Network Pharmacology, Molecular Docking and Molecular Dynamics to Explore the Potential Immunomodulatory Mechanisms of Deer Antler

Unraveling the mechanism of core prescription in primary liver cancer: integrative analysis through data mining, network pharmacology, and molecular simulation

This study aims to identify core Traditional Chinese Medicine compound prescriptions (TCM CPs) for Primary Liver Cancer (PLC) and their underlying mechanisms. A comprehensive search was conducted using China National Knowledge Infrastructure (CNKI) and the Chinese Medical Code V5.0, identifying 151 TCM CPs. Medication frequency and association rules were analyzed with TCMICS V3.0, while active compounds were identified via TCMSP and TCMIP V2.0. Targets were predicted using Swiss Target Prediction, and disease targets from DisGeNET, OMIM, and GeneCards were cross-referenced. A protein-protein interaction (PPI) network was constructed, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis using DAVID. In the process of studying active compounds, an orthogonal experiment was carried out on the extraction process of relevant herbs. The results of the orthogonal experiment and range analysis showed that for the extraction rate of the extract and the content of paeoniflorin, the decoction cycles had the most significant impact, followed by soaking time and water volume. The optimal extraction conditions were determined as soaking time of 30 min, water volume of tenfold, and 3 decoction cycles. Under these conditions, the extract yield reached 42.49%, and the paeoniflorin content was 73.60 mg/25.02 g crude herb (equivalent to 2.94 mg/g). ANOVA analysis further confirmed the significance of these factors. The results revealed 109 common targets between TCM component targets and disease targets, with key targets including STAT3, SRC, AKT1, HRAS, and PIK3CA. Molecular docking showed strong binding affinities of paeoniflorin and 3,5,6,7-tetramethoxy-2-(3,4,5-trimethoxyphenyl) chromone to PLC targets, with ADME predictions favoring paeoniflorin. Furthermore, Molecular Dynamics (MD) simulations revealed that paeoniflorin maintains stable binding to the target proteins, demonstrating promising conformational stability. The CCK-8 assay demonstrated that the core TCM CP exerted a dose-dependent inhibitory effect on HepG2 cells. After 24 h of intervention, the IC50 values of paeoniflorin and the TCM CP on HepG2 cells were 17.58 μg/mL and 120.5 μg/mL, respectively, which confirmed their anti-proliferative activity against PLC. This study identifies key active compounds and investigates their roles in modulating the Ras/Raf/MEK/ERK, AKT/NF-κB, and JAK-STAT signaling pathways, offering valuable insights into the therapeutic potential of TCM for PLC treatment.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-025-00352-2.

Multi-omic studies on the pathogenesis of Sepsis

BACKGROUND

Sepsis is a life-threatening inflammatory condition, and its underlying genetic mechanisms are not yet fully elucidated. We applied methods such as Mendelian randomization (MR), genetic correlation analysis, and colocalization analysis to integrate multi-omics data and explore the relationship between genetically associated genes and sepsis, as well as sepsis-related mortality, with the goal of identifying key genetic factors and their potential mechanistic pathways.

METHODS

To identify therapeutic targets for sepsis and sepsis-related mortality, we conducted an MR analysis on 11,643 sepsis cases and 1,896 cases of 28-day sepsis mortality from the UK Biobank cohort. The exposure data consisted of 15,944 potential druggable genes (expression quantitative trait loci, eQTL) and 4,907 plasma proteins (protein quantitative trait loci, pQTL). We then performed sensitivity analysis, SMR analysis, reverse MR analysis, genetic correlation analysis, colocalization analysis, enrichment analysis, and protein-protein interaction network analysis on the overlapping genes. Validation was conducted using 17,133 sepsis cases from FinnGen R12. Drug prediction and molecular docking were subsequently used to further assess the therapeutic potential of the identified drug targets, while PheWAS was used to evaluate potential side effects. Finally, mediation analysis was conducted to identify the mediating role of related metabolites.

RESULTS

The MR analysis results identified a significant causal relationship between 24 genes and sepsis. The robustness of these causal associations was further strengthened by SMR analysis, sensitivity analysis, and reverse MR analysis. Genetic correlation analysis revealed that only two of these genes were genetically correlated with sepsis. Colocalization analysis showed that only one gene was closely associated with sepsis, while validation using the FinnGen dataset identified three genes. In the MR analysis of 28-day sepsis mortality, seven genes were found to have significant associations, with reverse MR analysis excluding one gene. The remaining genes passed sensitivity analysis, with no significant genes identified in genetic correlation and colocalization analyses. Molecular docking demonstrated excellent binding affinity between drugs and proteins with available structural data. PheWAS at the gene level did not reveal any potential side effects of the related drugs.

CONCLUSIONS

The identified drug targets, associated pathways, and metabolites have enhanced our understanding of the complex relationships between genes and sepsis. These genes and metabolites can serve as effective targets for sepsis treatment, paving new pathways in this field and laying a foundation for future research.

Therapeutic Mechanisms of Medicine Food Homology Plants in Alzheimer's Disease: Insights from Network Pharmacology, Machine Learning, and Molecular Docking

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by a gradual decline in cognitive function. Currently, there are no effective treatments for this condition. Medicine food homology plants have gained increasing attention as potential natural treatments for AD because of their nutritional value and therapeutic benefits. In this work, we aimed to provide a deeper understanding of how medicine food homology plants may help alleviate or potentially treat AD by identifying key targets, pathways, and small molecule compounds from 10 medicine food homology plants that play an important role in this process. Using network pharmacology, we identified 623 common targets between AD and the compounds from the selected 10 plants, including crucial proteins such as STAT3, IL6, TNF, and IL1B. Additionally, the small molecules from the selected plants were grouped into four clusters using hierarchical clustering. The ConPlex algorithm was then applied to predict the binding capabilities of these small molecules to the key protein targets. Cluster 3 showed superior predicted binding capabilities to STAT3, TNF, and IL1B, which was further validated by molecular docking. Scaffold analysis of small molecules in Cluster 3 revealed that those with a steroid-like core-comprising three fused six-membered rings and one five-membered ring with a carbon-carbon double bond-exhibited better predicted binding affinities and were potential triple-target inhibitors. Among them, MOL005439, MOL000953, and MOL005438 were identified as the top-performing compounds. This study highlights the potential of medicine food homology plants as a source of active compounds that could be developed into new drugs for AD treatment. However, further pharmacokinetic studies are essential to assess their efficacy and minimize side effects.

Integrating network pharmacology, molecular docking, and bioinformatics to explore the mechanism of sparganii rhizoma in the treatment of laryngeal cancer

Sparganii Rhizoma (SR) has demonstrated promising anticancer effects across various malignancies; however, its mechanisms in laryngeal cancer (LC) remain poorly understood. This study employs network pharmacology and molecular docking to investigate the molecular mechanisms underlying SR's therapeutic effects on LC, providing novel insights for its potential use in treatment. Active compounds and targets of SR were identified through the TCMSP and Pharmmapper databases, while LC-related targets were sourced from GEO, GeneCards, OMIM, and PharmGkb databases. A Venn diagram generated from these datasets highlighted 58 overlapping targets. The STRING database and Cytoscape 3.9.1 software facilitated the construction of a protein-protein interaction network for these targets, and R language analysis revealed 15 core targets. GO and KEGG enrichment analyses, conducted with the ''clusterProfiler'' package, identified relevant biological processes, cellular components, and molecular functions associated with LC treatment. KEGG analysis suggested SR primarily regulates pathways such as TNF, IL-17, and P53. Molecular docking confirmed SR's ability to bind effectively to the 15 core targets. Molecular dynamics simulations further validated stable protein-ligand interactions for MAPK1, GSK3B, and MAPK14. Core target validation across transcriptional, translational, and immune infiltration levels was performed using GEPIA, HPA, cBioPortal, and TIMER databases. In conclusion, network pharmacology, molecular docking, and dynamics simulations provided insights into SR's mechanism in LC treatment, forming a theoretical basis for further investigation of its therapeutic potential.

Identification of potential diagnostic targets and therapeutic strategies for anoikis-related biomarkers in lung squamous cell carcinoma using machine learning and computational virtual screening

Objective

Lung squamous cell carcinoma (LUSC) is a common subtype of non-small cell lung cancer (NSCLC) characterized by high invasiveness, high metastatic potential, and drug resistance, resulting in poor patient prognosis. Anoikis, a specific form of apoptosis triggered by cell detachment from the extracellular matrix (ECM), plays a crucial role in tumor metastasis. Resistance to anoikis is a key mechanism by which cancer cells acquire metastatic potential. Although several studies have identified biomarkers related to LUSC, the role of anoikis-related genes (ARGs) remains largely unexplored.

Methods

Anoikis-related genes were obtained from the Harmonizome and GeneCards databases, and 222 differentially expressed genes (DEGs) in LUSC were identified via differential expression analysis. Univariate Cox regression analysis identified 74 ARGs significantly associated with survival, and a prognostic model comprising 8 ARGs was developed using LASSO and multivariate Cox regression analyses. The model was internally validated using receiver operating characteristic (ROC) curves and Kaplan-Meier (K-M) survival curves. Differences in immune cell infiltration and gene expression between high- and low-risk groups were analyzed. Virtual drug screening and molecular dynamics simulations were performed to evaluate the therapeutic potential of CSNK2A1, a key gene in the model. Finally, in vitro experiments were conducted to validate the therapeutic effects of the identified drug on LUSC.

Results

The 8-gene prognostic model demonstrated excellent predictive performance and stability. Significant differences in immune cell infiltration and immune microenvironment characteristics were observed between the high- and low-risk groups, suggesting the critical role of ARGs in shaping the immune landscape of LUSC. Virtual drug screening identified Dihydroergotamine as having the highest binding affinity for CSNK2A1. Molecular dynamics simulations confirmed that the CSNK2A1-Dihydroergotamine complex exhibited strong binding stability. Further in vitro experiments demonstrated that Dihydroergotamine significantly inhibited LUSC cell viability, migration, and invasion, and downregulated CSNK2A1 expression.

Conclusion

This study is the first to construct an anoikis-related prognostic model for LUSC, highlighting its role in the tumor immune microenvironment and providing insights into personalized therapy. Dihydroergotamine exhibited significant anti-LUSC activity and holds promise as a potential therapeutic agent. CSNK2A1 emerged as a robust candidate for early diagnosis and a therapeutic target in LUSC.

Exploring the molecular mechanism of Epimedium for the treatment of ankylosing spondylitis based on network pharmacology, molecular docking, and molecular dynamics simulations

Ankylosing spondylitis (AS) is a rheumatic disease that causes inflammation and bone formation in the spine. Despite significant advances in treatment, adverse side effects have triggered research into natural compounds. Epimedium (EP) is a traditional Chinese herb with a variety of pharmacological activities, including antirheumatic, anti-inflammatory, and immunomodulatory activities; however, its direct effects on AS treatment and the underlying molecular mechanisms have not been systematically studied. Thus, here, we used network pharmacology, molecular docking, and molecular dynamics simulations to explore the targets of EP for treating AS. We constructed an interaction network to elucidate the complex relationship between EP and AS. Sixteen active ingredients in EP were screened; 80 potential targets were identified. In particular, 8-(3-methylbut-2-enyl)-2-phenylchromone, anhydroicaritin, and luteolin were the core components and TNF, IL-6, IL-1β, MMP9, and PTGS2 were the core targets. The GO and KEGG analyses indicated that EP may modulate multiple biological processes and pathways, including the AGE-RAGE, TNF, NF-κB/MAPK, and TLR signaling pathways, for AS treatment. Molecular docking and molecular dynamics simulations showed good affinity between the active components and core targets of EP, with stable binding within 100 nanoseconds. In particular, 8-(3-methylbut-2-enyl)-2-phenylchromone possessed the highest free energy of binding to PTGS2 and TNF (-115.575 and - 87.676 kcal/mol, respectively). Thus, EP may affect AS through multiple pathways, including the alleviation of inflammation, oxidative stress, and immune responses. In summary, we identified the active components and potential targets of EP, highlighting new strategies for the further experimental validation and exploration of lead compounds for treating AS.

Integrated network pharmacology and experimental validation to explore the mechanisms of Coregonus peled-derived myosin ACE-inhibiting peptides for the treatment of hypertension

Coregonus peled is rich in protein and is a plentiful resource of bioactive peptides. This study was aimed at extracting novel Angiotensin I-converting enzyme (ACE) inhibitory peptides from Coregonus peled and revealing their potential hypotensive mechanisms. This paper screened six ACE inhibitory peptides with high bioactivity, good water solubility, and ADMET properties by computerized enzyme digestion of myosin-heavy chain from Coregonus peled, and LCYPR had the greatest ACE inhibition activity (IC50 = 47.8782 μM). There were 47 potentially critical targets of LCYPR for hypertension treatment, involving 135 biological processes (BP), 30 cellular components (CC), and 30 molecular functions (MF). The results of KEGG pathway analyse showed that the LCYPR participated in 50 pathways including the renin-angiotensin system, renin secretion, lipid and atherosclerosis, relaxin signaling pathway, IL-17 signaling pathway, atherosclerosis, fluid shear stress, and others, through the key targets such as AGT, AKT1, ACE, REN, CTSB, STAT3, PLG, SRC, MMP2, and F2 to regulate the blood pressure of organisms. In conclusion, the study obtained a novel ACE inhibitory peptide from the myosin-heavy chain of Coregonus peled and revealed the potential target and pathway of LCYPR to improve hypertension. The study provides new ideas and methods for developing novel antihypertensive peptides. The results provide a theoretical basis for developing functional foods of the Xinjiang specialty cold-water fish.

Sika Deer antler protein antagonizes the inflammatory response and oxidative damage induced by jellyfish venom

The investigation into specific treatments for jellyfish stings has consistently presented a significant medical challenge. Sika Deer antler protein (DAP), a valuable component of traditional Chinese medicine (TCM) known for its various pharmacological properties, has been widely utilized for the prevention and treatment of numerous diseases. In this study, proteome analysis and biological activity assays of DAP identified 94 distinct protein components and demonstrated its capability to scavenge free radicals. Moreover, administration of 50 mg/kg DAP notably enhanced survival rates in mice, mitigated increases in hematological indicators and inflammatory markers (IL-6, IL-1β, and TNF-α), and alleviated pathological abnormalities induced by jellyfish venom. Additionally, DAP intervention significantly decreased the hemolysis rate and improved the viability of RAW264.7 cells, while reducing cell apoptosis and oxidative stress. Transcriptome analysis and western blotting of RAW264.7 cells further confirmed that DAP inhibited the activation of the NF-κB and MAPK signaling pathways. Overall, DAP effectively countered the toxicity of jellyfish venom by reducing oxidative damage and inflammatory response, highlighting the potential of TCM in treating jellyfish stings.

Comparison of the composition, immunological activity and anti-fatigue effects of different parts in sika deer antler

Background

Sika deer (Cervus nippon Temminck, 1838) antler is a highly esteemed tonic renowned for its abundant assortment of polypeptides, polysaccharides, amino acids, and minerals, and is recognized for its multifarious pharmacological properties. However, limited research has been conducted regarding the variation in composition of deer antlers between the upper and basal sections, as well as their pharmacological effects on immunological activity and anti-fatigue in mice. The objective of this study was to conduct a comprehensive analysis on the appearance, chemical composition, and pharmacological effects of different components within sika deer antlers. This investigation aims to elucidate the disparities in quality among various parts of antlers and establish a theoretical foundation for the precise utilization of sika deer antlers.

Methods

The contents of protein, amino acids, polysaccharides, phospholipids, minerals and nucleotides in wax, powder, gauze and bone slices were determined by different nutrient assays. Then, 100 mice were randomly divided into 5 groups. The mice in control group were administered 0.3 mL of saline solution per day. The mice in experimental groups were administered 0.3 mL enzymatic hydrolysate of the wax slice, powder slice, gauze slice, bone slice separately per day, continuously for 14 days from the first day. The effect of antler on boosting immunity was evaluated by testing organ indices and assessing immunoglobulin levels by ELISA. Anti-fatigue effects were assessed by a mouse swimming test. Finally, the correlation between composition and pharmacological effects was analysed.

Results

The content of each marker substance gradually decreases from the upper to the basal of deer antler. The protein and uracil content in the wax slice were significantly higher than the other three groups (p < 0.05), and the phospholipid and inosine content were strongly significantly higher than the other three groups (p < 0.01). The content of polysaccharides and hypoxanthine in the wax slice group and powder slice group was significantly higher than that in the gauze slice group and bone slice group (p < 0.05). The amino acid content decreases from the upper to the basal section. Among, the content of Glu, Gly, His, and Pro wax slice was significantly higher than the other three groups (p < 0.01). The content of other minerals except Fe and Mg in the wax slice group was significantly higher than the other three groups (p < 0.01), and the content of Fe and Mg in the bone slice was the highest. Additionally, the immune organ index, immunoglobulin, and glycogen contents displayed a significant increase in comparison to both the control group and the other experimental groups (p < 0.05). And the swimming endurance of mice in the wax slice group was significantly prolonged (p < 0.01). The skeletal muscle state of the wax group mice exhibited superior characteristics, characterized by distinct horizontal stripes and tightly arranged muscle fibers. In contrast, the bone group displayed noticeable yet relatively less compact horizontal stripes. Among the organic and inorganic compositions of deer antler, the highest degree of correlation with the content of IgA, IgM, and IgG was found to be protein (r2 = 0.999), uracil (r2 = 0.987), and inosine (r2 = 0.999), respectively. The proteins (r2 = 0.997) appear to exert a significant influence on the anti-fatigue effect, while polysaccharides (r2 = 0.865) demonstrate the least relevance.

Conclusion

These outcomes indicated that the wax slice yielded optimal results among the tested parts and demonstrated the highest efficacy.

Anti-depression molecular mechanism elucidation of the phytochemicals in edible flower of Hemerocallis citrina Baroni

The edible flower of Hemerocallis citrina Baroni, commonly known as "Huang Huacai" in China, has anti-depressant effects. However, targets and molecular mechanisms of Hemerocallis citrina Baroni edible flowers (HEF) in depression treatment are still unclear. The potential anti-depression targets in HEF were identified by the intersecting results from typical drug databases. The network construction and Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analysis were carried out for core targets. The molecular docking was conducted to predict the binding affinity between the active components and the central targets. The intersecting results indicated that there were 24 active components in HEF, with 449 anti-depression targets identified. After screening through degree centrality (DC), betweenness centrality (BC), and closeness centrality (CC), 166 core targets were determined. Tumor protein 53 (TP53) and interleukin 6 (IL-6) had the highest degree values. The results of GO enrichment analysis associated with anti-depression revealed that the biological processes were negative regulation of osteoclast differentiation and positive regulation of phosphorus metabolic process. KEGG enrichment analysis results revealed that pathways, such as the phosphatidylinositol 3‑kinase-protein kinase B (PI3K-Akt) signaling pathway and mitogen-activated protein kinase (MAPK) signaling pathway, were primarily associated with anti-depression. Molecular docking results indicated that the top 10 active ingredients in HEF could bind to the central targets. This study applied network pharmacology to unveil the potential anti-depressive mechanisms of HEF, providing a theoretical basis for further exploration of the effective components in H. citrina edible flower parts.

Mechanism of action of Salvia miltiorrhiza on avascular necrosis of the femoral head determined by integrated network pharmacology and molecular dynamics simulation

Avascular necrosis of the femoral head (ANFH) is a progressive, multifactorial, and challenging clinical condition that often leads to hip dysfunction and deterioration. The pathogenesis of ANFH is complex, and there is no foolproof treatment strategy. Although some pharmacologic and surgical treatments have been shown to improve ANFH, the associated side effects and poor prognosis are of concern. Therefore, there is an urgent need to explore therapeutic interventions with superior efficacy and safety to improve the quality of life of patients with ANFH. Salvia miltiorrhiza (SM), a traditional Chinese medicine with a long history, is widely used for the treatment of cardiovascular and musculoskeletal diseases due to its multiple pharmacological activities. However, the molecular mechanism of SM for the treatment of ANFH is still unclear. Therefore, this study aimed to explore the potential targets and mechanisms of SM for the treatment of ANFH using network pharmacology and molecular modeling techniques. By searching multiple databases, we screened 52 compounds and 42 common targets involved in ANFH therapy and identified dan-shexinkum d, cryptotanshinone, tanshinone iia, and dihydrotanshinlactone as key compounds. Based on the protein-protein interaction (PPI) network, TP53, AKT1, EGFR, STAT3, BCL2, IL6, and TNF were identified as core targets. Subsequent enrichment analysis revealed that these targets were mainly enriched in the AGE-RAGE, IL-17, and TNF pathways, which were mainly associated with inflammatory responses, apoptosis, and oxidative stress. In addition, molecular docking and 100 nanoseconds molecular dynamics (MD) simulations showed that the bioactive compounds of SM had excellent affinity and binding strength to the core targets. Among them, dan-shexinkum d possessed the lowest binding free energy (-215.874 kcal/mol and - 140.277 kcal/mol, respectively) for AKT1 and EGFR. These results demonstrated the multi-component, multi-target, and multi-pathway intervention mechanism of SM in the treatment of ANFH, which provided theoretical basis and clues for further experimental validation and development of anti-ANFH drugs.

Visual toxicity in zebrafish larvae following exposure to 2,2',4,4'-tetrabromodiphenyl ether (BDE-47), triphenyl phosphate (TPhP), and isopropyl phenyl diphenyl phosphate (IPPP)

TPhP and IPPP, alternatives to PBDEs as flame retardants, have been studied for their developmental toxicity, but their visual toxicities are less understood. In this study, zebrafish larvae were exploited to evaluate the potential ocular impairments following exposure to BDE-47, TPhP, and IPPP. The results revealed a range of ocular abnormalities, including malformation, vascular issues within the eyes, and histopathological changes in the retina. Notably, the visually mediated behavioral changes were primarily observed in IPPP and TPhP, indicating that they caused more severe eye malformations and vision impairment than BDE-47. Molecular docking and MD simulations showed stronger binding affinity of TPhP and IPPP to RAR and RBP receptors. Elevated ROS and T3 levels induced by these compounds led to apoptosis in larvae eyes, and increased GABA levels induced by TPhP and IPPP hindered retinal repair. In summary, our results indicate TPhP and IPPP exhibit severer visual toxicity than BDE-47, affecting eye development and visually guided behaviors. The underlying mechanism involves disruptions in RA signaling, retinal neurotransmitters imbalance, thyroid hormones up-regulation, and apoptosis in larvae eyes. This work highlights novel insights into the need for cautious use of these flame retardants due to their potential biological hazards, thereby offering valuable guidance for their safer applications.

Identification and evaluation of candidate COVID-19 critical genes and medicinal drugs related to plasma cells

The ongoing COVID-19 pandemic, caused by the SARS-CoV-2 virus, represents one of the most significant global health crises in recent history. Despite extensive research into the immune mechanisms and therapeutic options for COVID-19, there remains a paucity of studies focusing on plasma cells. In this study, we utilized the DESeq2 package to identify differentially expressed genes (DEGs) between COVID-19 patients and controls using datasets GSE157103 and GSE152641. We employed the xCell algorithm to perform immune infiltration analyses, revealing notably elevated levels of plasma cells in COVID-19 patients compared to healthy individuals. Subsequently, we applied the Weighted Gene Co-expression Network Analysis (WGCNA) algorithm to identify COVID-19 related plasma cell module genes. Further, positive cluster biomarker genes for plasma cells were extracted from single-cell RNA sequencing data (GSE171524), leading to the identification of 122 shared genes implicated in critical biological processes such as cell cycle regulation and viral infection pathways. We constructed a robust protein-protein interaction (PPI) network comprising 89 genes using Cytoscape, and identified 20 hub genes through cytoHubba. These genes were validated in external datasets (GSE152418 and GSE179627). Additionally, we identified three potential small molecules (GSK-1070916, BRD-K89997465, and idarubicin) that target key hub genes in the network, suggesting a novel therapeutic approach. These compounds were characterized by their ability to down-regulate AURKB, KIF11, and TOP2A effectively, as evidenced by their low free binding energies determined through computational analyses using cMAP and AutoDock. This study marks the first comprehensive exploration of plasma cells' role in COVID-19, offering new insights and potential therapeutic targets. It underscores the importance of a systematic approach to understanding and treating COVID-19, expanding the current body of knowledge and providing a foundation for future research.

Transplanting network pharmacology technology into food science research: A comprehensive review on uncovering food-sourced functional factors and their health benefits

Network pharmacology is an emerging interdisciplinary research method. The application of network pharmacology to reveal the nutritional effects and mechanisms of active ingredients in food is of great significance in promoting the development of functional food, facilitating personalized nutrition, and exploring the mechanisms of food health effects. This article systematically reviews the application of network pharmacology in the field of food science using a literature review method. The application progress of network pharmacology in food science is discussed, and the mechanisms of functional factors in food on the basis of network pharmacology are explored. Additionally, the limitations and challenges of network pharmacology are discussed, and future directions and application prospects are proposed. Network pharmacology serves as an important tool to reveal the mechanisms of action and health benefits of functional factors in food. It helps to conduct in-depth research on the biological activities of individual ingredients, composite foods, and compounds in food, and assessment of the potential health effects of food components. Moreover, it can help to control and enhance their functionality through relevant information during the production and processing of samples to guarantee food safety. The application of network pharmacology in exploring the mechanisms of functional factors in food is further analyzed and summarized. Combining machine learning, artificial intelligence, clinical experiments, and in vitro validation, the achievement transformation of functional factor in food driven by network pharmacology is of great significance for the future development of network pharmacology research.

Integrated network pharmacology and molecular docking to investigate the potential mechanism of Tufuling on Alzheimer's disease

Objective

This study aimed to investigate the mechanism of Tu Fu Ling in treating Alzheimer's disease (AD) using network pharmacology and molecular docking.

Methods

The TCMSP and Swiss target prediction databases were utilized to confirm the active components of Tu Fu Ling and their corresponding targets, with target gene names converted using the UniProt database. Genes related to AD were collected from DisGeNET, GeneCards, and the Open Target Platform databases. Common target genes between the disease and the drug were obtained using Venny 2.1 tools and visualized using Cytoscape software. Protein-protein interaction (PPI) data were further analyzed to determine correlations between common target genes, and GO and KEGG pathway enrichment analyses were performed for intersecting genes. Finally, PYmol, AutoDock Tool, Discovery Studio 2020, and PyRx software were used for preliminary computer virtual verification and visualization of active drug ingredients and target proteins.

Results

Nine active ingredients meeting the screening criteria yielded a total of 168 genes after removing duplicates. A total of 3833 target genes were collected, with 129 overlapping target genes identified. GO enrichment analysis identified 643 biological processes, 82 cellular components, and 147 molecular functions. KEGG pathway enrichment analysis also revealed a pathway closely related to AD (hsa05010: Alzheimer's disease). In molecular docking analysis, the binding affinity between the 9 active ingredients and 10 core targets ranged from -3.5 to -12.3 kcal/mol, indicating strong binding.

Conclusion

This study preliminarily verified the combination of Tu Fu Ling's screened active ingredient and the calculated core target, suggesting a potential mechanism of action to improve the symptoms of AD patients through multi-target and multi-pathway approaches. This provides a valuable reference for further exploration of the pharmacological mechanism of AD and the formulation of drug therapy.

Exploring the Mechanism of Asiatic Acid against Atherosclerosis Based on Molecular Docking, Molecular Dynamics, and Experimental Verification

Asiatic acid (AA) is a pentacyclic triterpene derived from the traditional medicine Centella asiatica. It is known for its anti-inflammatory, antioxidant, and lipid-regulating properties. Though previous studies have suggested its potential therapeutic benefits for atherosclerosis, its pharmacological mechanism is unclear. The objective of this study was to investigate the molecular mechanism of AA in the treatment of atherosclerosis. Therefore, network pharmacology was employed to uncover the mechanism by which AA acts as an anti-atherosclerotic agent. Furthermore, molecular docking, molecular dynamics (MD) simulation, and in vitro experiments were performed to elucidate the mechanism of AA's anti-atherosclerotic effects. Molecular docking analysis demonstrated a strong affinity between AA and PPARγ. Further MD simulations demonstrated the favorable stability of AA-PPARγ protein complexes. In vitro experiments demonstrated that AA can dose-dependently inhibit the expression of inflammatory factors induced by lipopolysaccharide (LPS) in RAW264.7 cells. This effect may be mediated through the PPARγ/NF-κB signaling pathway. This research underscores anti-inflammation as a crucial biological process in AA treatments for atherosclerosis, with PPARγ potentially serving as a key target.

Exploration on the potential efficacy and mechanism of methyl salicylate glycosides in the treatment of schizophrenia based on bioinformatics, molecular docking and dynamics simulation

The etiological and therapeutic complexities of schizophrenia (SCZ) persist, prompting exploration of anti-inflammatory therapy as a potential treatment approach. Methyl salicylate glycosides (MSGs), possessing a structural parent nucleus akin to aspirin, are being investigated for their therapeutic potential in schizophrenia. Utilizing bioinformation mining, network pharmacology, molecular docking and dynamics simulation, the potential value and mechanism of MSGs (including MSTG-A, MSTG-B, and Gaultherin) in the treatment of SCZ, as well as the underlying pathogenesis of the disorder, were examined. 581 differentially expressed genes related to SCZ were identified in patients and healthy individuals, with 349 up-regulated genes and 232 down-regulated genes. 29 core targets were characterized by protein-protein interaction (PPI) network, with the top 10 core targets being BDNF, VEGFA, PVALB, KCNA1, GRIN2A, ATP2B2, KCNA2, APOE, PPARGC1A and SCN1A. The pathogenesis of SCZ primarily involves cAMP signaling, neurodegenerative diseases and other pathways, as well as regulation of ion transmembrane transport. Molecular docking analysis revealed that the three candidates exhibited binding activity with certain targets with binding affinities ranging from -4.7 to -109.2 kcal/mol. MSTG-A, MSTG-B and Gaultherin show promise for use in the treatment of SCZ, potentially through their ability to modulate the expression of multiple genes involved in synaptic structure and function, ion transport, energy metabolism. Molecular dynamics simulation revealed good binding abilities between MSTG-A, MSTG-B, Gaultherin and ATP2B2. It suggests new avenues for further investigation in this area.

Network pharmacology and molecular dynamics study of the effect of the Astragalus-Coptis drug pair on diabetic kidney disease

BACKGROUND

Diabetic kidney disease (DKD) is the primary cause of end-stage renal disease. The Astragalus-Coptis drug pair is frequently employed in the management of DKD. However, the precise molecular mechanism underlying its therapeutic effect remains elusive.

AIM

To investigate the synergistic effects of multiple active ingredients in the Astragalus-Coptis drug pair on DKD through multiple targets and pathways.

METHODS

The ingredients of the Astragalus-Coptis drug pair were collected and screened using the TCMSP database and the SwissADME platform. The targets were predicted using the SwissTargetPrediction database, while the DKD differential gene expression analysis was obtained from the Gene Expression Omnibus database. DKD targets were acquired from the GeneCards, Online Mendelian Inheritance in Man database, and DisGeNET databases, with common targets identified through the Venny platform. The protein-protein interaction network and the "disease-active ingredient-target" network of the common targets were constructed utilizing the STRING database and Cytoscape software, followed by the analysis of the interaction relationships and further screening of key targets and core active ingredients. Gene Ontology (GO) function and Kyoto Ency-clopedia of Genes and Genomes (KEGG) pathway enrichments were performed using the DAVID database. The tissue and organ distributions of key targets were evaluated. PyMOL and AutoDock software validate the molecular docking between the core ingredients and key targets. Finally, molecular dynamics (MD) simulations were conducted to simulate the optimal complex formed by interactions between core ingredients and key target proteins.

RESULTS

A total of 27 active ingredients and 512 potential targets of the Astragalus-Coptis drug pair were identified. There were 273 common targets between DKD and the Astragalus-Coptis drug pair. Through protein-protein interaction network topology analysis, we identified 9 core active ingredients and 10 key targets. GO and KEGG pathway enrichment analyses revealed that Astragalus-Coptis drug pair treatment for DKD involves various biological processes, including protein phosphorylation, negative regulation of apoptosis, inflammatory response, and endoplasmic reticulum unfolded protein response. These pathways are mainly associated with the advanced glycation end products (AGE)-receptor for AGE products signaling pathway in diabetic complications, as well as the Lipid and atherosclerosis. Molecular docking and MD simulations demonstrated high affinity and stability between the core active ingredients and key targets. Notably, the quercetin-AKT serine/threonine kinase 1 (AKT1) and quercetin-tumor necrosis factor (TNF) protein complexes exhibited exceptional stability.

CONCLUSION

This study demonstrated that DKD treatment with the Astragalus-Coptis drug pair involves multiple ingredients, targets, and signaling pathways. We propose a novel approach for investigating the molecular mechanism underlying the therapeutic effects of the Astragalus-Coptis drug pair on DKD. Furthermore, we suggest that quercetin is the most potent active ingredient and specifically targets AKT1 and TNF, providing a theoretical foundation for further exploration of pharmacologically active ingredients and elucidating their molecular mechanisms in DKD treatment.

Molecular Mechanism of Yangshen Maidong Decoction in the Treatment of Chronic Heart Failure based on Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulations

Chronic heart failure (CHF) is a complex multifactorial clinical syndrome leading to abnormal cardiac structure and function. The severe form of this ailment is characterized by high disability, high mortality, and morbidity. Worldwide, 2-17% of patients die at first admission, of which 17-45% die within 1 year of admission and >50% within 5 years. Yangshen Maidong Decoction (YSMDD) is frequently used to treat the deficiency and pain of the heart. The specific mechanism of action of YSMDD in treating CHF, however, remains unclear. Therefore, a network pharmacology-based strategy combined with molecular docking and molecular dynamics simulations was employed to investigate the potential molecular mechanism of YSMDD against CHF. The effective components and their targets of YSMDD and related targets of CHF were predicted and screened based on the public database. The network pharmacology was used to explore the potential targets and possible pathways that involved in YSMDD treated CHF. Molecular docking and molecular dynamics simulations were performed to elucidate the binding affinity between the YSMDD and CHF targets. Screen results, 10 main active ingredients, and 6 key targets were acquired through network pharmacology analysis. Pathway enrichment analysis showed that intersectional targets associated pathways were enriched in the Prostate cancer pathway, Hepatitis B pathway, and C-type lectin receptor signaling pathways. Molecular docking and molecular dynamics simulations analysis suggested 5 critical active ingredients have high binding affinity to the 5 key targets. This research shows the multiple active components and molecular mechanisms of YSMDD in the treatment of CHF and offers resources and suggestions for future studies.

Elucidation of Anti-Obesity Mechanisms of Phenolics in Artemisiae argyi Folium (Aiye) by Integrating LC-MS, Network Pharmacology, and Molecular Docking

The global prevalence of obesity is a pressing health issue, increasing the medical burden and posing significant health risks to humans. The side effects and complications associated with conventional medication and surgery have spurred the search for anti-obesity drugs from plant resources. Previous studies have suggested that Artemisiae argyi Folium (Aiye) water extracts could inhibit pancreatic lipase activities, control body weight increase, and improve the plasma lipids profile. However, the exact components and mechanisms were not precisely understood. Therefore, this research aims to identify the chemical profile of Aiye and provide a comprehensive prediction of its anti-obesity mechanisms. The water extract of Aiye was subjected to LC-MS analysis, which identified 30 phenolics. The anti-obesity mechanisms of these phenolics were then predicted, employing network pharmacology and molecular docking. Among the 30 phenolics, 21 passed the drug-likeness screening and exhibited 486 anti-obesity targets. The enrichment analysis revealed that these phenolics may combat obesity through PI3K-Akt signaling and MAPK, prolactin, and cAMP signaling pathways. Eight phenolics and seven central targets were selected for molecular docking, and 45 out of 56 docking had a binding affinity of less than -5 kcal/mol. This research has indicated the potential therapy targets and signaling pathways of Aiye in combating obesity.

Exploring the mechanism of Jinlida granules against type 2 diabetes mellitus by an integrative pharmacology strategy

Jinlida granule (JLD) is a Traditional Chinese Medicine (TCM) formula used for the treatment of type 2 diabetes mellitus (T2DM). However, the mechanism of JLD treatment for T2DM is not fully revealed. In this study, we explored the mechanism of JLD against T2DM by an integrative pharmacology strategy. Active components and corresponding targets were retrieved from Traditional Chinese Medicine System Pharmacology (TCMSP), SwissADME and Bioinformatics Analysis Tool for Molecular Mechanisms of Traditional Chinese Medicine Database (BATMAN-TCM) database. T2DM-related targets were obtained from Drugbank and Genecards databases. The protein-protein interaction (PPI) network was constructed and analyzed with STRING (Search Toll for the Retrieval of Interacting Genes/proteins) and Cytoscape to get the key targets. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genomes (KEGG) enrichment analyses were performed with the Database for Annotation, Visualization and Integrated Discovery (DAVID). Lastly, the binding capacities and reliability between potential active components and the targets were verified with molecular docking and molecular dynamics simulation. In total, 185 active components and 337 targets of JLD were obtained. 317 targets overlapped with T2DM-related targets. RAC-alpha serine/threonine-protein kinase (AKT1), tumor necrosis factor (TNF), interleukin-6 (IL-6), cellular tumor antigen p53 (TP53), prostaglandin G/H synthase 2 (PTGS2), Caspase-3 (CASP3) and signal transducer and activator of transcription 3 (STAT3) were identified as seven key targets by the topological analysis of the PPI network. GO and KEGG enrichment analyses showed that the effects were primarily associated with gene expression, signal transduction, apoptosis and inflammation. The pathways were mainly enriched in PI3K-AKT signaling pathway and AGE-RAGE signaling pathway in diabetic complications. Molecular docking and molecular dynamics simulation verified the good binding affinity between the key components and targets. The predicted results may provide a theoretical basis for drug screening of JLD and a new insight for the therapeutic effect of JLD on T2DM.

General Direct Anticancer Effects of Deer Growing Antler Extract in Several Tumour Cell Lines, and Immune System-Mediated Effects in Xenograft Glioblastoma

Deer antlers are the fastest growing tissue. Because they are based on proto-oncogenes, to avoid the risk of cancer, antlers evolved strong anticancer mechanisms, and thus their extract (DVA) is effective also against the few human tumours studied so far. We assessed whether DVA is a general anticancer compound by testing the direct effects in cells of different tumours: glioblastoma (GBM; lines U87MG and U251), colorectal (CRC; lines DLD-1, HT-29, SW480, and SW620), breast cancer (BRCA; lines MCF7, SKBR3, and PA00), and leukaemia (THP-1). DVA reduced the viability of tumours but not healthy cells (NHC; lines 293T and HaCaT). Mobility decreased at least for the longest test (72 h). Intraperitoneal/oral 200 mg DVA/kg administration in GBM xenograft mice for 28 d reduced tumour weight by 66.3% and 61.4% respectively, and it also reduced spleen weight (43.8%). In addition, tumours treated with DVA showed symptoms of liquefactive necrosis. Serum cytokines showed DVA up-regulated factors related to tumour fighting and down-regulated those related to inducing immune tolerance to the tumour. DVA shows general anticancer effects in the lines tested and, in GBM mice, also strong indirect effects apparently mediated by the immune system. DVA may contain a future anticancer medicine without secondary effects.

Abatement of the binding of human hexokinase II enzyme monomers by in-silico method with the design of inhibitory peptides

The hexokinase II enzyme is bound to the (VDAC1) channel in the form of a dimer and prevents the release of cell death factors from mitochondria to the cytoplasm. Studies have shown that blocking the binding of hexokinase II enzyme to (VDAC1) led to the initiation of apoptosis in cancer cells. No peptide has been designed so far to inhibit hexokinase II. The aim of this study was to inhibit the dimerization of enzyme subunits in order to inhibition the formation of (VDAC1) and the hexokinase II complex. In this study, the molecular dynamics simulation of the enzyme in monomer and dimer states was investigated in terms of RMSF, RMSD and radius of gyration. The following process involves extracting and designing variable-length peptides from the interacting segments of enzyme monomers. Using molecular dynamics simulation, the stability of the peptide was determined in terms of RMSD. Molecular docking was used to investigate the interaction between the designed peptides. Finally, the inhibitory effect of peptides on subunit association was measured using dynamic light scattering (DLS) technique. Our results showed that the designed peptides, which mimic common amino acids in dimerization, interrupt the bona fide form of the enzyme subunits. The result of this study provides a new way to disrupt the assembly process and thereby decreased the function of the hexokinase II.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-024-00201-8.

Elucidating the anti-cancer potential of Cinnamomum tamala essential oil against non-small cell lung cancer: A multifaceted approach involving GC-MS profiling, network pharmacology, and molecular dynamics simulations

Cinnamomum tamala (Buch.-Ham.) T.Nees & Eberm., or Indian Bay Leaf, is a well-known traditional ayurvedic medicine used to treat various ailments. However, the molecular mechanism of action of Cinnamomum tamala essential oil (CTEO) against non-small cell lung cancer (NSCLC) remains elusive. The present study aims to decipher the molecular targets and mechanism of CTEO in treating NSCLC. GC-MS analysis detected 49 constituents; 44 successfully passed the drug-likeness screening and were identified as active compounds. A total of 3961 CTEO targets and 4588 anti-NSCLC-related targets were acquired. JUN, P53, IL6, MAPK3, HIF1A, and CASP3 were determined as hub genes, while cinnamaldehyde, ethyl cinnamate and acetophenone were identified as core compounds. Enrichment analysis revealed that targets were mainly involved in apoptosis, TNF, IL17, pathways in cancer and MAPK signalling pathways. mRNA expression, pathological stage, survival analysis, immune infiltrate correlation and genetic alteration analysis of the core hub genes were carried out. Kaplan-Meier overall survival (OS) curve revealed that HIF1A and CASP3 are linked to worse overall survival in Lung Adenocarcinoma (LUAD) cancer patients compared to normal patients. Ethyl cinnamate and cinnamaldehyde showed high binding energy with the MAPK3 and formed stable interactions with MAPK3 during the molecular dynamic simulations for 100 ns. The MM/PBSA analysis revealed that van der Waals (VdW) contributions predominantly account for a significant portion of the compound interactions within the binding pocket of MAPK3. Density functional theory analysis showed cinnamaldehyde as the most reactive and least stable compound. CTEO exhibited selective cytotoxicity by inhibiting the proliferation of A549 cells while sparing normal HEK293 cells. CTEO triggered apoptosis by arresting the cell cycle, increasing ROS accumulation, causing mitochondrial depolarisation, and elevating caspase-3, caspase-8 and caspase-9 levels in A549 cells. The above study provides insights into the pharmacological mechanisms of action of Cinnamomum tamala essential oil against non-small cell lung cancer treatment, suggesting its potential as an adjuvant therapy.

Exploring the effect and mechanism of Aloin A against cancer cachexia-induced muscle atrophy via network pharmacology, molecular docking, molecular dynamics and experimental validation

80% of advanced cancer patients suffer from cachexia, but there are no FDA-approved drugs. Therefore, it is imperative to discover potential drugs.

OBJECTIVE

This study aims at exploring the effect and targets of Aloin A against cancer cachexia (CC)-induced muscle atrophy.

METHODS

Network pharmacology, molecular docking, molecular dynamics (MD) and animal model of CC-induced muscle atrophy with a series of behavior tests, muscle quality, HE staining and RT-PCR were performed to investigate the anticachectic effects and targets of Aloin A and its molecular mechanism.

RESULTS

Based on network pharmacology, 51 potential targets of Aloin A on CC-induced muscle atrophy were found, and then 10 hub genes were predicted by the PPI network. Next, KEGG and GO enrichment analysis showed that the anticachectic effect of Aloin A is associated with PI3K-AKT, MAPK, TNF, TLR, etc., pathways, and biological processes like inflammation, apoptosis and cell proliferation. Molecular docking and MD results showed good binding ability between the Aloin A and key targets. Moreover, experiments in vivo demonstrated that Aloin A effectively rescued muscle function and wasting by improving muscle quality, mean CSA, and distribution of muscle fibers by regulating HSP90AA1/AKT signaling in tumor-bearing mice.

CONCLUSION

This study offers new insights for researchers to understand the effect and mechanism of Aloin A against CC using network pharmacology, molecular docking, MD and experimental validation, and Aloin A retards CC-induced muscle wasting through multiple targets and pathways, including HSP90AA1/AKT signaling, which provides evidence for Aloin A as a potential therapy for cancer cachexia in clinic.

Exploring the potential mechanism of Taohong Siwu decoction in the treatment of avascular necrosis of the femoral head based on network pharmacology and molecular docking

Based on network pharmacology and molecular docking, this study seeks to investigate the mechanism of Taohong Siwu decoction (THSWD) in the treatment of avascular necrosis of the femoral head (AVNFH). The Traditional Chinese Medicine Systems Pharmacology database was used in this investigation to obtain the active ingredients and related targets for each pharmaceutical constituent in THSWD. To find disease-related targets, the terms "avascular necrosis of the femoral head," "necrosis of the femoral head," "steroid-induced necrosis of the femoral head," "osteonecrosis," and "avascular necrosis of the bone" were searched in the databases DisGeNET, GeneCards, Comparative Toxicogenomics Database, and MalaCards. Following the identification of the overlap targets of THSWD and AVNFH, enrichment analysis using gene ontology, Kyoto Encyclopedia of Genes and Genomes, Reactome, and WikiPathways was conducted. The "THSWD-drug-active compound-intersection gene-hub gene-AVNFH" network and protein-protein interaction network were built using Cytoscape 3.9.1 and string, and CytoHubba was used to screen hub genes. The binding activities of hub gene targets and key components were confirmed by molecular docking. 152 prospective therapeutic gene targets were found in the bioinformatics study of ONFH treated with THSWD, including 38 major gene targets and 10 hub gene targets. The enrichment analysis of 38 key therapeutic targets showed that the biological process of gene ontology analysis mainly involved cytokine-mediated signaling pathway, angiogenesis, cellular response to reactive oxygen species, death-inducing signaling complex. The Kyoto Encyclopedia of Genes and Genomes signaling pathway mainly involves TNF signaling pathway, IL-17 signaling pathway, and the Recactome pathway mainly involves Signaling by Interleukins, Apoptosis, and Intrinsic Pathway for Apoptosis. WikiPathways signaling pathway mainly involves TNF-related weak inducer of apoptosis signaling pathway, IL-18 signaling pathway. According to the findings of enrichment analysis, THSWD cured AVNFH by regulating angiogenesis, cellular hypoxia, inflammation, senescence, apoptosis, cytokines, and cellular proliferation through the aforementioned targets and signaling pathways. The primary component of THSWD exhibits a strong binding force with the key protein of AVNFH. This study sheds new light on the biological mechanism of THSWD in treating AVNFH by revealing the multi-component, multi-target, and multi-pathway features and molecular docking mechanism of THSWD.