Investigations into the therapeutic potential of Astragalus Mongholicus (AM, huáng qí) and Largehead Atractylodes (LA, bái zhú) reveal significant efficacy in mitigating the onset and progression of knee osteoarthritis (KOA), albeit with an elusive mechanistic understanding. This study delineates the primary bioactive constituents and their molecular targets within the AM-LA synergy by harnessing the comprehensive Traditional Chinese Medicine (TCM) network databases, including TCMSP, TCMID, and ETCM. Furthermore, an analysis of 3 gene expression datasets, sourced from the gene expression omnibus database, facilitated the identification of differential genes associated with KOA. Integrating these findings with data from 5 predominant databases yielded a refined list of KOA-associated targets, which were subsequently aligned with the gene signatures corresponding to AM and LA treatment. Through this alignment, specific molecular targets pertinent to the AM-LA therapeutic axis were elucidated. The construction of a protein-protein interaction network, leveraging the shared genetic markers between KOA pathology and AM-LA intervention, enabled the identification of pivotal molecular targets via the topological analysis facilitated by CytoNCA plugins. Subsequent GO and KEGG enrichment analyses fostered the development of a holistic herbal-ingredient-target network and a core target-signal pathway network. Molecular docking techniques were employed to validate the interaction between 5 central molecular targets and their corresponding active compounds within the AM-LA complex. Our findings suggest that the AM-LA combination modulates key biological processes, including cellular activity, reactive oxygen species modification, metabolic regulation, and the activation of systemic immunity. By either augmenting or attenuating crucial signaling pathways, such as MAPK, calcium, and PI3K/AKT pathways, the AM-LA dyad orchestrates a comprehensive regulatory effect on immune-inflammatory responses, cellular proliferation, differentiation, apoptosis, and antioxidant defenses, offering a novel therapeutic avenue for KOA management. This study, underpinned by gene expression omnibus gene chip analyses and network pharmacology, advances our understanding of the molecular underpinnings governing the inhibitory effects of AM and LA on KOA progression, laying the groundwork for future explorations into the active components and mechanistic pathways of TCM in KOA treatment.

BACKGROUND: Salidroside (SAL), the main component of Rhodiola rosea extract, is a flavonoid with biological activities, such as antioxidative stress, anti-inflammatory, and hypolipidemic. In this study, the potential therapeutic targets and mechanisms of SAL against oxidative stress in retinal ganglion cells (RGCs) were investigated on the basis of in-vitro experiments, network pharmacology, and molecular docking techniques.
METHODS: RGC oxidative stress models were constructed, and cell activity, reactive oxygen species (ROS), and apoptosis levels were examined for differences. The genes corresponding to rhodopsin, RGCs, and oxidative stress were screened from GeneCards, TCMSP database, and an analysis platform. The intersection of the three was taken, and a Venn diagram was drawn. Protein interactions, GO functional enrichment, and KEGG pathway enrichment data were analyzed by STRING database, Cytohubba plugin, and Metascape database. The key factors in the screening pathway were validated using qRT-PCR. Finally, molecular docking prediction was performed using MOE 2019 software, molecular dynamic simulations was performed using Gromacs 2018 software.
RESULTS: In the RGC oxidative stress model in vitro, the cell activity was enhanced, ROS was reduced, and apoptosis was decreased after SAL treatment. A total of 16 potential targets of oxidative stress in SAL RGCs were obtained, and the top 10 core targets were screened by network topology analysis. GO analysis showed that SAL retinal oxidative stress treatment mainly involved cellular response to stress, transcriptional regulatory complexes, and DNA-binding transcription factor binding. KEGG analysis showed that most genes were mainly enriched in multiple cancer pathways and signaling pathways in diabetic complications, nonalcoholic fatty liver, and lipid and atherosclerosis. Validation by PCR, molecular docking and molecular dynamic simulations revealed that SAL may attenuate oxidative stress and reduce apoptosis in RGCs by regulating SIRT1, NRF2, and NOS3.
CONCLUSIONS: This study initially revealed the antioxidant therapeutic effects and molecular mechanisms of SAL on RGCs, providing a theoretical basis for subsequent studies.

BACKGROUND: Patients with non-small cell lung cancer (NSCLC) are susceptible to coronavirus disease-2019 (COVID-19), but current treatments are limited. Icariside II (IS), a flavonoid compound derived from the plant epimedin, showed anti-cancer,anti-inflammation and immunoregulation effects. The present study aimed to evaluate the possible effect and underlying mechanisms of IS on NSCLC patients with COVID-19 (NSCLC/COVID-19).
METHODS: NSCLC/COVID-19 targets were defined as the common targets of NSCLC (collected from The Cancer Genome Atlas database) and COVID-19 targets (collected from disease database of Genecards, OMIM, and NCBI). The correlations of NSCLC/COVID-19 targets and survival rates in patients with NSCLC were analyzed using the survival R package. Prognostic analyses were performed using univariate and multivariate Cox proportional hazards regression models. Furthermore, the targets in IS treatment of NSCLC/COVID-19 were defined as the overlapping targets of IS (predicted from drug database of TMSCP, HERBs, SwissTarget Prediction) and NSCLC/COVID-19 targets. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis of these treatment targets were performed aiming to understand the biological process, cellular component, molecular function and signaling pathway. The hub targets were analyzed by a protein-protein interaction network and the binding capacity with IS was characterized by molecular docking.
RESULTS: The hub targets for IS in the treatment of NSCLC/COVID-19 includes F2, SELE, MMP1, MMP2, AGTR1 and AGTR2, and the molecular docking results showed that the above target proteins had a good binding degree to IS. Network pharmacology showed that IS might affect the leucocytes migration, inflammation response and active oxygen species metabolic process, as well as regulate the interleukin-17, tumor necrosus factor and hypoxia-inducible factor-1 signaling pathway in NSCLC/COVID-19.
CONCLUSIONS: IS may enhance the therapeutic efficacy of current clinical anti-inflammatory and anti-cancer therapy to benefit patients with NSCLC combined with COVID-19.

UNASSIGNED: Renshen Yangrong decoction (RSYRD) has been shown therapeutic effects on secondary malaise and fatigue (SMF). However, to date, its bioactive ingredients and potential targets remain unclear.
UNASSIGNED: The purpose of this study is to assess the potential ingredients and targets of RSYRD on SMF through a comprehensive strategy integrating network pharmacology, Mendelian randomization as well as molecular docking verification.
UNASSIGNED: Search for potential active ingredients and corresponding protein targets of RSYRD on TCMSP and BATMAN-TCM for network pharmacology analysis. Mendelian randomization (MR) was performed to find therapeutic targets for SMF. The eQTLGen Consortium (sample sizes: 31,684) provided data on cis-expression quantitative trait loci (cis-eQTL, exposure). The summary data on SMF (outcome) from genome-wide association studies (GWAS) were gathered from the MRC-IEU Consortium (sample sizes: 463,010). We built a target interaction network between the probable active ingredient targets of RSYRD and the therapeutic targets of SMF. We next used drug prediction and molecular docking to confirm the therapeutic value of the therapeutic targets.
UNASSIGNED: In RSYRD, network pharmacology investigations revealed 193 possible active compounds and 234 associated protein targets. The genetically predicted amounts of 176 proteins were related to SMF risk in the MR analysis. Thirty-seven overlapping targets for RSYRD in treating SMF, among which six (NOS3, GAA, IMPA1, P4HTM, RB1, and SLC16A1) were prioritized with the most convincing evidence. Finally, the 14 active ingredients of RSYRD were identified as potential drug molecules. The strong affinity between active components and putative protein targets was established by molecular docking.
UNASSIGNED: This study revealed several active components and possible RSYRD protein targets for the therapy of SMF and provided novel insights into the feasibility of using Mendelian randomization for causal inference between Chinese medical formula and disease.

BACKGROUND: Salvia miltiorrhiza Bunge (S. miltiorrhiza) is an important Traditional Chinese herbal Medicine (TCM) used to treat cardio-cerebrovascular diseases. Based on the pharmacodynamic substance of S. miltiorrhiza, the aim of present study was to investigate the underlying mechanism of S. miltiorrhiza against cardiac fibrosis (CF) through a systematic network pharmacology approach, molecular docking and dynamics simulation as well as experimental investigation in vitro.
METHODS: A systematic pharmacological analysis was conducted using the Traditional Chinese Medicine Pharmacology (TCMSP) database to screen the effective chemical components of S. miltiorrhiza, then the corresponding potential target genes of the compounds were obtained by the Swiss Target Prediction and TCMSP databases. Meanwhile, GeneCards, DisGeNET, OMIM, and TTD disease databases were used to screen CF targets, and a protein-protein interaction (PPI) network of drug-disease targets was constructed on S. miltiorrhiza/CF targets by Search Tool for the Retrieval of Interacting Genes/Proteins (STING) database. After that, the component-disease-target network was constructed by software Cytoscape 3.7. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed for the intersection targets between drug and disease. The relationship between active ingredient of S. miltiorrhiza and disease targets of CF was assessed via molecular docking and molecular dynamics simulation. Subsequently, the underlying mechanism of the hub compound on CF was experimentally investigated in vitro.
RESULTS: 206 corresponding targets to effective chemical components from S. miltiorrhiza were determined, and among them, there were 82 targets that overlapped with targets of CF. Further, through PPI analysis, AKT1 and GSK3β were the hub targets, and which were both enriched in the PI3K/AKT signaling pathway, it was the sub-pathways of the lipid and atherosclerosis pathway. Subsequently, compound-disease-genes-pathways diagram is constructed, apigenin (APi) was a top ingredients and AKT1 (51) and GSK3β (22) were the hub genes according to the degree value. The results of molecular docking and dynamics simulation showed that APi has strong affinities with AKT and GSK3β. The results of cell experiments showed that APi inhibited cells viability, proliferation, proteins expression of α-SMA and collagen I/III, phosphorylation of AKT1 and GSK3β in MCFs induced by TGFβ1.
CONCLUSIONS: Through a systematic network pharmacology approach, molecular docking and dynamics simulation, and confirmed by in vitro cell experiments, these results indicated that APi interacts with AKT and GSK3β to disrupt the phosphorylation of AKT and GSK3β, thereby inhibiting the proliferation and differentiation of MCFs induced by TGFβ1, which providing new insights into the pharmacological mechanism of S. miltiorrhiza in the treatment of CF.

BACKGROUND: Inflammation is directly related to disease progression and contributes significantly to the global burden of disease. Pothos chinensis (Raf.) Merr. (PCM) is commonly used in Yao medicine in China to treat tumors, and orthopedic illnesses such as knee osteoarthritis, and rheumatic bone discomfort. PCM was found to have significant anti-inflammatory properties in previous studies.
OBJECTIVE: To explore the active compounds of PCM and their anti-inflammatory pharmacological mechanisms through an integrated strategy of serum pharmacochemistry, network pharmacology, and serum metabolomics.
METHODS: The qualitative and quantitative analyses of the chemical components of PCM were performed using UPLC-QTOF-MS/MS and UPLC, respectively, and the prototype components of PCM absorbed into the blood were analyzed. Based on the characterized absorbed into blood components, potential targets and signaling pathways of PCM anti-inflammatory were found using network pharmacology. Furthermore, metabolomics studies using UPLC-QTOF-MS/MS identified biomarkers and metabolic pathways related to the anti-inflammatory effects of PCM. Finally, the hypothesized mechanisms were verified by in vivo and in vitro experiments.
RESULTS: Forty chemical components from PCM were identified for the first time, and seven of them were quantitatively analyzed, while five serum migratory prototype components were found. Network pharmacology KEGG enrichment analysis revealed that arachidonic acid metabolism, Tyrosine metabolism, TNF signaling pathway, NF-κB signaling pathway, and phenylalanine metabolism were the main signaling pathways of PCM anti-inflammatory. Pharmacodynamic results showed that PCM ameliorated liver injury and inflammatory cell infiltration and downregulated protein expression of IL-1β, NF-κB p65, and MyD88 in the liver. Metabolomics studies identified 53 different serum metabolites, mainly related to purine and pyrimidine metabolism, phenylalanine metabolism, primary bile acid biosynthesis, and glycerophospholipid metabolism. The comprehensive results demonstrated that the anti-inflammatory modulatory network of PCM was related to 5 metabolites, 3 metabolic pathways, 7 targets, and 4 active components of PCM. In addition, molecular docking identified the binding ability between the active ingredients and the core targets, and the anti-inflammatory efficacy of the active ingredients was verified by in vitro experiments.
CONCLUSIONS: Our study demonstrated the anti-inflammatory effect of PCM, and these findings provide new insights into the active ingredients and metabolic mechanisms of PCM in anti-inflammation.

UNASSIGNED: Despite the availability of around 30 antiseizure medications, 1/3 of patients with epilepsy fail to become seizure-free upon pharmacological treatment. Available medications provide adequate symptomatic control in two-thirds of patients, but disease-modifying drugs are still scarce. Recently, though, new paradigms have been explored.
UNASSIGNED: Three areas are reviewed in which a high degree of innovation in the search for novel antiseizure and antiepileptogenic medications has been implemented: development of novel screening approaches, search for novel therapeutic targets, and adoption of new drug discovery paradigms aligned with a systems pharmacology perspective.
UNASSIGNED: In the past, worldwide leaders in epilepsy have reiteratively stated that the lack of progress in the field may be explained by the recurrent use of the same molecular targets and screening procedures to identify novel medications. This landscape has changed recently, as reflected by the new Epilepsy Therapy Screening Program and the introduction of many in vitro and in vivo models that could possibly improve our chances of identifying first-in-class medications that may control drug-resistant epilepsy or modify the course of disease. Other milestones include the study of new molecular targets for disease-modifying drugs and exploration of a systems pharmacology perspective to design new drugs.

UNASSIGNED: Although previous clinical studies and animal experiments have demonstrated the efficacy of Gegen Qinlian Decoction (GQD) in treating Type 2 Diabetes Mellitus (T2DM) and Ulcerative Colitis (UC), the underlying mechanisms of its therapeutic effects remain elusive.
UNASSIGNED: This study aims to investigate the shared pathogenic mechanisms between T2DM and UC and elucidate the mechanisms through which GQD modulates these diseases using bioinformatics approaches.
UNASSIGNED: Data for this study were sourced from the Gene Expression Omnibus (GEO) database. Targets of GQD were identified using PharmMapper and SwissTargetPrediction, while targets associated with T2DM and UC were compiled from the DrugBank, GeneCards, Therapeutic Target Database (TTD), DisGeNET databases, and differentially expressed genes (DEGs). Our analysis encompassed six approaches: weighted gene co-expression network analysis (WGCNA), immune infiltration analysis, single-cell sequencing analysis, machine learning, DEG analysis, and network pharmacology.
UNASSIGNED: Through GO and KEGG analysis of weighted gene co-expression network analysis (WGCNA) modular genes and DEGs intersection, we found that the co-morbidity between T2DM and UC is primarily associated with immune-inflammatory pathways, including IL-17, TNF, chemokine, and toll-like receptor signaling pathways. Immune infiltration analysis supported these findings. Three distinct machine learning studies identified IGFBP3 as a biomarker for GQD in treating T2DM, while BACE2, EPHB4, and EPHA2 emerged as biomarkers for GQD in UC treatment. Network pharmacology revealed that GQD treatment for T2DM and UC mainly targets immune-inflammatory pathways like Toll-like receptor, IL-17, TNF, MAPK, and PI3K-Akt signaling pathways.
UNASSIGNED: This study provides insights into the shared pathogenesis of T2DM and UC and clarifies the regulatory mechanisms of GQD on these conditions. It also proposes novel targets and therapeutic strategies for individuals suffering from T2DM and UC.

Previous studies have indicated the efficacy of momordin Ic (MIc), a plant-derived triterpenoid, against several types of cancers, implying its potential for further development. However, comprehensive insights into the molecular mechanisms and targets of MIc in cholangiocarcinoma (CCA) are lacking. This study aimed to investigate the actions of MIc against CCA at the molecular level. Network pharmacology analysis was first employed to predict the mechanisms and targets of MIc. The results unveiled the potential involvement of MIc in apoptosis and cell migration, pinpointing Src and FAK as key targets. Subsequently, cell-based assays, in accordance with FAK/Src-associated metastasis, were conducted, demonstrating the ability of MIc to attenuate the metastatic behaviours of KKU-452 cells. The in vitro results further indicated the capability of MIc to suppress the epithelial-mesenchymal transition (EMT) process, notably by downregulating EMT regulators, including N-cadherin, vimentin, ZEB2 and FOXC1/2 expression. Furthermore, MIc suppressed the activation of the FAK/Src signalling pathway, influencing critical downstream factors such as MMP-9, VEGF, ICAM-1, and c-Myc. Molecular docking simulations also suggested that MIc could interact with FAK and Src domains and restrain kinases from being activated by hindering ATP binding. In conclusion, this study employs a comprehensive approach encompassing network pharmacology analysis, in vitro assays, and molecular docking to unveil the mechanisms and targets of MIc in CCA. MIc mitigates metastatic behaviours and suppresses key pathways, offering a promising avenue for future therapeutic strategies against this aggressive cancer.

UNASSIGNED: Based on network pharmacology and experimental validation, this study aimed to screen the potential targets of Liuwei Dihuang decoction (LW) against mild cognitive impairment (MCI).
UNASSIGNED: Based on network pharmacology, this study preliminarily explored the targets and molecular mechanisms of LW in the treatment of MCI. The results showed that the mechanism of action of LW against MCI may be related to the cAMP pathway. Then, an aging cell and animal model was established to further verify its molecular mechanism.
UNASSIGNED: A total of 23 active ingredients were identified in LW. In addition, through network pharmacological analysis, we found 22 anti-MCI active ingredients in LW, of which alisol B had the most significant effect, and predicted the potential mechanism pathway by which LW may improve MCI through the cAMP signaling pathway. Further in vivo and in vitro experiments confirmed that LW can alleviate cognitive dysfunction in aging mice and reduce D-galactose-induced senescent cells, which may be through activation of the cAMP/PKA/CREB signaling pathway.
UNASSIGNED: This study found that the traditional Chinese medicine formula LW may play a role in improving MCI by regulating the cAMP/PKA/CREB signaling pathway, which provides a reference for further clinical research on the anti-MCI effect of LW and its molecular mechanism.