinese Medicine (TCM) theory. Materials and Methods: The Traditional Chinese Medicine System Pharmacology Database and UniProt databases were used to screen the main ingredients and targets of the Huoluo Xiaoling Pill. The GeneCards database was used to screen the targets of the diseases, and Cytoscape 3.7.2 was used to construct a “Drug-Components-Targets-Disease” network to determine the core components. The STRING database was used to construct the protein-protein-interaction network, and gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomics enrichment analyses were carried out on the Metascape database. AutoDock 1.5.6 was used for molecular docking. Results: A total of 118 active components and 208 targets were screened in the Huoluo Xiaoling Pill. Quercetin, tanshinone IIA, luteolin, and ellagic acid were potential core components of Huoluo Xiaoling Pill treating the three diseases, and interleukin 6, Tumor necrosis factor, and vascular endothelial growth factor were potential key targets. Co-occurring GO biological processes involved responses to the molecules of bacterial origin, and the AGE-RAGE signaling, fluid shear stress, and atherosclerosis pathways were the co-occurring pathways. Molecular docking revealed good docking conditions between screened targets and components. Conclusion: This study predicted the mechanism of the Huoluo Xiaoling Pill in treating the three diseases. At the same time, the co-occurring targets and pathways between the three diseases provided a material basis for the TCM theory, “Treating different diseases with the same method.”

Keywords: Huoluo Xiaoling Pill; molecular docking; network pharmacology; traditional chinese medicine; treating different diseases with the same method


How to cite this article:
Hu YX, Zhang ZQ, Zhou QJ, Liao JY, Chai XL. Mechanism exploration of the classical traditional chinese medicine formula huoluo xiaoling pill in clinical treatment and the traditional chinese medicine theory “treating different diseases with the same method”: A network pharmacology study and molecular docking verification. World J Tradit Chin Med 2022;8:131-40

How to cite this URL:
Hu YX, Zhang ZQ, Zhou QJ, Liao JY, Chai XL. Mechanism exploration of the classical traditional chinese medicine formula huoluo xiaoling pill in clinical treatment and the traditional chinese medicine theory “treating different diseases with the same method”: A network pharmacology study and molecular docking verification. World J Tradit Chin Med [serial online] 2022 [cited 2022 May 18];8:131-40. Available from: https://www.wjtcm.net/text.asp?2022/8/1/131/336838



Hyperglycemia, hyperlipidemia, and metabolic syndrome (referred to in this manuscript as “the three diseases”) are mutually different and interrelated, belonging to the category of “Treating different diseases with the same method” in Traditional Chinese Medicine (TCM) theory. The Huoluo Xiaoling Pill, composed of the herbs Danggui, Danshen, Ruxiang, and Moyao, was first mentioned in Integrating Chinese and Western Medicine written by Mr. Zhang Xichun. In recent years, increasing attention has been paid to the potential of this formula to treat cardiovascular diseases. Modern studies have shown that the Huoluo Xiaoling Pill plays an important role in the treatment of cardiovascular diseases, including the three diseases,[1],[2],[3] but the mechanism and effective ingredients are still unknown. By constructing a “Drug-Components-Targets-Disease” network and identifying the pathways of the treatment process, network pharmacology (NP) played an important role in analyzing the mechanism of the treatment process between drugs and diseases by multiple components, targets, and pathways.[4] Therefore, the application of NP was expected to obtain the co-occurring components, targets, and pathways in the treatment of the three diseases by the Huoluo Xiaoling Pill, to explore a possible material basis for the TCM theory, “Treating different diseases with the same method.”


  Materials and Methods Top


The collection and screening of active ingredients in the Huoluo Xiaoling pill and the target prediction of its active components

Using the TCM System Pharmacology Database (TCMSP, https://tcmspw.com/),[5] we collected all the chemical components of the four TCMs Danggui, Danshen, Ruxiang, and Moyao, which constitute the Huoluo Xiaoling Pill. By screening criteria of oral bioavailability ≥OB% and drug-likeness ≥DL18,[6] the active chemical components of the Huoluo Xiaoling Pill were filtered out. All the collected targets of the active components were uploaded to the UniProt database, and the parameters “reviewed” and “human genes” were set to obtain potential targets.

Hyperglycemia, hyperlipidemia, and metabolic syndrome disease targets prediction

”Hyperglycemia,” “Hyperlipidemia” and “Metabolic Syndrome” were used as keywords to obtain the targets of the three diseases in the GeneCards database (https://www.genecards.org/).[7] The targets whose relevance scores were greater than the median were finally selected. The higher relevance score indicates that the target is closely related to the disease. According to the relevant literature, the targets whose relevance scores greater than the median were selected as the potential targets of the three diseases after deleting the duplicate values.

”Drug-component-target-disease” network construction

Venny (https://bioinfogp.cnb.csic.es/tools/venny/index.html) was used to draw a Venn diagram of the intersection of drug targets and disease targets. Microsoft Excel was used to build the network node information. The Excel file was imported into Cytoscape 3.7.2 to construct the “Drug-Components-Targets-Disease” networks of the Huoluo Xiaoling Pill for the treatment of three diseases and analyze their topological structures.

Construction and topology analysis of protein-protein-interaction network

The STRING database (https://string-db.org/)[8] was used to analyze the protein-protein interactions (PPI) of the shared targets. The combined score was set as >0.9 and the result imported into Cytoscape 3.7.2 to draw a PPI network diagram. Topological analysis was used to screen out key common targets based on the degree value.

Functional enrichment analysis

The Metascape database (http://metascape.org/)[9] was used to carry out the gene ontology (GO) function enrichment and Kyoto Encyclopedia of Genes and Genomics (KEGG) pathway enrichment analysis, with P < 0.05 as statistically significant. The results were visualized to analyze the relationship between the targets and pathways.

Molecular docking

AutoDock 1.5.6 software (Molecular Graphics Laboratory Department of Molecular Biology The Scripps Research Institute, MB-5 10550 N. Torrey Pines Rd La Jolla, CA 92037-1000, U.S.A) was used for molecular docking. The PDB (https://www.rcsb.org/)[10] and TCMSP (https://tcmspw.com/)[5] databases were used for the protein conformation of the key targets (receptor in molecular docking) and the 3D chemical structure (ligand in molecular docking) of the core components in the Huoluo Xiaoling Pill. Pymol 2.3.1 (https://pymol.org/) was used to dehydrate and de-ligand the protein conformation of the key targets. The results were saved as “.pdb” files. Receptors and ligands were hydrogenated and charged using AutoDock Tools, and then molecularly docked with AutoDock. The docking results were imported into Pymol for visualization.


  Results Top


Screening results of drug active ingredients and disease targets

A total of 118 active chemical components contained in Huoluoxiaolingdan were collected from the TCMSP database, including two from Danggui, 65 from Danshen, 8 from Ruxiang, and 45 from Moyao. The active chemical components in Danggui were the same as those in Moyao. After deleting the duplicate components, a total of 208 targets were identified as active components, as shown in the purple part of the oval in the lower left corner of [Figure 1].
Figure 1: Venn diagram of Huoluo Xiaoling Pill and the three diseases. The overlapping parts indicate the number of target genes that are intersected

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Disease targets related to the three diseases were obtained from the GeneCards database and those targets whose “relevance score” was greater than the median were retained. The results were as follows: 1361 targets for hyperglycemia, 689 for hyperlipidemia, and 1712 for metabolic syndrome. Subsequently, the targets of the disease were intersected with the 208 targets of active components in the Huoluo Xiaoling Pill (Huo Luo Xiao Ling Dan in Chinese, HLXLD) and the results are as follows: Hyperglycemia + HLXLD (92), hyperlipidemia + HLXLD (47), and metabolic syndrome + HLXLD (82). The other intersections are shown in [Figure 1].

Construction of “drug-component-target-disease” network and screening of the core components

Cytoscape 3.7.2 was used to construct “Drug-Components-Targets-Disease” networks for the Huoluo Xiaoling Pill and its treatment of the three diseases [Figure 2]. The degree value, which is determined by the number of links to a node, reflecting the frequency with which one node interacts with others, was used to evaluate the importance of a node and screen out the core components in the process of treating the three diseases with the Huoluo Xiaoling Pill. A node with a higher degree value is more significant than a lower one. As a result, components with higher degree values are more likely to be the core components of the formula. The results are as follows:
Figure 2: “Drug-component-target-disease” networks for the three diseases. (a) Hyperglycemia (b) Metabolic Syndrome (c) Hyperlipidemia (d) The intersection of three diseases

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Hyperglycemia

Quercetin (MOL000098, ID: MY41, Source: Moyao) with a degree value of 91, a betweenness centrality (BC) value of 0.30, and closeness centrality (CC) value of 0.54, was predicted to be the main active component of the Huoluo Xiaoling Pill. This was followed by BS (Degree = 75, BC = 0.20, CC = 0.52), stigmasterol (Degree = 66, BC = 0.19, CC = 0.51), and tanshinone IIA (Degree = 16, BC = 0.14, CC = 0.40). [Table 1] shows the top ten components of the Huoluo Xiaoling Pill in the hyperglycemia treatment network.
Table 1: The top 10 components of Huoluo Xiaoling Pill in the network of hyperglycemia treatment

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Hyperlipidemia

Quercetin (MOL000098, ID: MY41, Source: Moyao) with a degree value of 43, a BC value of 0.20, and CC value of 0.44, was predicted to be the main active component of the Huoluo Xiaoling Pill for the treatment of hyperglycemia. This was followed by luteolin (Degree = 14, BC = 0.035, CC = 0.35), stigmasterol (Degree = 8, BC = 0.049, CC = 0.017), and ellagic acid (Degree = 7, BC = 0.018, CC = 0.017). [Table 2] shows the top ten components of the Huoluo Xiaoling Pill in the network of hyperlipidemia treatment.
Table 2: The top 10 components of Huoluo Xiaoling Pill in the network of Hyperlipidemia treatment

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Metabolic syndrome

Quercetin (MOL000098, ID: MY41, Source: Moyao) with a degree value of 140, a BC value of 0.071, and CC value of 0.36, was predicted to be the main active component of the Huoluo Xiaoling Pill for the treatment of hyperglycemia. This was followed by BS (Degree = 70, BC = 0.0069, CC = 0.34), stigmasterol (Degree = 56, BC = 0.0081, CC = 0.34), and luteolin (Degree = 54, BC = 0.015, CC = 0.34). [Table 3] shows the top ten components of the Huoluo Xiaoling Pill in the network of metabolic syndrome treatment.
Table 3: The top 10 components of Huoluo Xiaoling Pill in the network of metabolic syndrome treatment

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In the picture, the green triangles represent the medicine of Huoluo Xiaoling Pill, the light yellow circles represent the drug ingredients: the light blue diamond shapes represent the common targets of Huoluo Xiaoling Pill and the disease, and the blue hexagons represent the disease; DS1-65 represent the chemical composition of Danshen;, RX1-8 represents the chemical composition of frankincense, MY1-43 represents the chemical composition of myrrh. Among them, A and B represent the common components of myrrh and angelica.

Quercetin was predicted to be one of the vital components in the treatment of the three diseases due to its high rank [Table 1], [Table 2], [Table 3]. Quercetin is a natural flavonol antioxidant with a variety of biological activities, which can inhibit the formation of foam cells, relieve endothelial cell dysfunction, and improve atherosclerosis.[11] By constructing the “Drug-Component-Target-Disease” network for the intersected genes of the three diseases [Figure 2]d, the active components of the prescription for the treatment of the three diseases were further analyzed. Topological analysis showed that quercetin [Figure 2]d had the highest degree value (69), followed by luteolin (23), oxalic acid (13), and tanshinone IIA (11). Most of these results are consistent with the results analyzed previously. Hence, it is speculated that quercetin, tanshinone IIA, luteolin, and ellagic acid are the core active components in the mechanism of treatment of the three diseases (”Treating different diseases with the same method”) using the Huoluo Xiaoling Pill. These results need to be verified by molecular docking.

The construction of protein-protein-interaction network

The number of targets at the intersection of the Huoluo Xiaoling Pill and hyperglycemia, hyperlipidemia, and metabolic syndrome [Figure 1] were as follows: Huoluo Xiaoling Pill-Hyperglycemia (91), Huoluo Xiaoling Pill-Hyperlipidemia (46), and Huoluo Xiaoling Pill-Metabolic Syndrome (81). The above intersection targets were imported into the STRING database to establish a PPI network, and the original data were imported into the Cytoscape 3.7.2 to draw the PPI networks of the Huoluo Xiaoling Pill and hyperglycemia, hyperlipidemia, and metabolic syndrome [Figure 3]. The topological characteristic analysis of the PPI network was then performed, and using the degree value, BC and CC parameters, targets with the top five degree values were selected as the core targets of the Huoluo Xiaoling Pill acting on the treatment of the three diseases. The specific results are as follows:
Figure 3: Protein-protein interactions network of Huoluo Xiaoling Pill - diseases targets. (a) Hyperglycemic (b) Metabolic Syndrome (c) Hyperlipidemia (d) The intersection of three diseases; the nodes in the figure indicate the common target protein of Huoluo Xiaoling Pill and the corresponding disease, the degree value of the node is positively related to the color depth and node area

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Hyperglycemia

As shown in [Figure 3]a, there were 90 nodes and 1456 edges in the network. Network topology characteristic data showed that Interleukin (IL)6 had the highest degree value (73), followed by AKT1 (72), Tumor necrosis factor (TNF) (68), Vascular endothelial growth factor (VEGFA) (67), and PTGS2 (61).

Hyperlipidemia

As shown in [Figure 3]b, there were 45 nodes and 439 edges in the network. Network topology characteristic data showed that IL6 had the highest degree value (39), followed by TNF (37), EGF (35), VEGFA (34), and NOS3 (32).

Metabolic syndrome

As shown in [Figure 3]c, there were 81 nodes and 1181 edges in the network. Network topology characteristic data showed that AKT1 had the highest degree value (64), followed by IL6 (63), TNF (60), VEGFA (58), and NOS3 (53).

The PPI networks of the Huoluo Xiaoling Pill and the three diseases are shown in [Figure 3]d, among which the degree values of IL6, TNF, and VEGFA ranked at the top three. Based on the analysis above, it can be seen that the co-occurring core targets of the Huoluo Xiaoling Pill in the treatment of the three diseases were IL6, TNF, and VEGFA, suggesting that these three target proteins were the key targets in the mechanism of treatment of the three diseases (”Treating different diseases with the same method”) with the Huoluo Xiaoling Pill. It also suggested that IL6, TNF, and VEGFA may be the molecular basis in the connection of the three diseases.

Functional enrichment analysis

To further clarify the pathways between the Huoluo Xiaoling Pill and the three diseases, the intersected targets of the Huoluo Xiaoling Pill and the three diseases were imported into the Metascape database for pathway enrichment analysis, and GO Biology Processes (GO-BP) and KEGG Pathway were obtained. The P value was used to screen the core pathway. The specific results were as follows:

A total of 297 major signaling pathways of hyperglycemia, including pathways in cancer, AGE-RAGE signaling pathways in diabetic complications, fluid shear stress, atherosclerosis, and other pathways [Figure 4]a were obtained from KEGG pathway enrichment. A total of 146 major signaling pathways of hyperlipidemia, including AGE-RAGE signaling pathways in diabetic complications, fluid shear stress, cancer and other pathways [Figure 4]b, were obtained from KEGG pathway enrichment. A total of 287 major signaling pathways of metabolic syndrome, including AGE-RAGE signaling pathways in diabetic complications, fluid shear stress, cancer and other pathways [Figure 4]c were obtained from KEGG pathway enrichment. The 2015 biological processes of hyperglycemia, 46 biological processes of hyperlipidemia, and 1857 biological processes of metabolic syndrome were obtained from GO-BP enrichment [Figure 4]d.
Figure 4: Kyoto Encyclopedia of Genes and Genomics and gene ontology-Biology Processes enrichment analysis of Hyperglycemia, Hyperlipidemia and Metabolic Syndrome. (a) Hyperglycemia Kyoto Encyclopedia of Genes and Genomics bubble chart; (b) Hyperlipidemia Kyoto Encyclopedia of Genes and Genomics bubble chart; (c) Metabolic Syndrome Kyoto Encyclopedia of Genes and Genomics bubble chart; (d) Gene ontology-Biology Processes analysis bar chart of the three diseases

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According to the summary of the results in [Figure 4], GO biological processes, such as responses to lipopolysaccharide and molecules of bacterial origin, appeared simultaneously in the treatment of the three diseases. The AGE-RAGE signaling pathway in diabetic complications and pathways of fluid shear stress, atherosclerosis, cancer, TNF signaling, and IL-17 signaling, were evaluated as mechanisms in the treatment of the three diseases using the Huoluo Xiaoling Pill. Among them, the AGE-RAGE signaling pathway [Figure 5], fluid shear stress and atherosclerosis pathways in diabetic complications [Figure 6] were ranked first in each disease, suggesting that the two were the main pathways in the mechanism of treatment of the three diseases using the Huoluo Xiaoling Pill.
Figure 5: AGE-RAGE signaling pathway in diabetic complications. The red gene in the figure is the target of the active ingredient of Huoluo Xiaoling Pill

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The red gene in the figure is the target of the active ingredient of Huoluo Xiaoling Pill.

Molecular docking

The core components quercetin, luteolin, tanshinone IIA, and ellagic acid were selected for molecular docking with key targets IL6, TNF, and VGFA. Positive results were observed in the overall docking situation [Table 4] and [Figure 7]. The docking results between tanshinone IIA and the core targets were even better. Among them, the binding energy of tanshinone IIA and VEGFA was the lowest (-7.63 kcal/mol), followed by tanshinone IIA and TNF (-6.77 kcal/mol), and luteolin and TNF (-6.76 kcal/mol). There were hydrogen bonds between tanshinone IIA and VEGFA along with amino acid residues SER-153 and ILE-154. According to the results of molecular docking, it can be predicted that the screened core components are likely to act on the targets. Among them, tanshinone IIA is more likely to be the core component of the Huoluo Xiaoling Pill, which acts on the three diseases.
Figure 6: Fluid shear stress and atherosclerosis. The red gene in the figure is the target of the active ingredient of Huoluo Xiaoling Pill

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Table 4: Molecular docking results (calculated by binding energy, kcal/mol)

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Figure 7: (a) Quercetin with IL6; (b) Quercetin with TNF; (c) Quercetin with VEGFA; (d) Tanshinone IIA with IL6; (e) Tanshinone IIA with TNF; (f) Tanshinone IIA with VEGFA; (g) Luteolin with IL6; (h) Luteolin with TNF; (i) Luteolin with VEGFA; (j) Ellagic acid with IL6; (k) Ellagic acid with TNF; (l) Ellagic acid with VEGFA

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  Discussion Top


Hyperglycemia, hyperlipidemia, and metabolic syndrome are common cardiovascular diseases that often co-occur in the clinic.[12] Hyperglycemia is considered when the blood glucose level is higher than the normal range, while hyperlipidemia is considered when one or more lipids in the plasma are higher than the normal value.[13] The liver is the main metabolic site of glycolipids in blood. Through the gluconeogenesis and glycogenolysis pathways or fatty acid synthesis and glycogen synthesis pathways, which are also carried out in the liver, glucose and lipids can be converted into one another. Hence, hyperglycemia and hyperlipidemia often appear together and affect each other in clinical practice. Metabolic syndrome is a group of clinical syndromes with obesity, hyperglycemia, dyslipidemia, and hypertension as the main manifestations and which seriously affects the health of the body.[14] It is a high-risk factor for major diseases such as cardiovascular and cerebrovascular diseases and type 2 diabetes,[14] and its pathogenesis is related to insulin resistance, elevated free fatty acids, etc.[15] It can be seen that the three diseases have many connections in terms of mechanism, clinical manifestations, and prognosis. Based on NP, our study predicted that there were 196 common disease targets represented by IL6, TNF, and VEGFA, among the three diseases. GO biological processes such as the responses to lipopolysaccharide and molecules of bacterial origin, and KEGG pathways such as the AGE-RAGE signaling pathway in diabetic complications, and fluid shear stress, atherosclerosis, cancer, and other common signaling pathways, play major roles in the treatment of the three diseases.

The following was written about the Huoluo Xiaoling Pill in Integrating Chinese and Western Medicine by Mr. Zhang Xichun: “Huoluo Xiaoling Pill, treating stagnation of qi and blood, fetishism and obstruction, pain in the heart and abdomen, leg pain and arm pain, internal and external sores and ulcers, and all visceral accumulation, meridian annihilation silt.” In addition to the Huoluo Xiaoling Pill, Mr. Zhang innovated many formulas based on the four medicines of Danggui, Danshen, Ruxiang, and Moyao, which were recorded in Integrated Chinese and Western Medicine.[16],[17] In clinical practice, the Huoluo Xiaoling Pill is mostly used to treat pain-related diseases such as low back pain and muscle strain, and has been used for metabolic-related diseases such as diabetic foot and tumor.[18] Although there have been some reports on the treatment of cardiovascular diseases such as coronary heart disease, hyperlipidemia, and hypertension using the Huoluo Xiaoling Pill, the number of clinical reports is still insufficient, and requires further research in the exploration of the mechanism of action.[19] Therefore, further in-depth exploration of the mechanism of action of the treatment may be of great significance in guiding the expansion of the scope of medications and developing new pharmaceutical preparations. The concept of “Treating different diseases with the same method” originated in Zhang Zhongjing's Shang Han Lun in the Eastern Han Dynasty: “Watch the pulse syndrome, know what to commit, and treat according to the syndrome.” This concept has been widely used by ancient Chinese doctors, but its mechanism of action remains unclear.[20] The multiple formulations of the Huoluo Xiaoling Pill in Integrating Chinese and Western Medicine fully demonstrated that the Huoluo Xiaoling Pill was able to treat different diseases, supporting “treating different diseases with the same method.” Additionally, there is a close relationship between hyperglycemia, hyperlipidemia, and metabolic syndrome, which are cardiovascular diseases. Hence, our study aimed to use NP and molecular docking technology to explore the material basis for “treating different diseases with the same method” as well as the efficacy of the Huoluo Xiaoling Pill in treating hyperglycemia, hyperlipidemia, and metabolic syndrome. The results showed that Huoluo Xiaoling Pill may act on the cardiovascular system through core components including quercetin, tanshinone IIA, luteolin, and ellagic acid, and the molecular docking results showed that the core components had good docking conditions with the core targets mentioned above. The binding energies of tanshinone IIA and VEGFA were the lowest.

Using NP and molecular docking technology, our study explained the mechanism of the Huoluo Xiaoling Pill in treating hyperglycemia, hyperlipidemia, and metabolic syndrome, and revealed the material basis of “treating different diseases with the same method” from the perspective of systems biology. The results showed that the core components including quercetin, tanshinone IIA, luteolin, and ellagic acid in the Huoluo Xiaoling Pill act together on IL6, TNF, VEGFA and other disease targets, and react on lipopolysaccharide. They also respond to the molecule of bacterial origin and other GO biological processes as well as the AGE-RAGE signaling pathway in diabetic complications, and the fluid shear stress, atherosclerosis, cancer, TNF signaling, and IL-17 signaling pathways, and other common pathways in the treatment of hyperglycemia, hyperlipidemia, and metabolic syndrome with Huoluo Xiaoling Pill, generating the effect of “treating different diseases with the same method.” At the same time, our study found that the process of “treating different diseases with the same method” mainly relies on a multi-source, multi-type, and multi-component compound material basis composed of a “Drug-Component-Target-Pathway-Disease” network. Therefore, if the Huoluo Xiaoling Pill has a similar “Components-Targets-Pathway” network with other diseases, it is likely to work on those diseases as well. This may provide new ideas for the expansion of drug indications and the theoretical research of “treating different diseases with the same method,” as well as a powerful reference for studying the mechanism of action of other classical TCM formulas (”different diseases with the same treatment”) and expanding the scope of treatment.

Due to the large number and high complexity of various drug components in TCM, and the many molecular changes involved in diseases and TCM syndromes,[21] there are many challenges in research on classical TCM formulas at this stage. NP is an emerging research method that can be used to discover biologically active compounds and clarify the mechanism of action of TCM formulas through the use of systems biology, highly integrated data analysis strategies, and visualization of interpretations. Furthermore, NP may be used to study the mechanism of interaction of TCM formulas with disease targets, which provides efficient methods and new opportunities in TCM formula research. This fits with the mechanism that the complex components of TCM formulas usually intervene in diseases through multiple pathways and targets.[4],[5] However, due to the imperfection of database information and the uncertainty of technical means, the research results have certain limitations. In the future, it will be necessary to conduct in-depth exploration and verification through in vitro experiments.


  Conclusion Top


The core components of the Huoluo Xiaoling Pill, including quercetin, tanshinone IIA, luteolin, and ellagic acid, act on key targets, including IL6, TNF, and VEGFA, through the response to molecules of bacterial origin, molecules of bacterial origin, and other biological processes, as well as the AGE-RAGE signaling pathway in diabetic complications, and fluid shear stress, atherosclerosis, cancer, and other pathways that play a role in the treatment of hyperglycemia, hyperlipidemia, and metabolic syndrome with the Huoluo Xiaoling Pill. At the same time, the co-occurring targets and signal pathways between the three diseases revealed that there is a material basis for the TCM theory of “treating different diseases with the same method.”

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Zeng S. Experimental Study of Huoluo Xiaoling Pill on Atherosclerosis Induced by High-Fat Diet in Rabbits, M.A. Thesis. Beijing: Beijing University of Chinese Medicine; 2012.  Back to cited text no. 1
    
2.
Hao L. Study on the Protective Effect of Huoluo Xiaoling Pill on Endothelial Cells, M.A. Thesis. Beijing: Beijing University of Chinese Medicine; 2016.  Back to cited text no. 2
    
3.
Chang B, Pan C, Chang B. Clinical observation on Huoluo Xiaoling Pill in the treatment of 86 cases of diabetic nephropathy. Beijing Tradit Chin Med 2010;29:922-4.  Back to cited text no. 3
    
4.
Yang Y, Yang K, Hao T, Zhu G, Ling R, Zhou X, et al. Prediction of molecular mechanisms for LianXia NingXin formula: A network pharmacology study. Front Physiol 2018;9:489.  Back to cited text no. 4
    
5.
Ru J, Li P, Wang J, Zhou W, Li B, Huang C, et al. TCMSP: A database of systems pharmacology for drug discovery from herbal medicines. J Cheminform 2014;6:13.  Back to cited text no. 5
    
6.
Hu W, Fu W, Wei X, Yang Y, Lu C, Liu Z. A network pharmacology study on the active ingredients and potential targets of Tripterygium wilfordii hook for treatment of rheumatoid arthritis. Evid Based Complement Alternat Med 2019;2019:5276865.  Back to cited text no. 6
    
7.
Liu Y, An T, Wan D, Yu B, Fan Y, Pei X. Targets and mechanism used by cinnamaldehyde, the main active ingredient in cinnamon, in the treatment of breast cancer. Front Pharmacol 2020;11:582719.  Back to cited text no. 7
    
8.
Porter SS, Liddle JC, Browne K, Pastrana DV, Garcia BA, Buck CB, et al. Histone modifications in papillomavirus virion minichromosomes. mBio 2021;12:e03274-20.  Back to cited text no. 8
    
9.
Liu F, Wu H. CC chemokine receptors in lung adenocarcinoma: The inflammation-related prognostic biomarkers and immunotherapeutic targets. J Inflamm Res 2021;14:267-85.  Back to cited text no. 9
    
10.
Burley SK, Berman HM, Bhikadiya C, Bi C, Chen L, Di Costanzo L, et al. RCSB Protein Data Bank: Biological macromolecular structures enabling research and education in fundamental biology, biomedicine, biotechnology and energy. Nucleic Acids Res 2019;47:D464-74.  Back to cited text no. 10
    
11.
Zhao L, Wang H, Du X. The therapeutic use of quercetin in ophthalmology: Recent applications. Biomed Pharmacother 2021;137:111371.  Back to cited text no. 11
    
12.
Madina M. Analysis of the relationship between diabetes mellitus complicated with hypertension and hyperlipidemia and serum uric acid. China Med Guide 2011;9:126-7. [doi: 10.15912/j.cnki.gocm. 2011.22.151].  Back to cited text no. 12
    
13.
Zhan H. Diagnostics. 4th ed. Beijing: China Traditional Chinese Medicine Publishing House; 2016.  Back to cited text no. 13
    
14.
Aguilar-Salinas CA, Viveros-Ruiz T. Recent advances in managing/understanding the metabolic syndrome. F1000Res 2019;8:v1000-370.  Back to cited text no. 14
    
15.
Liu L, Li W, Wang S, Zhou G, Sui Y, Jin J, et al. Review on Mechanism of Multi-target Intervention of Traditional Chinese Medicine on Metabolic Syndrome. Chin J Exp Pharm 2021;27:214-21. [doi: 10.13422/j.cnki.syfjx. 20210341].  Back to cited text no. 15
    
16.
Mu C, Cui J. Discussion on the use rules of crude drugs in Integrating Chinese and Western Medicine based on the levels of support and confidence of data mining. World J Integr Tradit Chin West Med 2019;14:18-21. [doi: 10.13935/j.cnki.sjzx. 190105].  Back to cited text no. 16
    
17.
Wei C, Fan W, Wang Q. Analysis on the Law of Compatibility of Frankincense and Myrrh in Records of Traditional Chinese and Western Medicine in Combination. Jilin Tradit Chin Med 2020;40:1651-4. [doi: 10.13463/j.cnki.jlzyy. 2020.12.031].  Back to cited text no. 17
    
18.
Duan J. Clinical observation on the treatment of bone metastasis cancer pain with Jiawei Huoluo Xiaoling Pill combined with pamidronate disodium. Sichuan Tradit Chin Med 2013;31:65-6. [doi: CNKI: Sun: SCZY.0.2013-07-028].  Back to cited text no. 18
    
19.
Deng R, Fang Y. Research progress of Huoluo Xiaoling Pill in the treatment of cardiovascular diseases. J Guiyang Coll Tradit Chin Med 2014;36:142-4. [doi: CNKI: Sun: gyzx. 0.2014-03-071].  Back to cited text no. 19
    
20.
Feng X, Sun P, Gao X, Shi X, Zhou K, Zhang J, et al. Professor LI Naiqing's academic experience of “female quadruple” in treating different diseases at the same time. Chin Geriatr Health Med 2020;18(06):140-2.   Back to cited text no. 20
    
21.
Li S, Zhang B. Traditional Chinese medicine network pharmacology: Theory, methodology and application. Chin J Nat Med 2013;11:110-20.  Back to cited text no. 21
    


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