Identification and quantification of putative active constituents of huangqin decoction for ulcerative colitis treatment through the integration of chemical profiling, network pharmacology, and bioinformatics
This study provides a comprehensive chemical profile of HQD and presents a new approach for evaluating and managing quality based on putative active constituents and may serve as a scientific basis for further pharmacological and clinical studies.
Abstract
Introduction Huangqin decoction (HQD), a traditional Chinese medicine prescription, is used to treat gastrointestinal diseases, including ulcerative colitis (UC). However, systematic research on the components of HQD remains insufficient. Therefore, we aimed to perform chemical profiling, network pharmacology, and bioinformatics analyses of HQD to identify candidate constituents potentially associated with UC and to establish a quantitative method for their determination in HQD. Methods Qualitative chemical profiling was performed to identify 51 compounds in HQD, and their potential targets were predicted. UC-related target genes were identified by combining results from public and Gene Expression Omnibus (GEO) databases. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to investigate the biological processes and signaling pathways associated with UC. Moreover, protein–protein interaction (PPI) analysis was performed. Based on these results, 15 putative active constituents of HQD were selected and quantified. Molecular docking analysis was then performed to evaluate the binding interactions between these compounds and key target proteins. Results A total of 947 HQD component-related, 1,868 UC-related, and 2,930 GEO database-related target genes were intersected to obtain 109 common target genes for HQD and UC. GO and KEGG enrichment analyses indicated that these targets were mainly associated with inflammatory and immune-related biological processes and signaling pathways. Among the identified targets, NOS2, AHR, MMP3, MMP9, and PRKCQ were highlighted as potential key targets. The analysis of three batches of HQD samples revealed that baicalin had the highest content. Molecular docking results indicated favorable predicted interactions between the putative active compounds and core target proteins, with several compound–target pairs exhibiting docking scores below −11.0 kcal/mol. Discussion This study not only provides a comprehensive chemical profile of HQD but also presents a new approach for evaluating and managing quality based on putative active constituents. These findings may serve as a scientific basis for further pharmacological and clinical studies.
This study provides experimental evidence supporting the protective effects of DSP against UC, with its actions likely mediated, at least in part, through the modulation of Th17 cell differentiation.
Yanxia Huang, Q. Lin, Min Zhu et al.· Combinatorial chemistry & hi...· 0 citations
Gout is a disease characterized by hyperuricemia and the deposition of urate crystals in joints and soft tissues, leading to recurrent acute arthritis. Its increasing prevalence imposes substantial clinical and socioeconomic burdens. Sishen Decoction (SSD) has been used in the treatment of gout, but its potential molecular mechanisms remain unclear. This study applied an integrated network pharmacology and molecular docking approach to identify potential targets and signaling pathways associated with SSD in gout. Active compounds and corresponding targets of SSD were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP), while gout-related targets were collected from the GeneCards and Online Mendelian Inheritance in Man (OMIM) databases. Overlapping targets were identified and used to construct a drug-component-target-disease network. A protein-protein interaction (PPI) network was established using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed, followed by molecular docking using the docking server analysis module. A total of 37 bioactive compounds were associated with 116 overlapping gout-related targets. The top hub targets included TP53, IL6, IL1B, TNF, AKT1, EGFR, CASP3, JUN, BCL2, and MMP9. GO analysis suggested that these targets are involved in gene expression regulation and signal transduction. KEGG enrichment analysis indicated significant associations with the mitogen-activated protein kinase (MAPK), phosphoinositide 3-kinase/protein kinase B (PI3K-Akt), interleukin-17 (IL-17), and tumor necrosis factor (TNF) signaling pathways. Molecular docking predicted favorable interactions between key compounds and hub targets, with all binding energies of ≤-5 kcal/mol. These computational findings provide potential mechanistic hypotheses for the action of SSD in gout and may support future experimental validation.
Tingting Zhou, Xiandong Liang· Journal of Visualized Experi...· 0 citations
: This study aimed to investigate the potential common targets, core active ingredients, and key signaling pathways of Yinchenhao Decoction combined with Lamivudine in the treatment of alcoholic liver disease (ALD) using network pharmacology and molecular docking, providing a theoretical basis for this integrative therapy. Active ingredients of Yinchenhao Decoction and Lamivudine targets were screened from the TCMSP and ChEMBL databases, while ALD-related targets were obtained from GeneCards, TTD, and DrugBank. Common targets were identified via Venny analysis, and a protein-protein interaction (PPI) network was constructed using STRING and Cytoscape. GO and KEGG enrichment analyses were performed with Metascape, and molecular docking was conducted using CB-Dock2. A total of 44 active compounds, 331 drug targets, and 1022 ALD targets were surveyed, yielding 44 overlapping targets. GO analysis indicated involvement in hormone response and nuclear receptor activity, while KEGG enrichment highlighted the "Chemical carcinogenesis–receptor activation" pathway. Molecular docking showed that aloe-emodin had the strongest binding affinity with IL-6 (–9.7), followed by lamivudine (–6.4), quercetin (–6.2), and kaempferol (–6.1). In conclusion, Yinchenhao Decoction combined with Lamivudine may treat ALD through multiple components acting on multiple targets and pathways, primarily via IL-6-driven inflammation control and nuclear receptor modulation, and IL-6 appears to be a useful biomarker for monitoring ALD progression under this combined therapy.
Shun Yang· International Journal of Fro...· 0 citations
BACKGROUND
Rosacea is a chronic inflammatory skin disorder with limited therapeutic options. Puhuaiyin (PHY), a traditional Chinese medicinal formula, shows clinical efficacy, but its multi-component mechanisms remain unclear.
METHODS
Chemical constituents of PHY were identified by UPLC-Q-TOF-MS. Network pharmacology was used to predict potential targets, which were intersected with rosacea-associated genes. Bioinformatics analyses (differential expression, WGCNA, and machine learning) were applied to the GEO dataset GSE65914 to refine core targets. Molecular docking and molecular dynamics simulations were conducted to validate the binding modes and stability between key active constituents and the core targets.
RESULTS
A total of 59 chemical constituents were identified in PHY, with five key active components subsequently screened: quercetin, emodin, kushenol N, physcion, and palmitic acid. Network pharmacology analysis revealed 44 intersecting targets, which were significantly enriched in inflammation-related pathways, such as MAPK, NF-κB, and JAK-STAT signaling. Integrated bioinformatics and machine learning approaches identified MMP9 and IL1B as core targets, both of which were markedly upregulated in rosacea lesions and demonstrated prominent diagnostic value (AUC = 0.999 for MMP9, 0.964 for IL1B). Molecular docking indicated strong binding affinity between the core components and MMP9/IL1B. Molecular dynamics simulations confirmed stable complex conformations over 200 ns, with MM/PBSA binding free energies of -15.54 Kcal/mol (quercetin-MMP9) and -15.57 Kcal/mol (quercetin- IL1B).
DISCUSSION
This study, through a multidisciplinary approach, systematically elucidates the "multi-component, multi-target, and multi-pathway" mode of action of PHY in the treatment of rosacea. However, the computational predictions remain to be further validated by in vivo and in vitro experiments. Future research should focus on verifying its therapeutic efficacy in animal or cellular models, as well as elucidating the regulatory effects of key active components on the MMP9 and IL1B targets.
CONCLUSION
These computational predictions suggest that PHY may exert therapeutic effects against rosacea via quercetin and other components targeting MMP9 and IL1B, thereby modulating MAPK, NF-κB, and JAK-STAT pathways. The proposed mechanisms include inhibition of inflammation, regulation of the immune microenvironment, attenuation of vascular dilation, and promotion of skin barrier recovery. These findings provide a theoretical basis for future experimental validation.
Dan Sun, Na-Na Yang, Yi-Ding Zhao et al.· Current Computer - Aided Dru...· 0 citations
Objective This study aimed to identify candidate therapeutic targets of oolong tea polyphenols (TP) against hyperuricemia (HUA) using network pharmacology and bioinformatics, and to validate the predicted molecular mechanism through in vivo experimentation. Methods Drug and disease targets were retrieved from public databases, and overlapping targets were identified by Venn diagram analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed on the shared targets, and a protein-protein interaction (PPI) network was constructed to identify hub genes. For in vivo validation, an HUA mouse model was established by 15 days of oral potassium oxonate (PO) administration. Model mice then received TP by gavage at low (0.5 g⋅kg−1⋅d−1), medium (1 g⋅kg−1⋅d−1), or high (2 g⋅kg−1⋅d−1) doses for an additional 15 days. Serum biochemical markers, histopathological changes, and pathway-related protein expression were assessed by enzyme-linked immunosorbent assay (ELISA), hematoxylin and eosin (HE) staining, and western blot analysis, respectively. Results Network pharmacology analysis identified 59 overlapping targets between TP and HUA; GO and KEGG enrichment analyses revealed that these targets were primarily associated with hormone metabolism and the PI3K-AKT signaling pathway. In the animal experiment, TP dose-dependently reduced serum uric acid (SUA) levels in hyperuricemic mice. At the molecular level, low and medium doses of TP suppressed phosphorylation of phosphatidylinositol 3-kinase (PI3K), protein kinase B (AKT), and mammalian target of rapamycin (mTOR), whereas the high dose paradoxically activated this pathway and concomitantly elevated interleukin-1β levels. These findings indicate that TP modulates uric acid metabolism through a non-monotonic, dose-dependent mechanism. Conclusion By combining network pharmacology with animal experiments, this study identified the PI3K/AKT/mTOR signaling pathway as a likely mediator of the anti-hyperuricemic action of oolong tea polyphenols (TP). A medium dose of TP achieved the most balanced outcome, attenuating inflammation and preserving hepatic and renal architecture; the high dose, by contrast, paradoxically elevated interleukin-1β (IL-1β) and overactivated PI3K/AKT/mTOR signaling, underscoring the importance of dose calibration. These data suggest that a medium dose of TP may represent a feasible dietary strategy against hyperuricemia. Further work—including monomer identification, direct target validation, and clinical evaluation—is warranted to confirm and extend these preclinical findings.
Fen-Qiu Lin, Duo-Er Lu, Jia Chen et al.· Frontiers in Nutrition· 0 citations
A comprehensive approach combining network pharmacology and in vitro validation was employed to systematically elucidate the anti-inflammatory mechanisms of Zingiber officinale Roscoe. First, its components were preliminarily identified via UPLC-Q-Exactive Orbitrap MS/MS, whose targets were obtained from the Swiss Target Prediction database and the Traditional Chinese Medicine Systems Pharmacology database. Inflammation-related targets were retrieved from GeneCards and OMIM databases. Overlapping targets between compound-related and inflammation-related genes were identified, followed by the construction of PPI networks and component-target networks. Subsequent GO and KEGG pathway enrichment analyses were performed. Through network pharmacology analysis, 6-Shogaol (20), 8-Shogaol (24), and 8-Gingerol (19) emerged as core active components, while AKT1, MAPK3, EGFR, SRC, and STAT3 were identified as key targets. KEGG enrichment analysis revealed that the anti-inflammatory effects were primarily associated with AGE-RAGE, PI3K-Akt, MAPK, TNF, and IL-17 signaling pathways. Subsequently, molecular docking was employed to validate the binding affinity between core components and key targets. Finally, anti-inflammatory activity was validated in vitro using the LPS-stimulated RAW 264.7 macrophage model, and gene expression was assessed via qRT-PCR. Collectively, this study elucidates the active constituents and molecular mechanisms underlying the anti-inflammatory action of Z. officinale, providing a theoretical basis for its development, utilization, and clinical application.
Jiaqi Guo, Yunan Sun, Xuegui Liu et al.· Biomedical chromotography· 0 citations
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