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Network pharmacology plays a pivotal role in systems biology, bridging the gap between traditional Chinese medicine (TCM) theory and contemporary pharmacological research. Network pharmacology enables researchers to construct multilayered networks that systematically elucidate TCM’s multi-component, multi-target mechanisms of action. This review summarizes key databases commonly used in network pharmacology, including those focused on herbs, components, diseases, and dedicated platforms for network pharmacology analysis. Additionally, we explore the growing use of network pharmacology in TCM, citing literature from Web of Science, PubMed, and CNKI over the past two decades with keywords like “network pharmacology”, “TCM network pharmacology”, and “herb network pharmacology”. The application of network pharmacology in TCM is widespread, covering areas such as identifying the material basis of TCM efficacy, unraveling mechanisms of action, and evaluating toxicity, safety, and novel drug development. However, challenges remain, such as the lack of standardized data collection across databases and insufficient consideration of processed herbs in research. Questions also persist regarding the reliability of study outcomes. This review aims to offer valuable insights and reference points to guide future research in precision TCM network pharmacology.

Rosacea is significantly associated with dementia, particularly Alzheimer’s disease (AD). However, the common underlying molecular mechanism connecting these two diseases remains limited. This study aimed to reveal the common molecular regulatory networks and identify the potential therapeutic drugs for rosacea and AD. There were 747 overlapped DEGs (ol-DEGs) that were detected in AD and rosacea, enriched in inflammation-, metabolism-, and apoptosis-related pathways. Using the TF regulatory network analysis, 37 common TFs and target genes were identified as hub genes. They were used to predict the therapeutic drugs for rosacea and AD using the DGIdb/CMap database. Among the 113 predicted drugs, melatonin (MLT) was co-associated with both RORA and IFN-γ in AD and rosacea. Subsequently, network pharmacology analysis identified 19 pharmacological targets of MLT and demonstrated that MLT could help in treating AD/rosacea partly by modulating inflammatory and vascular signaling pathways. Finally, we verified the therapeutic role and mechanism of MLT on rosacea in vivo and in vitro . We found that MLT treatment significantly improved rosacea-like skin lesion by reducing keratinocyte-mediated inflammatory cytokine secretion and repressing the migration of HUVEC cells. In conclusion, this study contributes to common pathologies shared by rosacea and AD and identified MLT as an effective treatment strategy for rosacea and AD via regulating inflammation and angiogenesis.

Background Icariin (ICA), an active ingredient extracted from Epimedium species, has shown promising results in the treatment of Alzheimer's disease (AD), although its potential therapeutic mechanism remains largely unknown. This study aimed to investigate the therapeutic effects and the underlying mechanisms of ICA on AD by an integrated analysis of gut microbiota, metabolomics, and network pharmacology (NP). Methods The cognitive impairment of mice was measured using the Morris Water Maze test and the pathological changes were assessed using hematoxylin and eosin staining. 16S rRNA sequencing and multi-metabolomics were performed to analyze the alterations in the gut microbiota and fecal/serum metabolism. Meanwhile, NP was used to determine the putative molecular regulation mechanism of ICA in AD treatment. Results Our results revealed that ICA intervention significantly improved cognitive dysfunction in APP/PS1 mice and typical AD pathologies in the hippocampus of the APP/PS1 mice. Moreover, the gut microbiota analysis showed that ICA administration reversed AD-induced gut microbiota dysbiosis in APP/PS1 mice by elevating the abundance of Akkermansia and reducing the abundance of Alistipe . Furthermore, the metabolomic analysis revealed that ICA reversed the AD-induced metabolic disorder via regulating the glycerophospholipid and sphingolipid metabolism, and correlation analysis revealed that glycerophospholipid and sphingolipid were closely related to Alistipe and Akkermansia . Moreover, NP indicated that ICA might regulate the sphingolipid signaling pathway via the PRKCA/TNF/TP53/AKT1/RELA/NFKB1 axis for the treatment of AD. Conclusion These findings indicated that ICA may serve as a promising therapeutic approach for AD and that the ICA-mediated protective effects were associated with the amelioration of microbiota disturbance and metabolic disorder. Graphical Abstract

Quercetin is a flavonoid with notable pharmacological effects and promising therapeutic potential. Quercetin plays a significant role in neuroinflammation, which helps reduce Alzheimer's disease (AD) severity. Quercetin (Q) and quercetin 3-O-glucuronide (Q3OG) are some of the most potent antioxidants available from natural sources. However, the natural form of quercetin converted into Q3OG when reacted with intestinal microbes. The study aims to ensure the therapeutic potential of Q and Q3OG. In this study, potential molecular targets of Q and Q3OG were first identified using the Swiss Target Prediction platform and pathogenic targets of AD were identified using the DisGeNET database. Followed by compound and disease target overlapping, 77 targets were placed in that AKT1, EGFR, MMP9, TNF, PTGS2, MMP2, IGF1R, MCL1, MET and PARP1 was the top-ranked target, which was estimated by CytoHubba plug-in. The Molecular docking was performed for Q and Q3OG towards the PDB:1UNQ target. The binding score of Q and Q3OG was − 6.2 kcal/mol and − 6.58 kcal/mol respectively. Molecular dynamics simulation was conducted for Q and Q3OG towards the PDB:1UNQ target at 200 ns. This study's results help identify the multiple target sites for the bioactive compounds. Thus, synthesizing new chemical entity-based quercetin on structural modification may aid in eradicating AD complications.

Background The current study aimed to evaluate the anti-inflammatory, anti-oxidant, and pronounced gastro-protective activities of β- Citronellol using in vitro , in vivo assays and in silico approaches. Methods In vitro assays, denaturation of bovine serum albumin, egg protein, and human Red Blood Cells (RBCs) membrane stabilization were performed, using Piroxicam as standard. For in vivo assessment, Histamine (0.1 ml from 1% w/v) and Formaldehyde (0.1 ml from 2% v/v) were used to mediate inflammation. In silico molecular docking and network pharmacology were employed to probe the possible target genes mediating gastroprotective effect of β-Citronellol at 25, 50, and 100 mg/kg, using indomethacin-induced (25 mg/kg i.p) gastric ulcer in rats. Moreover, Gastric tissues were evaluated for morphological, histopathological, and bio-chemical analysis of PGE 2, COX-I, COX-II, 5-LOX, eNOS, ICAM-1, oxygen-free radical scavengers (SOD, CAT), and oxidative stress marker (MDA). Results β - Citronellol prevented denaturation of proteins and RBCs membrane stabilization with maximum effect observed at 6,400 µg/mL. Citronellol decreased rat’s paw edema. Network pharmacology and docking studies revealed gastro-protective potential of Citronellol possibly mediated through arachidonic acid pathways by targeting COX-I, COX-II, PGE 2 , and 5-LOX. Citronellol reduced the ulcer indices, and histopathological changes. Further, β - Citronellol (50 and 100 mg/kg) increased gastric PGE 2, COX-1, and eNOS; while suppressing COX-2, 5-LOX and ICAM-1. Citronellol markedly enhanced the oxidative balance in isolated rat stomach tissues. Conclusions The anti-inflammatory, anti-oxidant, and gastro-protective effects of β - Citronellol against indomethacin-induced gastric ulcer model in rats through mediating COX-I, COX-II, PGE 2, 5-LOX, eNOS, and ICAM-1 inflammatory markers. Graphical abstract

Agarwood (Aquilaria malaccensis Lam.) is a resinous material from different geographical locations. The current evaluation of agarwood quality is usually based on its physical properties and chemical compounds, yet only a few studies have linked agarwood quality with its anxiolytic effect, as indicated by characteristic compounds. In this study, using solid-phase microextraction/gas chromatography–time-of-flight mass spectrometry (SPME/GC-TOFMS) and multivariate analysis, we found 116 significantly different compounds in agarwood samples from four locations in Southeast Asia with regard to their quality. Brunei and Nha Trang agarwood had abundant sesquiterpenoids, exhibiting notable pharmacological efficacy in relieving anxiety. Malaysian and Irian agarwood had abundant alcohols and aldehydes, qualifying them as high-quality spices. Compound–target–disease network and pathway enrichment analysis were further employed to predict 79 gene targets and 20 pathways associated with the anxiolytic effects based on the 62 sesquiterpenoids. The correlated relationships among the sesquiterpenoids and targets suggest that agarwood treats anxiety via multiple compounds acting on multiple targets. Varying levels of sesquiterpenes across agarwood groups might lead to differences in the anxiolytic effects via signaling pathways, such as neurotransmitter- and hormone-regulated pathways. Our study originally evaluates agarwood quality and its anxiolytic effect by linking the characteristic compounds to potential gene targets and pathways.

Plant secondary metabolites possess significant antioxidant and anti-inflammatory properties, but their complex polypharmacological mechanisms remain poorly understood. Network pharmacology has emerged as a powerful systems-level approach for investigating multi-target interactions of natural products. This review systematically analyzes network pharmacology applications in elucidating the antioxidant and anti-inflammatory mechanisms of plant metabolites, evaluating concordance between computational predictions and experimental validation. A comprehensive literature search was conducted across major databases (2015–2025), focusing on network pharmacology studies with experimental validation. Analysis revealed remarkable convergence toward common molecular mechanisms, despite diverse chemical structures. For antioxidant activities, the Nrf2/KEAP1/ARE pathway emerged as the most frequently validated mechanism, along with PI3K/AKT, MAPK, and NF-κB signaling. Anti-inflammatory mechanisms consistently involved NF-κB, MAPK, and PI3K/AKT pathways. Key targets, including AKT1, TNF-α, COX-2, NFKB1, and RELA, were repeatedly identified. Flavonoids, phenolic acids, and terpenoids dominated as bioactive compounds. Molecular docking studies supported predicted interactions, with experimental validation showing good concordance for pathway modulation and cytokine regulation. Network pharmacology provides a valuable framework for investigating the complex bioactivities of plant metabolites. The convergence toward common regulatory hubs suggests that natural compounds achieve protective effects by modulating central nodes that integrate redox balance and inflammatory responses. Despite limitations, including database dependency, integrating network pharmacology with experimental validation accelerates mechanistic understanding in natural-product drug discovery.

Crataegus azarolus L. (Rosaceae), commonly known as Mediterranean hawthorn, has long been valued in Traditional Medicine for treating cardiovascular and inflammation-related diseases, including diabetes, cancer, and rheumatism. Pharmacological benefits of Crataegus azarolus L. are notably linked to its anti-inflammatory properties. Fupenzic acid, a pentacyclic triterpene isolated from its leaves, holds significant pharmacological potential that remains elusive. This study investigates the unexplored capacity of fupenzic acid as a promising anti-inflammatory agent. Using a multidisciplinary approach that integrates network pharmacology, molecular docking, in vitro assays, and predictive in silico analyses of drug-like properties, ADME, and toxicity, the mechanisms and properties of fupenzic acid have been elucidated. Network pharmacology analysis identified the potential targets for fupenzic acid, with enrichment analyses revealing key processes like inflammatory response, cytokine signaling, innate immune system, and MAPK cascade regulation. Transcription factors such as RELA, SP1, and NFKB1 were predicted to play crucial roles in its therapeutic effects. PPI network analysis underscored NF-κB as a central hub, linking these pathways to its anti-inflammatory effects. In vitro experiments demonstrated that fupenzic acid effectively suppressed inflammatory mediators like NOS-2 and COX-2, through the NF-κB pathway. Molecular docking further confirmed its favorable interaction with NF-κB, reinforcing its mechanism of action. Additionally, in silico ADMET profiling revealed favorable drug-like properties including pharmacokinetics and toxicity profiles, emphasizing its suitability as a drug candidate. This study represents a major step forward in understanding the therapeutic potential of fupenzic acid, establishing it as a distinctive and promising anti-inflammatory agent. The findings identified it as a pharmacological agent for clinical development targeting inflammation-driven diseases and also provide a foundation for future translational research.

Liver diseases account for over two million deaths annually, amounting to 4% of mortality worldwide, underscoring the need for development of novel preventive and therapeutic strategies. The growing interest in natural hepatoprotective agents highlights the potential of traditional medicine for modern drug discovery, though unlocking their molecular complexity requires advanced tools. This study integrates cutting-edge computational techniques with traditional herbal knowledge to identify potential hepatoprotective compounds. Protein targets implicated in liver disorders were identified through network pharmacology and by leveraging the rich molecular diversity inherent in herbal compounds, phytocompounds were selected. The Gene Ontology, Kyoto Encyclopedia of Genes and Genome data were compiled and enrichment analysis was performed using the DAVID database. Molecular docking of selected phytocompounds with top five protein targets helped identify 14 compounds which were employed for building the pharmacophore model. In virtual screening, among 1089 compounds screened, 10 compounds were identified as potential hits based on their predicted scores and alignment with pharmacophore features. The interactions of resulting hits were then analyzed through redocking studies and validated through molecular dynamics simulation and ADMET studies. Notably, (2S,5E)-2-(3,4-Dihydroxybenzyl)-6-(3,4-dihydroxyphenyl)-4-oxo-5-hexenoic acid and 5′-hydroxymorin emerged as lead compounds for further investigation. Both compounds exhibited significant binding affinities with specific amino acids in selected targets, suggesting their potential to modulate key pathways involved in hepatic disorders. Our findings demonstrate the utility of this integrated approach which transits beyond traditional trial-and-error methods. This approach will accelerate the discovery of novel hepatoprotective compounds, providing deeper insights into their mechanistic pathways and action.

Chrysanthemum (Chrysanthemum morifolium Ramat.) has been recognized as both a food and medicinal substance in China since 2002 and possesses antioxidant, anti-inflammatory, antibacterial, and immunomodulatory activities. Previous studies suggest that Chrysanthemum may alleviate skin lesions resembling atopic dermatitis (AD); however, its underlying mechanisms remain unclear. In this study, we integrated network pharmacology and machine learning to systematically explore the potential mechanisms of Chrysanthemum in AD treatment. Four algorithms—Random Forest (RF), Lasso regression with cross-validation (LassoCV), Elastic Net (EN), and Extreme Gradient Boosting (XGB)—were compared, among which the XGB model achieved the best performance (accuracy = 0.9393). Further analysis identified 15 optimal features, two core targets (PTGS2 and MMP9), and one critical pathway (NF-κB signaling). To experimentally validate these findings, HaCaT keratinocytes were co-stimulated with TNF-α and IFN-γ to establish an in vitro inflammatory model, and co-treatment with three major flavonoids from Chrysanthemum—Acacetin, Diosmetin, and Chryseriol—significantly suppressed cytokine-induced COX-2 overexpression and reduced NF-κB p65 phosphorylation, confirming their inhibitory effects on NF-κB activation. These results were consistent with molecular docking and dynamics simulations, which demonstrated that these flavonoids, along with celecoxib, could stably bind to COX-2, thereby enhancing system stability and reducing residue fluctuations at the binding interface, revealing the molecular basis by which Chrysanthemum alleviates AD and supporting its modernization and therapeutic potential.