• Users Online: 251
  • Print this page
  • Email this page

Table of Contents
Year : 2021  |  Volume : 7  |  Issue : 4  |  Page : 419-426

Mechanism research of chonglou as a pain killer by network pharmacology

1 Guangdong Province Key Laboratory of Pharmacodynamic Constituents of TCM and New Drugs Research, College of Pharmacy, Jinan University; International Cooperative Laboratory of Traditional Chinese Medicine Modernization and Innovative Drug Development of Chinese Ministry of Education, College of Pharmacy, Jinan University, Guangzhou, Guangdong, China
2 Department of Physiology, Medical College of Nanchang University, Nanchang, Jiangxi, China
3 Deparment of Molecular Pharmacology, RWTH Aachen University, Aachen, Germany
4 Department of biological Pharmaceuticals, School of Life Science, Ludong University, Yantai, Shandong, China
5 Department of Pharmaceutical Experimental Center, College of Pharmacy, Guangxi Medical University, Nanning, Guangxi, China
6 Department of Medical Science, Brown University, Providence, Rhode Island, USA

Date of Submission13-Aug-2020
Date of Acceptance14-Oct-2020
Date of Web Publication09-Apr-2021

Correspondence Address:
Prof. Hong Nie
Guangdong Province Key Laboratory of Pharmacodynamic Constituents of TCM and New Drugs Research, College of Pharmacy, Jinan University, Guangzhou 510632, Guangdong
Login to access the Email id

Source of Support: None, Conflict of Interest: None

DOI: 10.4103/wjtcm.wjtcm_84_20

Rights and Permissions

Objective: The objective of this study is to screen the therapeutic targets of pain of traditional Chinese medicine Chonglou and explore the relevant mechanism by network pharmacology techniques and methods. Materials and Methods: The chemical components of Chonglou were collected according to chemistry database and related literature. SwissADME was used to collect the potential active ingredients from all the chemical components of Chonglou and SwissTarget Prediction was utilized to predict their targets. The genes related to pain were collected from GeneCards and Online Mendelian Inheritance in Man databases. Joint genes were uploaded to the online string database for the analysis and the PPI network was constructed. The “Chonglou-active component-target-pain” network was constructed by Cytoscape 3.7.1 software, Gene Ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed for key target proteins. The top three active components with most targets in the network were docked with the target proteins by the molecular docking technique. Results: A total of nine potential active compounds of Chonglou, 264 potential target genes, 2385 targets of pain disorder, and 128 common targets for drug and disease were screened. One hundred and thirty-one GO items were identified by the GO enrichment analysis, and 23 related signaling pathways were identified by the KEGG pathway enrichment analysis. Molecular-docking results show that pennogenin is the optimal butt ligand of PIK3CA, STAT3, mitogen-activated protein kinase 14, and ADORA1. Conclusion: It is preliminarily revealed that Chonglou might treat pain through multiple targets, multiple biology processes and multiple pain-related signaling pathways, providing reference for the subsequent experimental research.

Keywords: Chonglou, molecular docking, network pharmacology, pain

How to cite this article:
Liu YT, Situ YL, Zhao TT, Long LN, Zeng HK, Liang SD, Schmalzing G, Gao HW, Wei JB, He CH, Nie H. Mechanism research of chonglou as a pain killer by network pharmacology. World J Tradit Chin Med 2021;7:419-26

How to cite this URL:
Liu YT, Situ YL, Zhao TT, Long LN, Zeng HK, Liang SD, Schmalzing G, Gao HW, Wei JB, He CH, Nie H. Mechanism research of chonglou as a pain killer by network pharmacology. World J Tradit Chin Med [serial online] 2021 [cited 2021 Nov 29];7:419-26. Available from: https://www.wjtcm.net/text.asp?2021/7/4/419/328765

  Introduction Top

Pain is an unpleasant feeling and emotional experience associated with actual or potential tissue damage, it is always an intuitive manifestation of various diseases.[1] For a long time, pain, especially chronic pain, has been a clinical conundrum,[2] harassed about one-half of the population around the world, in China, the incidence of chronic pain is about 35.9%.[3] Nowadays, pain has become a major public health problem increasingly, lead to negative impacts on mental health of individuals and huge economic burden on individuals and society.[2],[4] The current treatments for pain, limited to certain toxic and side effects, could be improved, and the search for more effective drugs is ongoing.[5]

Chonglou is the dried rhizomes of the lily plant Paris polyphylla Smith var. yunnanensis (Franch.) Hand.-Mazz. or Paris polyphylla Smith var. chinensis (Franch.) Hara.[6] Chonglou was first recorded in Shen Nong's herbal classic in the name of Zaoxiu. As traditional Chinese medicine (TCM), Chonglou has the effect of reducing pain and swelling, heat-clearing and detoxifying and cooling the liver, and calming the convulsion. Chonglou is one of the most important components of various Chinese patent medicines with analgesic effect, such as Yunnan Baiyao, Panlong Qipian, and Shennong Zhentong Gao.[7],[8],[9] Clinical evidence shows that utilizing Chinese patent medicines with Chonglou as the main component for pain treatment has remarkable analgesic effects.[10],[11] Moreover, previous study reported using Chonglou extract alone to treat severe pain has achieved good therapeutic effect, with an efficiency of up to 95%.[12] However, few studies focus on the pain release effect of Chonglou, and the main active components and mechanism behind its analgesic effect remain unclear.

Network pharmacology uses multi-disciplinary technical methods such as systems biology, multidirectional pharmacology, computational biology, and network analysis to conduct multi-level network construction and explore the connection between drugs and diseases from an integral perspective.[13],[14] Since TCM herbal has been considered as a multi-component and multi-target therapeutics which potentially meets the demands of treating a number of complex diseases in an integrated manner, in recent years, network pharmacology has become a powerful tool to clarify the complex and integral mechanisms of TCM.[15],[16] At present, network pharmacology approach was utilized to identify the active ingredients of Chonglou and predict the key targets and potential mechanism when used to treat pain.

  Materials and Methods Top

Active ingredients screen

We identified the chemical ingredients in Chonglou using Chemistry Database (http://www.organchem.csdb.cn) based on the literature.[17],[18] For active ingredients screening, all the chemical structures of the collected compounds in Chonglou were typed into SwissADME database (http://www.swissadme.ch/) to predict their pharmacokinetics and drug-likeness. All the ingredients, got in accordance with the following two conditions were screened:

  1. igh gastrointestinal absorption
  2. At least two outcomes of Lipinski, Ghose, Veber, Egan, Muegge are Yes.

Target prediction

The screened active ingredients in Chonglou were imported into SwissTarget Prediction database (http://www.swisstargetprediction.ch/), with the species set to “Homosapiens” to predict potential targets. All the targets with Probability >0.0 were collected.

Pain-related targets screening

Genecards database (https://www.genecards.org/) and Online Mendelian Inheritance in Man (OMIM) database (https://omim.org/) was utilized to obtain pain-related targets. The key word “pain” was screened in these two databases to screen all the reported pain-related genes, and the genes with Relevance score >5 in Genecards database and the genes in OMIM databases were collected. The pain related targets obtained from these two databases were combined, and the overlaps were eliminated.

Construction of protein-protein interaction network and “Chonglou-active components-targets-pain” network

The common targets of Chonglou and pain related targets were obtained by R 3.6.3 (the R Foundation, https://www.r-project. org/foundation/). String 11.0 database (https://string-db.org/) was applied to analyze the interrelationship of these targets to get the protein-protein interaction (PPI) network (the species were limited to homosapiens and the threshold was set to high confidence (0.700)). The “Chonglou-active components-targets-pain” network was generated and analyzed using Perl 5.26 (the Perl Foundation, 340 S Lemon Ave #6055 Walnut, CA 91789, U.S.) and Cytoscape 3.7.1 (National Institute of General Medical Sciences of the National Institutes of Health, U.S).

Gene ontology function and kyoto encyclopedia of genes and genomes pathway enrichment analysis

Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was performed with the help of cluster Profiler database based on the joint targets of Chonglou and pain. The significance threshold was set as P < 0.05.

Molecular docking

(1) Draw the three dimensional structures of active components with ChemBio3D Ultra 14.0; *(2) Retrieved and downloaded the crystal structure of the target protein through the protein databank (PDB) database; (3) Removed the water and ligand from the target protein with AutoDock Tools 1.5.6 and add hydrogen atoms to it to calculated the charge, and determined the size and center of the docking box with AutoDock Tools1.5.6; (4) The active ingredients were docked with the target protein using Vina 1.1.2, and the conformation with the highest affinity was selected; (5) analyzed and plotted the results with Pymol.

  Results Top

Screening of active ingredients of Chonglou

One hundred and fifteen main chemical components of Chonglou were collected, and nine active compounds of them were screened based on the pharmacokinetics and drug-likeness prediction of SwissADME [Table 1].
Table 1: The main active ingredients of Chonglou

Click here to view

Acquisition of the targets potentially related to pain treatment of Chonglou

These nine active ingredients of Chonglou have been related to 264 target genes according to SwissTarget Prediction database. Eighteen pain-related genes were obtained from OMIM database. Meanwhile, 11676 pain-related genes were obtained in Genecards database. Genes which Relevance score >5 were collected, and the overlapped genes of these two databases were eliminated. Finally, 2385 pain-related targets were obtained. With the help of R 3.6.3, a Venny analysis chart of the targets of active components in Chonglou and pain-related targets were drawn, and 128 potential therapeutic targets of Chonglou in pain treatment were screened [Figure 1].
Figure 1: Chonglou active ingredient and pain target Venny analysis chart. Drug represents TCM Chonglou, Disease represents pain

Click here to view

Protein-protein interaction network analysis

In order to show the interactions of these 128 potential analgesic targets of Chonglou intuitively, a PPI network was constructed by String 11.0 [Figure 2]. The network contains 128 nodes and 511 edges, with an average node degree of 8.05 and an average local clustering coefficient of 0.533. The top 30 of the key targets were selected according to the count value [Figure 3], mainly including PIK3CA, STAT3, HSP90AA1, SRC, CCND1, mitogen-activated protein kinase (MAPK) 1/3/8, AR, EGFR, interleukin 6 (IL6), etc.
Figure 2: Chonglou analgesic targets protein-protein interaction network. The lines represent the interaction of the proteins

Click here to view
Figure 3: Key targets of Chonglou protein-protein interaction network for pain release (top 30). The X axis represents the number of proteins that interact with the protein in front of the bar

Click here to view

Chonglou active components-targets-pain” interaction network analysis

On the purpose of explaining the complex relationships among Chonglou, pain and therapeutic targets more clearly and straightly, the network diagram of “Chonglou-active components-targets-pain” was constructed and visualized using Perl language and Cytoscape 3.7.1 software [Figure 4]. In [Figure 4], the red node represents disease pain; the yellow node represents TCM Chonglou; green nodes represent the active ingredients in Chonglou; and blue nodes represent the potential therapeutic targets. The larger the nodes in the diagram, the greater their impact on the analgesic effect. As shown in the diagram, pennogenin, paristerone, and β-ecdysone have more potential targets, these multi-target compounds may play a key role in the analgesic effect of Chonglou. Moreover, there are 70 target genes having two or more ligand compounds among all 128 potential targets. Meanwhile, MAPK14, ADORA1, and IL2 are potential targets of up to four active ingredients of Chonglou. This network diagram shows the characteristics of Chonglou acting on multiple targets with multiple components and synergistically exerting analgesic effects through the multiple pathways.
Figure 4: The network of “Chonglou-active components-targets-pain”. The yellow triangle node represents Chonglou; the red diamond node represents pain; the green rectangle nodes represent the active analgesic components of Chonglou; the blue oval nodes represent the targets; the lines represent the the interaction relationships of the nodes

Click here to view

Gene ontology function enrichment analysis

Through the GO analysis of the potential analgesic targets of Chonglou, 131 gene functions were obtained and the top 20 of them are listed in [Figure 5]. The results indicated that the active ingredients of Chonglou may exert analgesic effect through various biological processes such as neurotransmitter receptor activity, nuclear receptor activity, transcription factor activity, protein serine/threonine kinase activity, steroid hormone receptor activity and mitogen-activated protein kinase activity, and various molecular functions such as steroid binding, peptide binding, heme binding, hormone binding, and tetrapyrrole binding.
Figure 5: GO analysis of the key targets of the analgesic effect of Chonglou (top 20). The length and color of the bars are determined by the number of associated genes and their P values

Click here to view

Kyoto encyclopedia of genes and genomes pathway enrichment analysis

A total of 23 relative signaling pathways were obtained through KEGG analysis, and 20 enrichment pathways with higher significance were screened [Figure 6]. According to the result, various pathways such as neuroactive ligand receptor interaction, serotonergic synapse, cyclic guanosine monophosphate-protein kinases G (cGMP-PKG) signaling pathway, adrenergic in cardiomyocytes, and calcium signaling pathway were involved in the process of the analgesic effect of Chonglou. Among these key pathways, neuroactive ligand-receptor interaction, serotonergic synapse, calcium signaling pathway, and dopaminergic synapse were tightly related to pain. Meanwhile, the results also showed that the targets of Chonglou active ingredients are distributed on different signal pathways and play an analgesic effect through the interaction of multi-components and multi-targets.
Figure 6: KEGG analysis of the key targets of the analgesic effect of Chonglou (top 20). The size and color of the dots are determined by the number of associated genes and their P values

Click here to view

Molecular docking

The active components with most potential targets were selected to exert molecular docking, and the proteins were selected according to the key targets of PPI network and “Chonglou-active components-targets-pain” interaction network. The binding pattern of ligand to protein is shown in [Figure 7]. [Table 2] shows the potential binding of the three active components to the selected proteins PIK3CA, STAT3, MAPK14, and ADORA1. These small molecules bind to amino acid residues such as histidine, phenylalanine, leucine, tryptophan (TRP), and so on. The best docking ligand of these four proteins is pennogenin. Moreover, the highest score of docking protein is pennogenin, which binds to target proteins through hydrogen bonds and π-π bonds.
Figure 7: Binding patterns of active components of Chonglou with different target proteins

Click here to view
Table 2: Affinity and amino acid sites of ligand-protein detected by molecular docking

Click here to view

  Discussion Top

The composition of TCM is complex, and it acts on multiple targets and multiple pathways to play its roles in treating diseases through multiple contained components. The method of network pharmacology can be utilized to construct “TCM-active components-targets-disease” network through data mining and analysis, so as to better explain the overall relationship between TCM and its targets.

In the present study, pennogenin, paristerone, β-ecdysone, diosgenin, alanine, γ-aminobutyric acid (GABA), trillin, asparagine, and diosgenin-3-O-β-D-glucopyranoside were found to be potential active analgesic ingredients in Chonglou, and polyphyllin I, polyphyllin II, polyphyllin VI, and polyphyllin VII are the prescribed components in the quality standard of Chonglou. Polyphyllin I and polyphyllin II belong to diosgenin, and polyphyllin VI and polyphyllin VII belong to pennogenin. It was reported that pennogenin and diosgenin in Chonglou have strong analgesic effect, since the pain behaviors of mice were obviously reduced in hot plate test, acetic acid twisting test, and Hargraves' test.[19] Moreover, it was found that the saponins in Chonglou could increase the content of adreno-cortico-tropic-hormone in the hippocampus of acute morphine tolerance rats and alleviate the acute morphine tolerance in complete Freund's adjuvant induced arthritis, showing significant sedative and analgesic effects.[20] The ecdysone substance is one of the main ingredients in Chonglou.[18] Previous study indicated that β-ecdysone could inhibit the release of anti-immunoglobulin E-induced histamine from rat peritoneal cavity mast cells, and significantly reduce the release of histamine in mast cells caused by Concanavalin A.[21] In addition, β-ecdysone also could increase the activity of acetylcholinesterase in the rat brain.[22] Hence, these functions of β-ecdysone may be the underlying mechanism of its analgesic effect. As one of the important inhibitory neurotransmitters, GABA could curb the transmission of pain signals in the pain modulation pathways.[23] Previous studies had already shown that GABA could exert a central analgesic effect by inhibiting pain modulation pathways.[24],[25] These reports provided some theoretical support for our findings.

The PPI network indicated that pain-related targets such as PIK3CA, STAT3, MAPK1/3/8, HSP90AA1, SRC, CCND1, and IL6 are the critical targets for the analgesic effect of Chonglou. PIK3CA is one of the key proteins in PI3K/Akt/mTOR signaling pathway,[26] closely related to stress response processes such as inflammation, cell proliferation, and apoptosis. Moreover, PIK3CA had been already proved to be involved in acute and chronic pain caused by various reasons.[27],[28],[29] STAT3 is an important nuclear transcription factor in the JAK/STAT signaling pathway, which plays an important role in various neurobiological processes such as neuronal degeneration, synaptic plasticity, learning, and memory.[30] In recent years, many studies have shown that STAT3 is involved in the occurrence of various pains. For example, nerve injury or chemotherapeutic drug treatment could significantly activate spinal STAT3 and inhibiting the activation of STAT3 would obviously alleviates nerve injury or chemotherapeutic drug-induced hyperalgesia.[31],[32],[33] MAPK1/3/8, closely related to neuropathic pain, are important members of the MAPK signaling pathway.[34] In addition, study has shown that IL6 up-regulates the expression and function of CaV 3.2 T-type calcium channels, thereby sensitizing dorsal root ganglion neurons and mediating neuropathic pain.[35] Hence, in this study, the predicted potential key targets on the analgesic effect of Chonglou could be the potential research targets in future molecular biology experiments.

The results of GO enrichment analysis indicated that Chonglou may have a certain influence on neurotransmitter receptor activity, nuclear receptor activity, and steroid hormone receptor activity, which are all related to the targets and effects of Chonglou. KEGG enrichment analysis results showed that the signaling pathways of the analgesic effect of Chonglou mainly involved neuroactive ligand-receptor interaction, serotonergic synapse, cGMP-PKG signaling pathway, adrenergic in cardiomyocytes and calcium signaling pathway, and the related genes included PTGS1, PTGS2, SLC6A4, MAOA, MAOB, ADRB2, ADRB1, ADRA1A, ADRA1B, and CHRM2. Serotonin (5-HT) plays a very important role in the occurrence of pain, since it was reported that 5-HT exerts central analgesic effects in a variety of rat pain models.[36] Moreover, 5-HT also plays an important regulatory role in chronic pain, because there is evidence that 5-HT receptor agonists could be potential drugs for the treatment of pain in future.[37] A lot clinical analgesics, such as gabapentin and pregabalin, targets calcium ion channels.[38] Their analgesic effect on calcium signal pathway involves a variety of physiological and biochemical reactions, and the mechanism behind is complex. Calcium signaling pathway could regulate TRP pathways which are closely related to peripheral neuralgia. The functional structures of TRPV1/3/4 ion channels are intimately related to Ca2+ ion channels, and they are related to some certain mechanisms that induce pain.[39] In addition, the results of KEGG analysis indicated that Chonglou possibly act on the process of neuroactive ligand-receptor interaction and thereby exerting central and peripheral analgesia.

Molecular docking results indicated that the three-dimensional structure of the active compounds in Chonglou is highly compatible with the structure of the potential protein receptor, and they interact through hydrogen bonds and π-π bonds between the ligands and the active site residues. It is suggested that these active components might bind to the active sites of PIK3CA, STAT3, MAPK14, and ADORA1 to exert analgesic effect.

In summary, with the help of network pharmacology methods and molecular docking technique, the present study predicted the potential active components and analgesic mechanisms of Chonglou. Chonglou may exert the analgesic effect through its active components, such as pennogenin, paristerone, β-ecdysone, diosgenin, and GABA, and the underlying mechanisms might be the regulation of key targets such as PI3KCA, STAT3, MAPK1/3/8/14, and ADORA1 and the regulation of pain-related signaling pathways, such as neuroactive ligand-receptor interaction, serotonergic synapse, and calcium signaling pathway. This study thoroughly explored the relationship between Chonglou and pain treatment, predicted the potential analgesic targets and mechanisms of Chonglou, and provided ideas for future molecular biology verification and development of new drugs.


This work was financially supported by Natural Science Foundation of China (No. 81861138042), Natural Science Foundation of China (No. 81673634), Natural Science Foundation of Shandong, China (No. ZR2019MC004), and the high-end talent team construction foundation (No. 108-10000318).

Financial support and sponsorship

This work was financially supported by Natural Science Foundation of China (No. 81861138042), Natural Science Foundation of China (No. 81673634), Natural Science Foundation of Shandong, China (No.ZR2019MC004) and the high-end talent team construction foundation (No. 108-10000318).

Conflicts of interest

There are no conflicts of interest.

  References Top

Gao C. Discussion on the definition of pain. Chin J Pain Med 2017;023:23-4.  Back to cited text no. 1
Tsang A, Von Korff M, Lee S, Alonso J, Karam E, Angermeyer MC, et al. Common chronic pain conditions in developed and developing countries: Gender and age differences and comorbidity with depression-anxiety disorders. J Pain 2008;9:883-91.  Back to cited text no. 2
Chen B, Li L, Donovan C, Gao Y, Ali G, Jiang Y, et al. Prevalence and characteristics of chronic body pain in China: A national study. Springerplus 2016;5:938.  Back to cited text no. 3
Kurita GP, Sjøgren P, Juel K, Højsted J, Ekholm O. The burden of chronic pain: A cross-sectional survey focussing on diseases, immigration, and opioid use. Pain 2012;153:2332-8.  Back to cited text no. 4
Zhang D, Ma S, Sun J, Yang B, Zhang CL, Lin HM, et al. Investigation of the analgesic mechanism of Paeonia lactiflora based on network pharmacology. Jilin J Chin Med 2019;39:1654-8.  Back to cited text no. 5
National Pharmacopoeia Committee. Pharmacopoeia of the People's Republic of China. Vol. 2. Beijing, China: Medical Science Press; 2015.  Back to cited text no. 6
Geng F. Pharmacological effect and clinical evaluation of Panlongqi tablet. Chin J Mod Drug Appl 2009;3:130-1.  Back to cited text no. 7
Wang C. Research progress of Yunnan Baiyao preparation. Chin J Ethnomed Ethnopharm 2012;21:36-7.  Back to cited text no. 8
National Pharmacopoeia Committee. Drug Standard of the Ministry of Health of the People's Republic of China: Prescription Preparation of Traditional Chinese Medicine. Vol. 10. Beijing, China: National Pharmacopoeia Committee; 1995.  Back to cited text no. 9
Fu L, Niu F. Effect of Yunnan Baiyao powder combined with lidocaine external application on pain degree of ankle sprain patients. J External Ther Tradit Chin Med 2020;29:14-5.  Back to cited text no. 10
Wang S. Clinical efficacy of Panlongqi tablet combine traction for treatment of low back pain caused by lumbar disc herniation. Chin J Clin Ration Drug Use 2017;010:150-1.  Back to cited text no. 11
Zeng M, Zeng S, Liu Z, Zeng TX. Observation on the treatment of chemotherapy leakage, analgesia and detumescence with Extract of Paris polyphylla. J Clin Exp Med 2007;006:148.  Back to cited text no. 12
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. 13
Hopkins AL. Network pharmacology: The next paradigm in drug discovery. Nat Chem Biol 2008;4:682-90.  Back to cited text no. 14
Liu AL, Du GH. Network pharmacology: New guidelines for drug discovery. Yao Xue Xue Bao 2010;45:1472-7.  Back to cited text no. 15
Shanghai Institute of Organic Chemistry of CAS. Chemistry Database [DB/OL]. Available from: http://www.organchem.csdb. cn. [1978 2019]. Last access: 06-Oct-2020.  Back to cited text no. 16
Yang YG, Zhang J, Zhang JY, Wang YZ. Research progress in chemical constituents in plants of Paris L. and their pharmacological effects. Chin Tradit Herb Drugs 2016;047:3301-23.  Back to cited text no. 17
Guang X, Li RS, Duan BZ, Wang Y, Fan M, Wang S, et al. Advances in research on chemical constituents and pharmacological effects of Paris genus and prediction and analysis of quality markers. Chin Tradit Herb Drugs 2019;050:4838-52.  Back to cited text no. 18
Ding LS, Zhao M, Li MY, Chen LM, Wang ZM, Wang ZJ, et al. Study on the anti-nociceptive and anti-inflammatory effects of the extract of aerial part and rhizome of Paris polyphylla var. Chinensis. Nat Prod Res Dev 2018;30:832-9.  Back to cited text no. 19
Xu HW, Li HD, Wang J, Fan XT, Li XC, Gong FY. Rhizoma Paridis saponins reverses the decline of ACTH in hypothalamus of morphine tolerant arthritic rats. Chin J Neurosci 2001(03):259-64.  Back to cited text no. 20
Takei M, Endo K, Nishimoto N, Shiobara Y, Inoue S, Matsuo S. Effect of ecdysterone on histamine release from rat peritoneal mast cells. J Pharm Sci 1991;80:309-10.  Back to cited text no. 21
Catalan RE, Aragones MD, Godoy JE, Martinez AM. Ecdysterone induces acetylcholinesterase in mammalian brain. Comp Biochem Physiol Part C 1984;78:193-5.  Back to cited text no. 22
Cheng HJ, Xiang LQ, Ya BL, Liu WY. Research progress in GABA A receptor on pain modulation in dorsal root ganglion neurons. J Jilin Univ (Medicine Edition) 2018;44:1322-5.  Back to cited text no. 23
Pokusaeva K, Johnson C, Luk B, Uribe G, Fu Y, Oezguen N, et al. GABA-producing Bifidobacterium dentium modulates visceral sensitivity in the intestine. Neurogastroenterol Motil 2017;29:12904.  Back to cited text no. 24
Fischer BD. GABAA receptors as targets for the management of pain-related disorders: Historical perspective and update. CNS Neurol Disord Drug Targets 2017;16:658-63.  Back to cited text no. 25
Dobyns WB, Mirzaa GM. Megalencephaly syndromes associated with mutations of core components of the PI3K〢KT–MTOR pathway: PIK3CA, PIK3R2, AKT3, and MTOR. Am J Med Genet C Semin Med Genet 2019;181:582-90.  Back to cited text no. 26
Liu Y, Qin X, Lu X, Jiang J. Effects of inhibiting the PI3K/Akt/mTOR signaling pathway on the pain of sciatic endometriosis in a rat model. Can J Physiol Pharmacol 2019;97:963-70.  Back to cited text no. 27
Zhang J, Wang L, Wang H, Su Z, Pang X. Neuroinflammation and central PI3K/Akt/mTOR signal pathway contribute to bone cancer pain. Mol Pain 2019;15:1-12.  Back to cited text no. 28
Chen SP, Zhou YQ, Liu DQ, Zhang W, Manyande A, Guan XH, et al. PI3K/Akt pathway: A potential therapeutic target for chronic pain. Curr Pharm Des 2017;23:1860-8.  Back to cited text no. 29
Zong SH, Zeng GF, Fang Y, Zou B, Gao TH. The role of signal transducer and activator of transcription 3 in Th17 cell differentiation in spinal cord injury rat model. Guangdong Med J 2014;35:812-5.  Back to cited text no. 30
Zhang XS, Li X, Luo HJ, Huang ZX, Liu CC, Wan Q, et al. Activation of the RAGE/STAT3 pathway in the dorsal root ganglion contributes to the persistent pain hypersensitivity induced by lumbar disc herniation. Pain Physician 2017;20:419-27.  Back to cited text no. 31
Xue ZJ, Shen L, Wang ZY, Hui SY, Huang YG, Ma C. STAT3 inhibitor WP1066 as a novel therapeutic agent for bCCI neuropathic pain rats. Brain Res 2014;1583:79-88.  Back to cited text no. 32
Liu S, Mi WL, Li Q, Zhang MT, Han P, Hu S, et al. Spinal IL-33/ST2 Signaling Contributes to Neuropathic Pain via Neuronal CaMKII-CREB and Astroglial JAK2-STAT3 Cascades in Mice. Anesthesiology 2015;123:1154-69.  Back to cited text no. 33
Li SC, Liu ZX, Wang XD, Xie CY. The advance in the relationship between p38MAPK activation and neuropathic pain. Chin J Pain Med 2016;6:458-60.  Back to cited text no. 34
Liu FY. The mechanism of IL-6 up regulating Cav3.2 T-type calcium channel in neuropathic pain. Chin J Pain Med 2019;25:250.  Back to cited text no. 35
Muñoz-Islas E, Vidal-Cantú GC, Bravo-Hernández M, Cervantes-Duran C, Quinonez-Bastidas GN, Pineda-Farias JB, et al. Spinal 5-HT5A receptors mediate 5-HT-induced antinociception in several pain models in rats. Pharmacol Biochem Behav 2014;120:25-32.  Back to cited text no. 36
Bardin L. The complex role of serotonin and 5-HT receptors in chronic pain. Behav Pharmacol 2011;22:390-404.  Back to cited text no. 37
Yu RH, Qi WY, Liu C, Gao XM, Xu HM. Mechanism and research progress of ion channel analgesics. Prog Pharm Sci 2020;44:56-65.  Back to cited text no. 38
Moore C, Gupta R, Jordt SE, Chen Y, Liedtke WB. Regulation of pain and itch by TRP channels. Neurosci Bull 2018;34:120-42.  Back to cited text no. 39


  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6], [Figure 7]

  [Table 1], [Table 2]


    Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
    Access Statistics
    Email Alert *
    Add to My List *
* Registration required (free)  

  In this article
Materials and Me...
Article Figures
Article Tables

 Article Access Statistics
    PDF Downloaded34    
    Comments [Add]    

Recommend this journal