This study elucidates the potential of HSD as a treatment for Alopecia areata and provides insights into its mechanisms of action, offering a novel approach for treating AA with multi-targeted traditional Chinese medicine.
Abstract
Background Alopecia areata (AA) is a common non-scarring autoimmune disease with a complex pathogenesis, high recurrence rates, and difficulty in achieving a cure. Recent years have seen an increasing focus on both clinical and basic research regarding AA. Hejie Shengfa Decoction (HSD), a traditional Chinese medicine formula, has shown certain efficacy in the clinical treatment of AA, though its underlying mechanisms remain unclear. Methods In this study, we retrieved the active ingredients of HSD and their associated targets from public databases. We then identified AA-related targets through bioinformatics analysis of publicly available AA datasets. A protein-protein interaction (PPI) network was constructed to generate the HSD-AA action network by integrating drug-specific targets and disease-related targets. Functional enrichment analysis was subsequently performed. To further investigate key genes, three machine learning algorithms—least absolute shrinkage and selection operator (LASSO) regression, support vector machine-recursive feature elimination (SVM-RFE), and Random Forest—were applied Additionally, immune cell infiltration analysis was carried out to examine the roles of these key genes in the local immune microenvironment. Molecular docking and molecular dynamics simulations were employed to assess the binding stability of the active ingredients with the core targets. Results The results revealed that HSD contains 96 active ingredients and 985 related targets. From the AA dataset, 955 differentially expressed genes and 492 co-expressed modular genes were identified, resulting in 23 intersecting genes after integration. Machine learning algorithms identified four key target genes among these 23. Immune infiltration analysis suggested that HSD could influence the immune microenvironment of AA by modulating the expression of these key targets. Molecular docking and molecular dynamics simulations confirmed strong and stable binding interactions between HSD’s main active ingredients—especially quercetin—and the core targets. Conclusion This study elucidates the potential of HSD as a treatment for AA and provides insights into its mechanisms of action, offering a novel approach for treating AA with multi-targeted traditional Chinese medicine.
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
Chronic pruritus is associated with chronic inflammatory skin diseases and is often non-histamine-dependent, involving immune dysregulation and inflammatory signaling. Conventional antihistamine-based therapies often show limited efficacy, emphasizing the need for alternative approaches targeting upstream immune and inflammatory pathways. Chunwangbosim-dan (CWBSD) is a traditional East Asian herbal prescription. Among its components, Coptidis Rhizoma (CR) and Rehmanniae Radix (RR) were selected based on reproducible anti-inflammatory activity. We investigated their potential anti-pruritic effects using an in silico approach.
Compounds of CR and RR were identified from the TCMSP and TCMID, and their putative targets were predicted using SwissTargetPrediction. Pruritus-related genes were collected from GeneCards, OMIM, and TTD. Overlapping targets were used to construct PPI networks via STRING and h Cytoscape (Degree and MCC) to define hub genes. GO and KEGG enrichment analyses were performed using STRING. Molecular docking simulations were conducted using AutoDock Vina to evaluate binding affinities between representative compounds and key hub proteins.
Network pharmacology analysis revealed that the selected components of CWBSD interacted with multiple pruritus-associated immune targets and were significantly enriched in inflammatory and immune signaling pathways, including MAPK, PI3K-Akt, JAK-STAT, IL-17, and chemokine signaling pathways. Molecular docking demonstrated strong and stable binding interactions between coptisine from CR and key signaling mediators such as AKT1, JAK2, and EGFR. In addition, isoacetoside from RR exhibited favorable binding affinities with MAPK family proteins, supporting their potential role in modulating inflammatory signal transduction.
CR and RR may modulate pruritus-relevant immune signaling through multi-target, multi-pathway actions, supporting experimental validation of CWBSD as a complementary strategy for chronic pruritus.
Portions of this work was carried out within the Korea Institute of Oriental Medicine, (grant number KSN18384113).
Computational and Systems Immunology (COMP)
Aejin Kim, Young Sook Kim, Bongkyun Park et al.· Journal of Immunology· 0 citations
It is suggested that Huangqin exerts multi-target effects on AD, centered on AKT1-mediated signaling crosstalk, to regulate inflammatory and immune pathways.
Introduction: Pediatric immune dysregulation and recurrent infections are closely associated with impaired neurodevelopment through shared inflammatory and neuroimmune pathways. Conventional single-target therapies often fail to address this biological complexity. Swarna Bindu Prasana (SBP), a classical Ayurvedic formulation, is traditionally used to enhance immune resilience and cognitive development; however, its systems-level biological mechanisms remain insufficiently characterized.
Methods: A computational, literature-mining-driven network pharmacology approach was applied to investigate the conserved SBP components: honey (Madhu), butter/ghee (Ghrita), and gold nanoparticles (Swarna Bhasma). The 300 most relevant immune-related PubMed abstracts per component were analyzed using biomedical named entity recognition. Identified immune targets were subjected to compound–target network construction, protein–protein interaction (PPI) analysis, Gene Ontology and KEGG pathway enrichment, transcription factor enrichment (ChEA3), and disease association analysis (MalaCards).
Results: Twenty-three immune-related targets were identified, of which 21 formed a highly interconnected PPI network. IL6 emerged as the principal convergent hub across all components, followed by TLR4 and IL10. Functional enrichment analyses highlighted cytokine signaling, Toll-like receptor pathways, JAK–STAT signaling, and adaptive immune differentiation (Th1/Th2/Th17). Key upstream regulators included NF-κB, STAT family members, FOXP3, and TBX21. Disease enrichment revealed strong associations with immune deficiency, autoimmune disorders, inflammatory bowel disease, and asthma.
Conclusion: These findings suggest that SBP exerts multi-target, network-based immunomodulatory effects, providing a mechanistic framework that supports its traditional use and informs future experimental and pediatric clinical validation.
Narendra Lamichhane, Lisa Dal Pozzo, Ashma Bhattarai et al.· Journal of Ayurveda and Inte...· 0 citations
Abstract Objective This study assessed the pharmacological prospects of Pteridaceae phytoconstituents using an integrated network pharmacology (NP) and computational molecular docking (MD) strategy. Materials and Methods Various peer-reviewed literature databases, including ScienceDirect, PubMed, Scopus, and Google Scholar, were used to gather bioactive constituents reported from this family. Absorption, Distribution, Metabolism, Excretion and Toxicology (ADMET) parameters, drug-likeness rules, and bioavailability scores were evaluated using SwissADME software, while toxicity profiles were predicted using ProTox-3.0. Potential targets of each compound were identified using Swiss Target Prediction software. Breast cancer–specific genes were obtained from OMIM (Online Mendelian Inheritance in Man), UniProt, CTD (Comparative Toxicogenomic Database), PharmGKB, and GeneCards. NP tools were employed to identify common targets between drugs and diseases, construct a protein–protein interaction (PPI) network, and perform Gene Ontology (GO) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analyses. Finally, MD analysis was performed to determine the binding efficiency of selected compounds with hub genes, thereby validating their potential activity. Results The study identified 143 predicted targets for six Pteridaceae-derived compounds, along with 12,120 breast cancer–associated targets retrieved from multiple databases. Comparison yielded 139 overlapping protein targets (4 of which showed low interaction scores), which were subsequently mapped into a PPI network consisting of 135 nodes and 683 edges. KEGG-based pathway and GO enrichment analyses revealed 111 signaling pathways, 86 biological processes, 22 cellular components, and 20 molecular functions. KEGG pathway analysis identified the interleukin-17 pathway as significantly enriched. MD analysis showed that pterosin J exhibited the highest binding affinities among the six compounds tested, with docking scores of −7.4, −7.3, −7.3, and −6.7 kcal/mol against PTGS2, HSP90AA1, GSK-3β, and MAPK3, respectively. Conclusion The present bioinformatics study suggested that pterosin J may have anticancer potential against breast cancer. Further in vitro and in vivo experiments are suggested to confirm the potential of the compound.
P. Gupta, Pankaj Sharma, A. K. Yadav et al.· Ibnosina Journal of Medicine...· 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
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