A Network Pharmacology-Based Study of the Molecular Mechanisms of Shaoyao-Gancao Decoction in Treating Parkinson's Disease

Insights into dietary phytochemicals targeting Parkinson's disease key genes and pathways: A network pharmacology approach

Parkinson's disease (PD) is a complex neurological disease associated with the degeneration of dopaminergic neurons. Oxidative stress is a key player in instigating apoptosis in dopaminergic neurons. To improve the survival of neurons many dietary phytochemicals have gathered significant attention recently. Thus, the present study implements a comprehensive network pharmacology approach to unravel the mechanisms of action of dietary phytochemicals that benefit disease management. A literature search was performed to identify ligands (i.e., comprising dietary phytochemicals and Food and Drug Administration pre-approved PD drugs) in the PubMed database. Targets associated with selected ligands were extracted from the search tool for interactions of chemicals (STITCH) database. Then, the construction of a gene-gene interaction (GGI) network, analysis of hub-gene, functional and pathway enrichment, associated transcription factors, miRNAs, ligand-target interaction network, docking were performed using various bioinformatics tools together with molecular dynamics (MD) simulations. The database search resulted in 69 ligands and 144 unique targets. GGI and subsequent topological measures indicate histone acetyltransferase p300 (EP300), mitogen-activated protein kinase 1 (MAPK1) or extracellular signal-regulated kinase (ERK)2, and CREB-binding protein (CREBBP) as hub genes. Neurodegeneration, MAPK signaling, apoptosis, and zinc binding are key pathways and gene ontology terms. hsa-miR-5692a and SCNA gene-associated transcription factors interact with all the 3 hub genes. Ligand-target interaction (LTI) network analysis suggest rasagiline and baicalein as candidate ligands targeting MAPK1. Rasagiline and baicalein form stable complexes with the Y205, K330, and V173 residues of MAPK1. Computational molecular insights suggest that baicalein and rasagiline are promising preclinical candidates for PD management.

Role of Network Pharmacology in Prediction of Mechanism of Neuroprotective Compounds

Network pharmacology is an emerging pioneering approach in the drug discovery process, which is used to predict the therapeutic mechanism of compounds using various bioinformatic tools and databases. Emerging studies have indicated the use of network pharmacological approaches in various research fields, particularly in the identification of possible mechanisms of herbal compounds/ayurvedic formulations in the management of various diseases. These techniques could also play an important role in the prediction of the possible mechanisms of neuroprotective compounds. The first part of the chapter includes an introduction on neuroprotective compounds based on literature. Further, network pharmacological approaches are briefly discussed. The use of network pharmacology in the prediction of the neuroprotective mechanism of compounds is discussed in detail with suitable examples. Finally, the chapter concludes with the current challenges and future prospectives.

Exploring the mechanism of metformin action in Alzheimer's disease and type 2 diabetes based on network pharmacology, molecular docking, and molecular dynamic simulation

Background

Metformin, which has been shown to be highly effective in treating type 2 diabetes (T2D), is also believed to be valuable for Alzheimer's disease (AD). Computer simulation techniques have emerged as an innovative approach to explore mechanisms.

Objective

To study the potential mechanism of metformin action in AD and T2D.

Methods

The chemical structure of metformin was obtained from PubChem. The targets of metformin were obtained from PubChem, Pharm Mapper, Batman, SwissTargetPrediction, DrugBank, and PubMed. The pathogenic genes of AD and T2D were retrieved from the GeneCards, OMIM, TTD, Drugbank, PharmGKB, and DisGeNET. The intersection of metformin with the targets of AD and T2D is represented by a Venn diagram. The protein-protein interaction (PPI) and core targets networks of intersected targets were constructed by Cytoscape 3.7.1. The enrichment information of GO and Kyoto Encyclopedia of Gene and Genomics (KEGG) pathways obtained by the Metascape was made into a bar chart and a bubble diagram. AutoDockTools, Pymol, and Chem3D were used for the molecular docking. Gromacs software was used to perform molecular dynamics (MD) simulation of the best binding target protein.

Results

A total of 115 key targets of metformin for AD and T2D were obtained. GO analysis showed that biological process mainly involved response to hormones and the regulation of ion transport. Cellular component was enriched in the cell body and axon. Molecular function mainly involved kinase binding and signal receptor regulator activity. The KEGG pathway was mainly enriched in pathways of cancer, neurodegeneration, and endocrine resistance. Core targets mainly included TP53, TNF, VEGFA, HIF1A, IL1B, IGF1, ESR1, SIRT1, CAT, and CXCL8. The molecular docking results showed best binding of metformin to CAT. MD simulation further indicated that the CAT-metformin complex could bind well and converge relatively stable at 30 ns.

Conclusion

Metformin exerts its effects on regulating oxidative stress, gluconeogenesis and inflammation, which may be the mechanism of action of metformin to improve the common pathological features of T2D and AD.

The Anti-atherosclerosis Mechanism of Ziziphora clinopodioides Lam. Based On Network Pharmacology

We investigated the mechanisms underlying the effects of Ziziphora clinopodioides Lam. (ZCL) on atherosclerosis (AS) using network pharmacology and in vitro validation.We collected the active components of ZCL and predicted their targets in AS. We constructed the protein-protein interaction, compound-target, and target-compound-pathway networks, and performed GO and KEGG analyses. Molecular docking of the active components and key targets was constructed with Autodock and Pymol software. Validation was performed with qRT-PCR, ELISA, and Western blot.We obtained 80 components of ZCL. The network analysis identified that 14 components and 37 genes were involved in AS. Then, 10 key nodes in the PPI network were identified as the key targets of ZCL because of their importance in network topology. The binding energy of 8 components (Cynaroside, α-Spinasterol, Linarin, Kaempferide, Acacetin, Genkwanin, Chrysin, and Apiin) to 4 targets (MMP9, TP53, AKT1, SRC) was strong and <-1 kJ/mol. In addition, 13 of the 14 components were flavonoids and thus total flavonoids of Ziziphora clinopodioides Lam. (ZCF) were used for in vitro validation. We found that ZCF reduced eNOS, P22phox, gp91phox, and PCSK9 at mRNA and protein levels, as well as the levels of IL-1β, TNF-α, and IL-6 proteins in vitro (P < 0.05).We successfully predicted the active components, targets, and mechanisms of ZCL in treating AS using network pharmacology. We confirmed that ZCF may play a role in AS by modulating oxidative stress, lipid metabolism, and inflammatory response via Cynaroside, Linarin, Kaempferide, Acacetin, Genkwanin, Chrysin, and Apiin.

Screening of Biomarkers and Quality Control of Shaoyao Gancao Decoction Using UPLC-MS/MS Combined with Network Pharmacology and Molecular Docking Technology

Shaoyao Gancao Decoction (SGD) is a classic prescription of traditional Chinese medicine (TCM), which is composed of Paeoniae Radix Alba and Glycyrrhizae Radix et Rhizoma, and has the clinical effect of anti-liver injury, but its active ingredients are unclear. In this study, the joint application of phytochemical compositional analysis, network pharmacology, and molecular docking technology was utilized to screen the active components of SGD against liver injury. Firstly, a total of 110 compounds were identified by UPLC-Q-TOF-MS/MS, including 54 flavonoids, 23 triterpenoids, 10 monoterpenoids, 6 coumarins, and 17 other compounds. Secondly, based on the above plant chemical compositions, network pharmacology was used to search for the active components of SGD against liver injury, and 19 components were considered to be the active components, including 1,2,3,4,6-penta-O-galloyl-β-D-glucopyranose, ferulic acid, coniferyl ferulate, benzoyl paeoniflorin, hesperidin, liquiritin, liquiritigenin, glycyrrhizic acid, caffeic acid, rutin, chlorogenic acid, gallic acid, methyl gallate, isoliquiritin apioside, albiflorin, neochlorogenic acid, isoliquiritin, narirutin, and naringenin. Thirdly, molecular docking was used to verify the efficacy of the compounds and showed that the compounds bound well to key targets. Furthermore, the 19 components were detected in the rat serum, which also demonstrated that they could be biomarkers. Because it is generally believed that the ingredients that can be absorbed into the blood may be active ingredients. In the end, we determined the contents of 19 key components in 10 different batches of SGD. The method has satisfactory linearity, stability, accuracy, repeatability, and recovery. This study clarified the active components, key targets, and pathways of SGD against liver injury and provided a new idea for the selection of quality control indicators in traditional Chinese medicine.

The pathogenesis and treatment mechanism of Parkinson's disease from the perspective of traditional Chinese medicine

BACKGROUND

Parkinson's disease (PD) is the second most common neurodegenerative disease with no treatment currently available to modify its progression. Traditional Chinese medicine (TCM) has gained attention for its unique theoretical basis and clinical effects. Many studies have reported on the clinical effects and pharmacological mechanisms of Chinese herbs in PD. However, few studies have focused on the treatment mechanisms of anti-PD TCM drugs from the perspective of TCM itself.

PURPOSE

To elaborate the treatment mechanisms of anti-PD TCM drugs in the perspective of TCM.

METHODS

We performed a literature survey using traditional books of Chinese medicine and online scientific databases including PubMed, Web of Science, Google Scholar, China National Knowledge Infrastructure (CNKI), and others up to July 2021.

RESULTS

TCM theory states that PD is caused by a dysfunction of the zang-fu organs (liver, spleen, kidney, and lung) and subsequent pathogenic factors (wind, fire, phlegm, and blood stasis). Based on the pathogenesis, removing pathogenic factors and restoring visceral function are two primary treatment principles for PD in TCM. The former includes dispelling wind, clearing heat, resolving phlegm, and promoting blood circulation, while the latter involves nourishing the liver and kidney and strengthening the spleen. The anti-PD mechanisms of the active ingredients of TCM compounds and herbs at different levels include anti-apoptosis, anti-inflammation, and anti-oxidative stress, as well as the restoration of mitochondrial function and the regulation of autophagy and neurotransmitters.

CONCLUSION

Chinese herbs and prescriptions can be used to treat PD by targeting multiple pharmacological mechanisms.

Network Pharmacology and Bioinformatics Approach Reveals the Multi-Target Pharmacological Mechanism of Fumaria indica in the Treatment of Liver Cancer

Liver cancer (LC), a frequently occurring cancer, has become the fourth leading cause of cancer mortality. The small number of reported data and diverse spectra of pathophysiological mechanisms of liver cancer make it a challenging task and a serious economic burden in health care management. Fumaria indica is a herbaceous annual plant used in various regions of Asia to treat a variety of ailments, including liver cancer. Several in vitro investigations have revealed the effectiveness of F. indica in the treatment of liver cancer; however, the exact molecular mechanism is still unrevealed. In this study, the network pharmacology technique was utilized to characterize the mechanism of F. indica on liver cancer. Furthermore, we analyzed the active ingredient-target-pathway network and uncovered that Fumaridine, Lastourvilline, N-feruloyl tyramine, and Cryptopine conclusively contributed to the development of liver cancer by affecting the MTOR, MAPK3, PIK3R1, and EGFR gene. Afterward, molecular docking was used to verify the effective activity of the active ingredients against the prospective targets. The results of molecular docking predicted that several key targets of liver cancer (along with MTOR, EGFR, MAPK3, and PIK3R1) bind stably with the corresponding active ingredient of F. indica. We concluded through network pharmacology methods that multiple biological processes and signaling pathways involved in F. indica exerted a preventing effect in the treatment of liver cancer. The molecular docking results also provide us with sound direction for further experiments. In the framework of this study, network pharmacology integrated with docking analysis revealed that F. indica exerted a promising preventive effect on liver cancer by acting on liver cancer-associated signaling pathways. This enables us to understand the biological mechanism of the anti liver cancer activity of F. indica.

Network Pharmacology Approach for Medicinal Plants: Review and Assessment

Natural products have played a critical role in medicine due to their ability to bind and modulate cellular targets involved in disease. Medicinal plants hold a variety of bioactive scaffolds for the treatment of multiple disorders. The less adverse effects, affordability, and easy accessibility highlight their potential in traditional remedies. Identifying pharmacological targets from active ingredients of medicinal plants has become a hot topic for biomedical research to generate innovative therapies. By developing an unprecedented opportunity for the systematic investigation of traditional medicines, network pharmacology is evolving as a systematic paradigm and becoming a frontier research field of drug discovery and development. The advancement of network pharmacology has opened up new avenues for understanding the complex bioactive components found in various medicinal plants. This study is attributed to a comprehensive summary of network pharmacology based on current research, highlighting various active ingredients, related techniques/tools/databases, and drug discovery and development applications. Moreover, this study would serve as a protocol for discovering novel compounds to explore the full range of biological potential of traditionally used plants. We have attempted to cover this vast topic in the review form. We hope it will serve as a significant pioneer for researchers working with medicinal plants by employing network pharmacology approaches.

An Integrated Analysis of Network Pharmacology and Experimental Validation to Reveal the Mechanism of Chinese Medicine Formula Naotaifang in Treating Cerebral Ischemia-Reperfusion Injury

BACKGROUND

Cerebral ischemia-reperfusion injury (CIRI) is a crucial factor leading to a poor prognosis for ischemic stroke patients. As a novel Chinese medicine formula, Naotaifang (NTF) was proven to exhibit a neuroprotective effect against ischemic stroke, clinically, and to alleviate CIRI in animals. However, the mechanisms underlying the beneficial effect have not been fully elucidated.

METHODS

In this study, we combined a network pharmacology approach and an in vivo experiment to explore the specific effects and underlying mechanisms of NTF in the treatment of ischemia-reperfusion injury. A research strategy based on network pharmacology, combining target prediction, network construction, gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and molecular docking was used to predict the targets of NTF in treating the ischemic stroke and CIRI. On the other hand, we used HPLC and HRMS to identify biologically active components of NTF. Middle cerebral artery occlusion models in rats were utilized to evaluate the effect and the underlying mechanisms of NTF against CIRI after ischemic stroke.

RESULTS

Network pharmacology analysis revealed 43 potential targets and 14 signaling pathways for the treatment of NTF against CIRI after ischemic stroke. Functional enrichment analysis showed that a STAT3/PI3K/AKT signaling pathway serves as the target for in vivo experimental study validation. The results of animal experiments showed that NTF significantly alleviated CIRI by decreasing neurological score, infarct volume, numbers of apoptotic neuronal cells, increasing density of dendritic spines and survival of neurons. Furthermore, NTF could increase the expression of p-STAT3, PI3K, p-AKT. In addition, the detection of apoptosis-related factors showed that the NTF could raise the expression of Bcl-2 and reduce the expression of Bax.

CONCLUSION

This network pharmacological and experimental study indicated that NTF, as a therapeutic candidate for the management of CIRI following ischemic stroke, may exert a protective effect through the STAT3/PI3K/AKT signaling pathway.

Current Approaches and Tools Used in Drug Development against Parkinson's Disease

Parkinson's disease is a progressive neurodegenerative disorder characterized by the death of nerve cells in the substantia nigra of the brain. The treatment options for this disease are very limited as currently the treatment is mainly symptomatic, and the available drugs are not able to completely stop the progression of the disease but only to slow it down. There is still a need to search for new compounds with the most optimal pharmacological profile that would stop the rapidly progressing disease. An increasing understanding of Parkinson's pathogenesis and the discovery of new molecular targets pave the way to develop new therapeutic agents. The use and selection of appropriate cell and animal models that better reflect pathogenic changes in the brain is a key aspect of the research. In addition, computer-assisted drug design methods are a promising approach to developing effective compounds with potential therapeutic effects. In light of the above, in this review, we present current approaches for developing new drugs for Parkinson's disease.

Formulated Chinese medicine Shaoyao Gancao Tang reduces NLRP1 and NLRP3 in Alzheimer's disease cell and mouse models for neuroprotection and cognitive improvement

Amyloid β (Aβ) plays a major role in the neurodegeneration of Alzheimer’s disease (AD). The accumulation of misfolded Aβ causes oxidative stress and inflammatory damage leading to apoptotic cell death. Traditional Chinese herbal medicine (CHM) has been widely used in treating neurodegenerative diseases by reducing oxidative stress and neuroinflammation. We examined the neuroprotective effect of formulated CHM Shaoyao Gancao Tang (SG-Tang, made of Paeonia lactiflora and Glycyrrhiza uralensis at 1:1 ratio) in AD cell and mouse models. In Aβ-GFP SH-SY5Y cells, SG-Tang reduced Aβ aggregation and reactive oxygen species (ROS) production, as well as improved neurite outgrowth. When the Aβ-GFP-expressing cells were stimulated with conditioned medium from interferon (IFN)-γ-activated HMC3 microglia, SG-Tang suppressed expressions of inducible nitric oxide synthase (iNOS), NLR family pyrin domain containing 1 (NLRP1) and 3 (NLRP3), tumor necrosis factor (TNF)-α, interleukin (IL)-1β and IL-6, attenuated caspase-1 activity and ROS production, and promoted neurite outgrowth. In streptozocin-induced hyperglycemic APP/PS1/Tau triple transgenic (3×Tg-AD) mice, SG-Tang also reduced expressions of NLRP1, NLRP3, Aβ and Tau in hippocampus and cortex, as well as improved working and spatial memories in Y maze and Morris water maze. Collectively, our results demonstrate the potential of SG-Tang in treating AD by moderating neuroinflammation.

Determining novel candidate anti-hepatocellular carcinoma drugs using interaction networks and molecular docking between drug targets and natural compounds of SiNiSan

BACKGROUND

SiNiSan (SNS) is an ancient traditional Chinese medicine (TCM) used to treat liver and spleen deficiencies. We studied the unique advantages of using SNS to treat hepatocellular carcinoma (HCC) with multiple components and targets to determine its potential mechanism of action.

METHODS

The active compounds from the individual herbs in the SNS formula and their targets were mined from Traditional Chinese Medicine Systems Pharmacology Database (TCMSP). HCC-associated targets were collected from the TCGA and GEO databases and samples were collected from patients with stage III hepatocellular carcinoma. A compound-disease target network was constructed, visualized, and analyzed using Cytoscape software. We built a protein-protein interaction (PPI) network using the String database. We enriched and analyzed key targets using GSEA, GO, and KEGG in order to explore their functions. Autodock software was used to simulate the process of SNS molecules acting on HCC targets.

RESULTS

A total of 113 candidate compounds were taken from SNS, and 64 of the same targets were chosen from HCC and SNS. The predominant targets genes were PTGS2, ESR1, CHEK1, CCNA2, NOS2 and AR; kaempferol and quercetin from SNS were the principal ingredients in HCC treatment. The compounds may work against HCC due to a cellular response to steroid hormones and histone phosphorylation. The P53 signaling pathway was significantly enriched in the gene set GSEA enrichment analysis and differential gene KEGG enrichment analysis.

CONCLUSIONS

Our results showed that the SNS component has a large number of stage III HCC targets. Among the targets, the sex hormone receptors, the AR and ESR1 genes, are the core targets of SNS component and the most active proteins in the PPI network. In addition, quercetin, which has the most targets, can act on the main targets (BAX, CDK1, CCNB1, SERPINE1, CHEK2, and IGFBP3) of the P53 pathway to treat HCC.

An Investigation of the Molecular Mechanisms Underlying the Analgesic Effect of Jakyak-Gamcho Decoction: A Network Pharmacology Study

Herbal drugs have drawn substantial interest as effective analgesic agents; however, their therapeutic mechanisms remain to be fully understood. To address this question, we performed a network pharmacology study to explore the system-level mechanisms that underlie the analgesic activity of Jakyak-Gamcho decoction (JGd; Shaoyao-Gancao-Tang in Chinese and Shakuyaku-Kanzo-To in Japanese), an herbal prescription consisting of Paeonia lactiflora Pallas and Glycyrrhiza uralensis Fischer. Based on comprehensive information regarding the pharmacological and chemical properties of the herbal constituents of JGd, we identified 57 active chemical compounds and their 70 pain-associated targets. The JGd targets were determined to be involved in the regulation of diverse biological activities as follows: calcium- and cytokine-mediated signalings, calcium ion concentration and homeostasis, cellular behaviors of muscle and neuronal cells, inflammatory response, and response to chemical, cytokine, drug, and oxidative stress. The targets were further enriched in various pain-associated signalings, including the PI3K-Akt, estrogen, ErbB, neurotrophin, neuroactive ligand-receptor interaction, HIF-1, serotonergic synapse, JAK-STAT, and cAMP pathways. Thus, these data provide a systematic basis to understand the molecular mechanisms underlying the analgesic activity of herbal drugs.

The Underlying Mechanism of Paeonia lactiflora Pall. in Parkinson's Disease Based on a Network Pharmacology Approach

Background: Parkinson's disease (PD) is the second most common neurodegenerative disease worldwide, yet as of currently, there is no disease-modifying therapy that could delay its progression. Paeonia lactiflora Pall. is the most frequently used herb in formulas for PD in Traditional Chinese Medicine and also a potential neuroprotective agent for neurodegenerative diseases, while its mechanisms remain poorly understood. In this study, we aim to explore the underlying mechanism of P. lactiflora in treating PD utilizing a network pharmacology approach. Methods: The protein targets of P. lactiflora ingredients and PD were first obtained from several databases. To clarify the key targets, a Protein-Protein-Interaction (PPI) network was constructed and analyzed on the String database, and then enrichment analysis was performed by the Metascape platform to determine the main Gene Ontology biological processes and Kyoto Encyclopedia of Genes and Genomes pathways. Finally, the Ingredient-Target-Pathway (I-T-P) network was constructed and analyzed by Cytoscape software. Results: Six active ingredients of P. lactiflora (kaempferol, ß-sitosterol, betulinic acid, palbinone, paeoniflorin and (+)-catechin) as well as six core targets strongly related to PD treatment [AKT1, interleukin-6, CAT, Tumor necrosis factor (TNF), CASP3, and PTGS2] were identified. The main pathways were shown to involve neuroactive ligand-receptor interaction, Calcium signaling pathway, PI3-Akt signaling pathway, TNF signaling pathway, and apoptosis signaling pathway. The main biological process included the regulation of neurotransmitter levels. Conclusion: P. lactiflora may retard neurodegeneration by reducing neuroinflammation, inhibiting intrinsic and extrinsic apoptosis, and may improve motor and non-motor symptoms by regulating the levels of neurotransmitters. Our study has revealed the mechanism of P. lactiflora in the treatment of PD and may contribute to novel drug development for PD.

Application of network pharmacology and molecular docking to elucidate the potential mechanism of Eucommia ulmoides-Radix Achyranthis Bidentatae against osteoarthritis

BACKGROUND

Osteoarthritis is a disabling disease, which seriously affects the quality of life of patients. Increasing evidence has indicated that Chinese herbal medicine including Eucommia ulmoides (EU) and Radix Achyranthis Bidentatae (RAB) have potential in the treatment of osteoarthritis, and this is associated with their multi-target and multi-link action characteristics. Although their potential anti-arthritic activity has been reported, the exact mechanism of EU-RAB action in osteoarthritis remains unexplored. Therefore, this study explores the mechanism of EU-RAB against osteoarthritis using network pharmacology and molecular docking technology.

METHODS

Public databases including TCMSP、BATMAN-TCM、OMIM and Genecards were used to predict the bioactive ingredients and putative targets of EU-RAB against osteoarthritis. Enrichment analysis was performed to expound the biological functions and associated pathways of the hub targets. Cytoscape software was used to construct a "compounds-targets-pathways" network for elucidating the comprehensive molecular mechanism of EU-RAB against osteoarthritis. Molecular docking was used to verify the correlation between the main active ingredients and hub targets.

RESULTS

Network pharmacological analysis of EU-RAB in the treatment of osteoarthritis, identified 50 active ingredients including quercetin, kaempferol, wogonin, and baicalein with important biological effect. A total of 68 key targets were screened, including IL-6, EGFR, MAPK8, etc., and they were found to be enriched in a series of signaling pathways, such as apoptosis, TNF, MAPK, PI3K/AKT, and IL-17 signaling pathways. Moreover, molecular docking analysis showed that the main ingredients were tightly bound to the core targets, further confirming the anti-arthritic effects.

CONCLUSION

Based on network pharmacology and molecular docking analysis, the present study provides insights into the potential mechanism of EU-RAB in osteoarthritis after successfully screening for associated key target genes and signaling pathways. These findings further provide a theoretical basis for further pharmacological research into the potential mechanism of EU-RAB in osteoarthritis.

An Investigation of the Mechanism of Rapid Relief of Ulcerative Colitis Induced by Five-flavor Sophora Flavescens Enteric-coated Capsules Based on Network Pharmacology

AIM AND OBJECTIVE

Five-Flavor Sophora flavescens Enteric-Coated Capsules (FSEC) are the only proprietary Chinese medicine approved for the treatment of ulcerative colitis (UC) in China. Phase II and III clinical trials have shown that the curative effect of FSEC in relieving UC was not inferior to that of mesalazine granules and enteric-coated tablets, but its pharmacological mechanism is unclear. Therefore, the network pharmacology is used to reveal the more comprehensive effective components and targets of FSEC in the treatment of UC.

METHODS

We screened the components of FSEC based on the TCMSP database, determined the action targets of these compounds through target fishing, and integrated the UC disease targets of several disease gene databases. The FSEC-UC composite targets were obtained by matching the two results, and then a PPI network was constructed to analyze the relationship between these targets, and the core targets were selected by topological correlation parameters. Finally, GO-BP and KEGG enrichment analyses were carried out using the clusterProfiler software package.

RESULTS

One hundred and sixty active components of FSEC were identified and 77 targets were obtained. Of these, 30 core targets were the main targets of FESC in the treatment of UC. And quercetin, kaempferol, luteolin and mangiferin were regarded as the core active components of FSEC. The results screened by GO and KEGG enrichment analysis showed that FSEC played a comprehensive therapeutic role in immune recognition, anti-inflammation and antioxidation mainly through IL-17, TNF, Toll-like receptor, NF-kappa B, and Th17 cell differentiation.

CONCLUSION

The molecular mechanism of UC remission induced by FSEC was predicted by network pharmacology. These findings provide an important theoretical basis for further study of the effective substances and mechanism of FSEC in the treatment of UC.