Protein-protein Interaction Network Research Articles

Identification of Crosstalk Genes between Lung Adenocarcinoma and Periodontitis.

Lung adenocarcinoma (LUAD) represents a significant global health issue. Smoking contributes to the development of periodontitis and LUAD. The connections between the two are still ambiguous. Based on RNA expression data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, differentially expressed genes (DEGs) in Periodontitis and LUAD were collected. Protein-protein interaction (PPI) networks were produced by mining genes intersecting with crossover DEGs. Genes in the subnetwork and the top 15 genes of the topology score were defined as the crosstalk gene. Feature selection and diagnostic model construction were conducted based on Recursive Feature Elimination (RFE) and support vector machines (SVM). Additionally, we analyzed the immune cells and signaling pathways influenced by the crosstalk gene. A total of 29 crossover DEGs between Periodontitis and LUAD were filtered, with 20 genes interacting with them in the PPI network. Five subnetworks with similar interaction patterns in the PPI network were detected. Based on the network topology analysis, genes ranking in the top 15 were used to take the intersection with those genes in the 5 subnetworks. Twelve intersecting genes were identified. Based on RFE and SVM algorithms, FKBP11 and MMP13 were considered as the Crosstalk genes for both Periodontitis and LUAD. The diagnostic model composed of FKBP11 and MMP13 showed excellent diagnostic potential. In addition, we found that FKBP11 and MMP13 influenced Macrophages, M1, T cells, CD8 activity, immune-related pathways, and cell cycle pathways. We identified the crosstalk genes (FKBP11 and MMP13) between periodontitis and LUAD. The two genes affected the comorbidity status between the two diseases through immune cell activity.

Revealing key proteins in comparison of tumor and para-tumor tissues in stage I esophageal squamous cell carcinoma: A combined gene expression clustering and protein interaction network analysis

Esophageal Squamous Cell Carcinoma (ESCC) which is diagnosed in advanced stages and metastasis to the vital organs, remained the sixth fatal malignancy among other types of cancer-related death. Considering the lack of specific clinical symptoms in the early development of the disease, finding suitable biomarkers and tissue-specific alterations for effective screening of ESCC is targeted in this project. Gene expression profiles of tumor tissue and para-tumors of stage I ESCC patients were retrieved from the Gene Expression Omnibus (GEO) database. The significant tissue-specific differentially expressed genes (DEGs) were identified and studied based on fold change distribution and the functional role of genes in the action map. A total number of 11,483 significant DEGs discriminated the tumor tissue from para-tumor tissue. Clustering analysis of significant DEGs led to identifying 220 DEGs as the final significant genes. Protein interaction network and action map analysis of the final gene list showed matrix metallopeptidase-9 (MMP9) as the critical gene related to the development of ESCC diseases in stage I. Significant expression change of MMP9 in esophageal carcinoma was validated in UALCAN (The University of Alabama at Birmingham Cancer Data Analysis Portal). This study highlighted the pivotal role of MMP9 in combination with SPP1, MMP13, and IL18 as a possible biomarkers panel in studies of tumor invasion and prognosis for stage I ESCC disease.

Gene prioritization-based Active Bio-module identification for Bioinformatics

Massive multi-omics data are being used to research cancer pathogenesis at the molecular level as high-throughput sequencing technology advances. Many present approaches frequently fail to detect strongly coupled modules that are intimately associated with cancer. By combining two forms of omics data, a technique to active bio-module identification known as IdeMod is proposed, which employs gene expression and protein-protein interaction networks. IdeMod is a p-step random walk kernel regression model-based gene activity score algorithm that uses the Pareto optimum consensus (POC) method's dominance connections to generate a prioritised list of genes. IdeMod uses the SA GPROX simulated annealing technique to identify the PPI network's most linked and high-priority bio-modules. The techniques RegMod, LEAN, SigMod, ModFinder, and IdeMod were experimentally tested on real-world cervical and BRCA datasets. These findings show that the IdeMod algorithm may identify a densely linked module containing multiple genes that either promote or hinder tumour growth. The BRCA1 gene increases the likelihood of developing hereditary breast cancer associated with BRCA mutations. As a result, the IdeMod technique can be used in conjunction with other tools to detect bio-modules.

Molecular docking and transcriptomic analysis reveal the mechanism of myosin-derived peptides activating bitter receptor of hT2R1

To better understand the bitterness effect and molecule mechanism of myosin-derived peptides activating bitter receptors, the interaction between myosin-derived peptides of dry-cured ham and bitter receptors was investigated by molecular docking and molecular dynamics simulation; the signal transduction mechanism of myosin-derived peptides was explored by HEK-293T cells using calcium imaging and transcriptomics analysis. Lower CDOCKER energy was observed during the interaction between myosin-derived peptides and hT2R1 by molecular docking compared with hT2R4, hT2R5, hT2R8, hT2R14 and hT2R16. Hydrogen bonds and hydrophobic interaction were the most important interaction forces which stabilized the interaction of hT2R1 and myosin-derived peptides. Compared with LEKEKSELK and TEELEEAKK, the RMSF values and EC50 values of HVLATLGEK were lower, indicating that hT2R1 was more sensitive to HVLATLGEK stimulation. Transcriptomics and KEGG analyses showed that 767 differentially expressed genes were found and mainly involved in cAMP signaling pathway, neuroactive ligand-receptor interaction, calcium signaling pathway and MAPK signaling pathway after stimulating of HVLATLGEK. Protein-protein interaction network further demonstrated that DDIT3, FOS, FOSB, MYC, EGR1 and CCN2 were the key genes to connect the six functional clusters including ligand-receptor interaction and signal transduction.

Transcriptome signature for multiple biotic and abiotic stress in barley (Hordeum vulgare L.) identifies using machine learning approach

Barley (Hordeum vulgare L.) is exposed to various biotic and abiotic stresses, making it crucial to fully understand the gene signatures that respond to stress. This study utilizes machine learning to analyze transcriptomic data from 515 RNA-seq profiles across 18 independent studies, covering eleven abiotic and three biotic stress types. Through meticulous data preprocessing, including quality assessment and batch effect correction, we have identified 4,311 genes for further analysis. Feature selection was performed using five weighting algorithms, resulting in the prioritization of 400 core genes. Machine learning models, specifically Random Forest and C4.5, were optimized and evaluated using a 10-fold cross-validation approach. The C4.5 algorithm demonstrated superior accuracy in predicting stress-responsive signatures. Key genes, such as bHLH119 and E3 ubiquitin protein ligase DRIP2, were identified as potential biomarkers. Functional enrichment analysis, conducted through protein-protein interaction networks and Gene Ontology/KEGG pathway analysis, has revealed significant involvement in lipid biosynthesis, signal transduction, and defense response processes. These findings highlight the crucial roles of the identified biomarkers genes in barley's resilience to stress and provide potential targets for genetic improvement. Future research should focus on validating these biomarkers in different barley cultivars and under field conditions to enhance crop resilience against stressors.

Identification and validation of autophagy‑related genes in hypertrophic cardiomyopathy.

Hypertrophic cardiomyopathy (HCM) is an autosomal dominant cardiac disorder characterized by ventricular hypertrophy resulting from the disordered arrangement of myocardial cells, which leads to impaired cardiac function or death. Autophagy (AT) is a biochemical process through which lysosomes degrade and recycle damaged or discarded intracellular components to protect cells against external environmental conditions, such as hypoxia and oxidative stress. AT is closely related to HCM, and thus, serves an important role in myocardial hypertrophy. However, the precise mechanism underlying the regulation of AT in cardiac hypertrophy remains elusive. The present study aimed to examine the role and mechanisms of AT-related genes (ARGs) in HCM through bioinformatics analysis and experimental validation and to identify potential targeted drugs for HCM. In this study, cardiac samples were obtained from healthy individuals and patients with HCM from the GEO database, and screened for differentially expressed ARGs to further investigate their potential interactions and functional pathways. These genes were subjected to functional enrichment analysis to identify potential crosstalk and involved pathways. Based on a protein-protein interaction network, EIF4EBP1, MCL1, PIK3R1, CCND1 and PPARG were identified as potential biomarkers for the diagnosis and treatment of HCM. Furthermore, 10 components with therapeutic potential for HCM were predicted based on the aforementioned hub genes. The results of bioinformatics analysis were validated using H9c2 cells stimulated with angiotensin II, which represented an in vitro model of cardiac hypertrophy. Overall, the present study demonstrated that the expression levels of ARGs were substantially altered in HCM. Therefore, these genes may be used as diagnostic biomarkers and therapeutic targets for HCM.

Network Pharmacology Studies on the Molecular Mechanism of Hashimoto's Thyroiditis Treated with Shutiao Qiji Decoction.

In recent years, the number of patients with Hashimoto's thyroiditis has been increasing, and traditional Chinese medicine ingredients and combinations have been applied to treat Hashimoto's thyroiditis to increase efficacy and reduce side effects during the treatment process. Shutiao Qiji Decoction is one of the Chinese traditional medicine prescriptions, which is commonly used to treat cancer, tumor, etc. It is also used for thyroid-related diseases in the clinic. Hashimoto's thyroiditis is an autoimmune disease. In this study, the mechanism of Shutiao Qiji Decoction in treating Hashimoto's thyroiditis was studied through network pharmacology and molecular docking verification. Each Chinese medicine ingredient of Shutiao Qiji Decoction was retrieved from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. The related genes of HT were searched from the UniProt and GeneCards databases. Meanwhile, we used Cytoscape to construct the protein-protein interaction (PPI) visual network analysis, and used the search tool to search the database of Interacting Genes (STRING) to build a PPI network. These key proteins were enriched and analyzed by molecular docking validation, Gene Ontology (GO), and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Hashimoto's thyroiditis disease model was established in SD rats, and SQD was administered by gavage after the successful establishment of the model. After 6 weeks of continuous administration of the drug by gavage, tissue samples were collected and the thyroid and spleen tissues were visualized by HE staining to verify the therapeutic effect. The results showed that there were 287 TCM active ingredients, 1920 HT-related disease targets, and 176 drug and disease targets in SQD. Through PPI analysis, GP analysis, and KEGG analysis of the common targets of drugs and diseases, we found their pathways of action to be mainly cancer action pathway, PI3K-AKT signaling pathway, and T-cell action pathway. The active ingredients of the drugs in SQD, malvidin, stigmasterol, porin-5-en-3bta-ol, and chrysanthemum stigmasterol, were docked with the related target proteins, MAPK, GSK3β, TSHR, and NOTCH molecules. The best binding energies obtained from docking were mairin with TSHR, stigmasterol with TSHR, poriferast-5-en-3beta-ol with MAPK, and chryseriol with GSK3β, with binding energies of -6.84 kcal/mol, -6.53 kcal/mol, -5.03 kcal/mol, and -5.05 kcal/mol, respectively. HE staining sections of rat thyroid and spleen tissues showed that SQD had a therapeutic effect on Hashimoto's thyroiditis and restored its immune function. It is verified by molecular docking results that Shutiao Qiji Decoction has a potential therapeutic effect on Hashimoto's thyroiditis in the MAPK/TSHR/NOTCH signal pathway, and that the main components, mairin, stigmasterol, poriferast-5-en-3beta-ol, and chryseriol play a role in it. SQD has been shown to have a good therapeutic effect on Hashimoto's thyroiditis.

Kaempferol improves depression-like behaviors through shifting microglia polarization and suppressing NLRP3 via tilting the balance of PPARγ and STAT1 signaling.

The pathogenesis of depression is largely influenced by dyshomeostasis of neuroinflammation regulated by microglia M1/M2 polarization, and NLRP3 inflammasome acts critical roles in shifting microglia polarization. Kaempferol (Kae), a major flavonoid in edible plants, possesses anti-inflammation and anti-depression capacity, but its underlying cellular and molecular mechanisms of antidepressive effect have not yet fully explored. In vivo studies with lipopolysaccharide (LPS)-induced depressive mice were carried out to evaluate antidepressant effect of Kae. In vitro, BV2 microglia cell line stimulated by LPS along with IFN-γ to detect pharmacological effects of Kae on microglia polarization and NLRP3. Based on two depression-related GEO datasets (GSE54570 and GSE54568) and the potential targets of Kae obtained from GeneCards database, enrichment analysis and protein-protein interaction (PPI) network construction reveal potential therapeutic targets of Kae for depression. Then the precise antidepressant mechanisms of Kae were verified by western blot and immunofluorescent staining in vivo and vitro. Our results showed that Kae significantly improves LPS-induced depressive behaviors and alleviates neuroinflammation in prefrontal cortex. Moreover, Kae obviously shifted microglia polarization to M2 phenotype, and also suppressed NLRP3 in prefrontal cortex and BV2. Enrichment analysis and PPI network construction suggested PPARγ and STAT1 signaling are related to regulation of NLRP3 in depression. Furtherly, Kae remarkably enhanced PPARγ activation and inhibited nuclear translocation of p-STAT1 in microglia of prefrontal cortex and BV2. Importantly, pre-incubation with PPARγ antagonist T0070907 or overexpression with CASTAT1 (constitutively active STAT1) both prevented pharmacologic effects of Kae on shifting microglia polarization and suppressing NLRP3 in BV2. Noteworthily, T0070907 significantly blocked the inhibitory effect of Kae on STAT1 while overexpression with CASTAT1 abolished the effect of Kae on PPARγ activation in BV2. Above results suggested that pharmacologic effects of Kae on microglia polarization and NLRP3 are dependent on the balance of counter-regulatory PPARγ and STAT1 signaling. Our results indicated that the shifting microglia polarization and suppression of NLRP3 via tilting the balance of PPARγ and STAT1 signaling may be the antidepressant mechanism of Kae, which provides a novel perspective for elucidating antidepressive effect of Kae.

Network Pharmacology Prediction and Molecular Docking-based Strategy to Explore the Potential Mechanism of Guiyi Tonglong Prescription in the Treatment of Benign Prostatic Hyperplasia

Background: Benign prostatic hyperplasia (BPH) is a common condition affecting the urinary tract. This study aimed at exploring the potential of Guiyi Tonglong (GYTL) prescription for the treatment of benign prostatic hyperplasia using network pharmacology and molecular docking technology. Methods: The main active ingredients in GYTL prescription were identified from the Traditional Chinese Medicine Systems Pharmacology and the Integrative Pharmacology-based Traditional Chinese Medicine (TCMIP) databases based on drug similarity of ≥ 30% and oral bioavailability of ≥ 0.18. Protein–protein interaction (PPI) networks, gene ontology, and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were used to study the interactions and pathway enrichment and establish ingredient-target-pathway networks. The structure of the active ingredient was docked to that of the potential protein target using the AutoDock molecular docking software. Results: A total of 86 active ingredients and 130 potential targets were screened from GYTL prescription, and a PPI network was constructed to identify the five most important core targets, namely SRC, TP53, STAT3, AKT1, and PIK3CA. Enrichment analysis revealed that GYTL prescription may play a role in the treatment of BPH through multiple signaling pathways, such as PI3K-Akt, EGFR, AGE-RAGE, and HIF-1. Molecular docking indicated a potential interaction between the active ingredients and targets. Conclusion: These results provide further information regarding the active ingredients and molecular mechanisms of GYTL prescription in treating BPH.

Cpd861 Targeting BCL2 to Alleviate Hepatic Fibrosis: Network Pharmacology, Mendelian Randomization, and Molecular Docking Mechanisms.

Compound 861 (Cpd861) is a traditional Chinese herbal compound for the treatment of hepatic fibrosis (HF). In the current investigation, Cpd861 has been demonstrated to have an underlying molecular mechanism and material foundation for the treatment of HF through network pharmacology, Mendelian randomization (MR), and molecular docking. Public databases were consulted for Cpd861 constituents and HF targets. Protein-protein interactions (PPIs) were established using STRING software, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. To elucidate the causal relationship between potential targets and liver injury, MR was used as a methodological tool. Finally, a molecular docking analysis was conducted between the active compound and the key target. We obtained 174 active ingredients and 113 intersecting genes. Through the PPI network, high-degree targets were identified, namely CTNNB1, ESR1, FOS, MDM2, CCND1, TP53, RELA, and BCL2. As shown by GO and KEGG pathway enrichment analyses, Cpd861 functions through xenobiotic stimulus and oxidative stress-related genes, as well as the PI3K-AKT and non-alcoholic fatty liver disease (NAFLD) signaling pathways. The results of MR showed that MDM2 and BCL2 had a causal relationship with liver injury. Molecular docking results showed that several active compounds in Cpd861 were stably bound to BCL2. This study made predictions regarding the efficacious components, as well as potential targets and pathways of Cpd861 in the therapy of HF. This will open up a new perspective for further investigation of the molecular mechanism of Cpd861 in the treatment of HF.

REMR: Identification of RNA Editing-mediated MiRNA Regulation in Cancers

Dysregulation of adenosine-to-inosine (A-to-I) RNA editing has been implicated in cancer progression. However, a comprehensive understanding of how A-to-I RNA editing is incorporated into miRNA regulation to modulate gene expression in cancer remains unclear, given the lack of effective identification methods. To this end, we introduced an information theory-based algorithm named REMR to systematically identify 12,006 A-to-I RNA editing-mediated miRNA regulatory triplets (RNA editing sites, miRNAs, and genes) across ten major cancer types based on multi-omics profiling data from The Cancer Genome Atlas (TCGA). Through analyses of functional enrichment, transcriptional regulatory networks, and protein-protein interaction (PPI) networks, we showed that RNA editing-mediated miRNA regulation potentially affects critical cancer-related functions, such as apoptosis, cell cycle, drug resistance, and immunity. Furthermore, triplets can serve as biomarkers for classifying cancer subtypes with distinct prognoses or drug responses, highlighting the clinical relevance of such regulation. In addition, an online resource (http://www.jianglab.cn/REMR/) was constructed to support the convenient retrieval of our findings. In summary, our study systematically dissected the RNA editing-mediated miRNA regulations, thereby providing a valuable resource for understanding the mechanism of RNA editing as an epitranscriptomic regulator in cancer.

The Therapeutic Mechanisms of Shenyan Oral Liquid I Against Chronic Kidney Disease Based on Network Pharmacology and Experimental Validation.

Chronic Kidney Disease (CKD) leads to structural and functional abnormalities of the kidneys and seriously jeopardizes human health. Shenyan Oral Liquid (SOLI), a Chinese medicinal preparation, has been reported to protect podocytes in patients with chronic kidney disease (CKD). The objective of this study is to investigate the mechanism of action of the Chinese medicinal preparation Senyan Oral Liquid (SOLI) in the treatment of CKD by protecting podocytes through network pharmacology technology and experimental validation. Compounds of SOLI and targets of CKD disease were collected and screened. The SOLI network of bioactive compounds targeting CKD and the protein-protein interaction (PPI) network were constructed using Cytoscape software and the STRING online database. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed using the R software Cluster Profiler package. Molecular docking was performed using Autodock software to verify the binding ability of bioactive compounds and target genes. Subsequently, the potential mechanism of SOLI on CKD predicted by network pharmacological analysis was experimentally studied and verified in an adriamycin-induced nephropathy rat model. A total of 81 targets of SOLI components acting on CKD were identified. The results of the PPI analysis clarified that five key target genes (TNF, AKT1, IL6, VEGFA, and TP53) play a critical role in the treatment of CKD by SOLI. The GO analysis and KEGG enrichment analysis indicated that SOLI acts through multiple pathways, including the PI3K/AKT signaling pathway against CKD. Molecular docking showed that the main compounds of SOLI and five key genes had strong binding affinity. In a rat model of adriamycin-induced nephropathy, SOLI significantly ameliorated disease symptoms and improved renal histopathology. Mechanistic studies showed that SOLI upregulated the expression level of Nephrin, inhibited the PI3K/AKT pathway in renal tissues, and ultimately suppressed the activation of autophagy-related proteins in CKD. SOLI exerted a renoprotective effect by regulating the Nephrin-PI3K/AKT autophagy signaling pathway, and these findings provide new ideas for the development of SOLI-based therapeutic approaches for CKD.

Integrative Bioinformatics and Experimental Analysis of Curcumin's Role in Regulating Ferroptosis to Combat Osteoporosis

This study utilized bioinformatics and data mining techniques to explore the molecular mechanism of curcumin in treating osteoporosis (OP) through the lens of ferroptosis, thereby identifying novel therapeutic targets. The datasets GSE35958, GSE35956, GSE7429, and GSE7158 were obtained from the Gene Expression Omnibus (GEO) database. GSE35958 and GSE35956 were employed as training sets for data integration, while GSE7429 and GSE7158 served as independent validation sets. Through retrieval from the FerrDb database, iron death-related genes (FRGs) were identified, and the differentially expressed genes (DEGs) were intersected to obtain differentially expressed FRGs (DEFRGs). Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted, followed by the construction of a Protein-Protein Interaction (PPI) network to identify Hub genes. The DGIdb database was utilized to predict candidate drugs associated with the Hub genes, and molecular docking and in vitro experiments confirmed that curcumin targets the Hub genes EGFR and PTGS2.Through in vitro testing of curcumin on BMSC cells, researchers examined cell vitality, iron death, osteogenic differentiation, mineralization, and the impact on EGFR and PTGS2 levels. The analysis yielded 2212 DEGs, 484 FRGs, with 45 FDEGs at the intersection. GO analysis revealed involvement in regulating mitochondrial proteins, amino acid transport across plasma membranes, and protein ubiquitination. KEGG pathway analysis indicated associations with iron death, FoxO signaling, mTOR signaling, cell aging, osteoclast differentiation, and GSH metabolism. Utilizing the MCC algorithm, five Hub genes were identified: MAPK3, PTGS2, TGFB1, CYBB, and EGFR, showing diagnostic potential for iron death. Curcumin displayed affinity for EGFR and PTGS2, mitigating iron-induced effects on BMSCs such as increased reactive oxygen species, Fe3+ levels, and decreased mitochondrial membrane potential. Furthermore, curcumin reversed these effects, suggesting EGFR and PTGS2 as targets for curcumin to inhibit BMSC ferroptosis and potentially delay osteoporosis development. Maintaining iron homeostasis and targeting BMSC ferroptosis could offer therapeutic avenues for iron overload-induced osteoporosis.

Banxia Xiexin Decoction Prevents HT22 Cells from High Glucose-induced Neurotoxicity via JNK/SIRT1/Foxo3a Signaling Pathway.

Type 2 diabetes-associated cognitive dysfunction (DCD) is a chronic complication of diabetes that has gained international attention. The medicinal compound Banxia Xiexin Decoction (BXXXD) from traditional Chinese medicine (TCM) has shown potential in improving insulin resistance, regulating endoplasmic reticulum stress (ERS), and inhibiting cell apoptosis through various pathways. However, the specific mechanism of action and medical value of BXXXD remain unclear. We utilized TCMSP databases to screen the chemical constituents of BXXXD and identified DCD disease targets through relevant databases. By using Stitch and String databases, we imported the data into Cytoscape 3.8.0 software to construct a protein-protein interaction (PPI) network and subsequently identified core targets through network topology analysis. The core targets were subjected to Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. The results were further validated through in vitro experiments. Network pharmacology analysis revealed the screening of 1490 DCD-related targets and 190 agents present in BXXXD. The topological analysis and enrichment analysis conducted using Cytoscape software identified 34 core targets. Additionally, GO and KEGG pathway analyses yielded 104 biological targets and 97 pathways, respectively. BXXXD exhibited its potential in treating DCD by controlling synaptic plasticity and conduction, suppressing apoptosis, reducing inflammation, and acting as an antioxidant. In a high glucose (HG) environment, the expression of JNK, Foxo3a, SIRT1, ATG7, Lamp2, and LC3 was downregulated. BXXXD intervention on HT22 cells potentially involved inhibiting excessive oxidative stress, promoting neuronal autophagy, and increasing the expression levels of JNK, SIRT1, Foxo3a, ATG7, Lamp2, and LC3. Furthermore, the neuroprotective effect of BXXXD was partially blocked by SP600125, while quercetin enhanced the favorable role of BXXXD in the HG environment. BXXXD exerts its effects on DCD through multiple components, targets, levels, and pathways. It modulates the JNK/SIRT1/Foxo3a signaling pathway to mitigate autophagy inhibition and apoptotic damage in HT22 cells induced by HG. These findings provide valuable perspectives and concepts for future clinical trials and fundamental research.

Network Pharmacology, Molecular Docking and Experimental Verification Revealing the Mechanism of Fule Cream against Childhood Atopic Dermatitis.

The Fule Cream (FLC) is an herbal formula widely used for the treatment of pediatric atopic dermatitis (AD), however, the main active components and functional mechanisms of FLC remain unclear. This study performed an initial exploration of the potential acting mechanisms of FLC in childhood AD treatment through analyses of an AD mouse model using network pharmacology, molecular docking technology, and RNA-seq analysis. The main bioactive ingredients and potential targets of FLC were collected from the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP) and SwissTargetPrediction databases. An herb-compound-target network was built using Cytoscape 3.7.2. The disease targets of pediatric AD were searched in the DisGeNET, Therapeutic Target Database (TTD), OMIM, DrugBank and GeneCards databases. The overlapping targets between the active compounds and the disease were imported into the STRING database for the construction of the protein-protein interaction (PPI) network. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of the intersection targets were performed, and molecular docking verification of the core compounds and targets was then performed using AutoDock Vina 1.1.2. The AD mouse model for experimental verification was induced by MC903. The herb-compound-target network included 415 nodes and 1990 edges. Quercetin, luteolin, beta-sitosterol, wogonin, ursolic acid, apigenin, stigmasterol, kaempferol, sitogluside and myricetin were key nodes. The targets with higher degree values were IL-4, IL-10, IL-1α, IL-1β, TNFα, CXCL8, CCL2, CXCL10, CSF2, and IL-6. GO enrichment and KEGG analyses illustrated that important biological functions involved response to extracellular stimulus, regulation of cell adhesion and migration, inflammatory response, cellular response to cytokine stimulus, and cytokine receptor binding. The signaling pathways in the FLC treatment of pediatric AD mainly involve the PI3K-Akt signaling pathway, cytokine‒cytokine receptor interaction, chemokine signaling pathway, TNF signaling pathway, and NF-κB signaling pathway. The binding energy scores of the compounds and targets indicate a good binding activity. Luteolin, quercetin, and kaempferol showed a strong binding activity with TNFα and IL-4. This study illustrates the main bioactive components and potential mechanisms of FLC in the treatment of childhood AD, and provides a basis and reference for subsequent exploration.

The inhibition of rutin on Src kinase blocks high glucose-induced EGFR/ERK transactivation in diabetic nephropathy by integrative approach of network pharmacology and experimental verification

BackgroundAlthough clinical strategies for diabetic nephropathy (DN) therapy include stringent blood pressure control through blockade of the renin-angiotensin system and management of hyperglycemia, the condition is still observed to progress relentlessly. PurposeTo elucidate the protective effects of rutin on podocytes in db/db mice with integrative approach of network pharmacology and experimental verification. MethodsThe study employs network pharmacology to identify common targets between rutin and DN, constructs a potential protein-protein interaction (PPI) network, and conducts Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Molecular docking is utilized to evaluate the interaction between rutin and protein targets. Additionally, experimental validation is performed using db/db mice and human podocyte cell models. ResultsRutin has been found to have a significant renoprotective effect, reducing blood glucose, proteinuria, and improving renal function in db/db mice. Rutin's inhibition of Src kinase reduces the phosphorylation levels of EGFR and ERK, which may mitigate podocyte injury. Additionally, rutin exhibits antioxidant properties, capable of lowering the levels of reactive oxygen species (ROS) in kidney tissue and increasing the activity of antioxidant enzymes like superoxide dismutase (SOD). These effects help protect podocytes from oxidative stress, further supporting the potential application of rutin in the treatment of DN. ConclusionsThe inhibition of rutin on Src kinase blocks high glucose-induced EGFR/ERK transactivation and protects podocyte injury in DN, indicating it might serve as a promising therapeutic agent for podocyte-targeted therapies.

Exploration of the key active ingredients and mechanisms of Sparganii Rhizoma-Curcumae Rhizoma compatible formulation against human colorectal cancer through network pharmacology and in vitro experiments

IntroductionSparganii Rhizoma-Curcumae Rhizoma (SR-CR) formulation may offer an effective treatment for human colorectal cancer (CRC). However, the active ingredients and underlying mechanisms of this herbal formulation remain unclear. MethodsThis study integrates network pharmacology, molecular docking and experimental verification to identify key active ingredients and elucidate the mechanisms of SR-CR in CRC treatment. ResultsTwenty-three active components of SR-CR were identified using the TCMSP, UniProt and Gene Cards databases. These components were associated with 178 targets, of which 118 are directly related to CRC. Protein-protein interaction (PPI) network analysis identified protein kinase B (AKT) 1, epidermal growth factor receptor (EGFR), SRC, Bcl2 and CASP3 as core anti-CRC targets. Gene Ontology (GO) and KEGG pathway analyses were performed on these 178 intersecting targets, and the results showed that these targets are involved in EGFR tyrosine kinase inhibitor resistance and AGE-RAGE signaling pathway in diabetic complications. At the same time, five compounds, including bisdemethoxycurcumin, formononetin, β-sitosterol, stigmasterol and hederagenin, were selected based on the target number of effective components and tested for cytotoxicity against human CRC cell lines HT-29, HCT-8 and HCT-116 in vitro. The results showed that bisdemethoxycurcumin exhibited significant anti-proliferative activity against HCT-116 cells. Molecular docking results indicated that bisdemethoxycurcumin effectively binds with AKT, EGFR, Bcl-2 and CASP3. Further pharmacological experiments demonstrated that bisdemethoxycurcumin inhibits HCT-116 cell proliferation and migration via inhibiting EGFR-AKT pathway, and induces apoptosis by up-regulating Bcl-2 expression. DiscussionBased on our study, inhibiting the EGFR-AKT pathway and upregulating Bcl2 may be one of the mechanisms by which SR-CR inhibits the growth of CRC. The main active ingredients of SR-CR include bisdemethoxycurcumin, formononetin, β-sitosterol, stigmasterol and hederagenin, which may exert anti-colon cancer activity by targeting the regulation of AKT, EGFR, Bcl-2 and CASP3. However, we need more in vitro and in vivo evidence to confirm this conclusion. This study lays the foundation for further research on the pharmacological mechanism of SR-CR in the treatment of CRC.

Unifying Theory and Experiments: Multi-Target Pharmacology of Dajihan Pill Against Hyperlipidemia

Background: The increasing incidence of hyperlipidemia (HLP) is attributed to the imbalance in redox homeostasis, aberrant lipid metabolism, and the excessive intake of empty calories. Dajihan Pill (DJHP) is a Traditional Chinese Medicine (TCM) formula composed of Zingiberis Rhizoma (ZR), Piperis Longi Fructus (PLF), Alpiniae Officinarum Rhizome (AOR), and Cinnamomi Cortex (CC) in a ratio of 3:2:3:2. It exhibits a significant preventive effect on HLP. Certainly, the active components and the precise mechanism of action are not fully understood. Therefore, this study aims to elucidate the preventive and ameliorative mechanisms of DJHP against HLP by integrating network pharmacology, molecular docking, and experimental validation. Methods: Based on the pharmacological method, active ingredients in DJHP and targets were extracted from Traditional Chinese Medicine System Pharmacology (TCMSP) and UniProt. Then core compounds and targets were obtained by constructing “compounds-targets-disease” and proteinprotein interaction (PPI) network. Gene Ontology (GO) function analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) were employed to elucidate further the associated action mechanism. The molecular binding mechanisms between the core ingredients and targets were elucidated through molecular docking. Additionally, the antioxidant capacities of DJHP extracts were investigated by assessing their DPPH, hydroxyl, and ABTS radical scavenging activities. Results: A total of 45 active compounds and 258 targets were identified in DJHP. Network analysis indicated that quercetin, beta-sitosterol, kaempferol, and oleic acid might serve as core bioactive compounds. Seven core targets, including AKT1, INS, and TNF, were identified as potential preventive targets. GO analysis suggested the improvement of HLP by DJHP may be related to the lipid metabolic process, high-density lipoprotein particle, triglyceride binding, and inflammatory response. The KEGG analysis indicated TNF, HIF-1, and AMPK signaling pathways were involved. The observations of active compounds binding with core targets indicated an excellent combination. Additionally, antioxidant results showed that DJHP exhibited significant DPPH, hydroxyl, and ABTS radical scavenging activities. Conclusion: Theoretical and experimental investigations indicate that DJHP can effectively modulate various signaling pathways and enhance the redox system, thus mitigating HLP. Our work provided a basis for the pharmacological study of DJHP in preventing HLP and further research.

Deciphering the Underlying Mechanisms of Sanleng-Ezhu for the Treatment of Idiopathic Pulmonary Fibrosis Based on Network Pharmacology and Single-cell RNA Sequencing Data.

To decipher the underlying mechanisms of Sanleng-Ezhu for the treatment of idiopathic pulmonary fibrosis based on network pharmacology and single-cell RNA sequencing data. Idiopathic Pulmonary Fibrosis (IPF) is the most common type of interstitial lung disease. Although the combination of herbs Sanleng (SL) and Ezhu (EZ) has shown reliable efficacy in the management of IPF, its underlying mechanisms remain unknown. Based on LC-MS/MS analysis and the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) database, we identified the bioactive components of SL-EZ. After obtaining the IPF-related dataset GSE53845 from the Gene Expression Omnibus (GEO) database, we performed the differential expression analysis and the weighted gene co-expression network analysis (WGCNA), respectively. We obtained lowly and highly expressed IPF subtype gene sets by comparing Differentially Expressed Genes (DEGs) with the most significantly negatively and positively related IPF modules in WGCNA. Subsequently, we performed Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses on IPF subtype gene sets. The low- and highexpression MCODE subgroup feature genes were identified by the MCODE plug-in and were adopted for Disease Ontology (DO), GO, and KEGG enrichment analyses. Next, we performed the immune cell infiltration analysis of the MCODE subgroup feature genes. Single-cell RNA sequencing analysis demonstrated the cell types which expressed different MCODE subgroup feature genes. Molecular docking and animal experiments validated the effectiveness of SL-EZ in delaying the progression of pulmonary fibrosis. We obtained 5 bioactive components of SL-EZ as well as their corresponding 66 candidate targets. After normalizing the samples of the GSE53845 dataset from the GEO database source, we obtained 1907 DEGs of IPF. Next, we performed a WGCNA analysis on the dataset and got 11 modules. Notably, we obtained 2 IPF subgroups by contrasting the most significantly up- and down-regulated modular genes in IPF with DEGs, respectively. The different IPF subgroups were compared with drugcandidate targets to obtain direct targets of action. After constructing the protein interaction networks between IPF subgroup genes and drug candidate targets, we applied the MCODE plug-in to filter the highest-scoring MCODE components. DO, GO, and KEGG enrichment analyses were applied to drug targets, IPF subgroup genes, and MCODE component signature genes. In addition, we downloaded the single-cell dataset GSE157376 from the GEO database. By performing quality control and dimensionality reduction, we clustered the scattered primary sample cells into 11 clusters and annotated them into 2 cell subtypes. Drug sensitivity analysis suggested that SL-EZ acts on different cell subtypes in IPF subgroups. Molecular docking revealed the mode of interaction between targets and their corresponding components. Animal experiments confirmed the efficacy of SL-EZ. We found SL-EZ acted on epithelial cells mainly through the calcium signaling pathway in the lowly-expressed IPF subtype, while in the highly-expressed IPF subtype, SL-EZ acted on smooth muscle cells mainly through the viral infection, apoptosis, and p53 signaling pathway.

Molecular mechanisms and potential targets of lycopene for alleviating renal ischemia-reperfusion injury revealed by network pharmacology and animal experiments

ObjectiveRenal IRI is one of the leading causes of AKI. How to effectively mitigate renal IRI is important for the recovery of renal function. The regulatory mechanism of lycopene, a natural antioxidant, in renal IRI is currently unknown. Therefore, we utilized network pharmacology and animal experiments to explore the possible mechanisms and potential targets of lycopene for alleviating renal IRI. MethodsWe obtained lycopene-regulated genes and renal IRI-related genes from the CTD database and GeneCards database, respectively. Subsequently, the two were intersected and the intersecting genes we defined as lycopene-regulated genes in renal IRI. Next, we explored their potential biological functions and mechanisms through enrichment analysis. Meanwhile, we constructed a rat renal IRI model and validated the protective effects of lycopene and related mechanisms. To further explore the Hub genes regulated by lycopene, we constructed a PPI protein interactions network and characterized the Hub genes using Cytoscape software. We also verified the expression of Hub genes using animal experiments and molecular docking techniques. Finally, we constructed TF-Hub gene and miRNA-Hub gene regulatory networks. ResultsWe obtained a total of 255 lycopene-regulated genes and 327 renal IRI-related genes. The enrichment analysis revealed that they were closely related to the regulation of oxidative stress as well as the regulation of inflammatory factors. At the same time, the MAPK signaling pathway was significantly enriched. Next, we found in animal experiments that lycopene significantly alleviated the level of oxidative stress and inflammation during renal IRI, and had a protective effect on kidney damage. Also, we found that this protective effect may be achieved by inhibiting the MAPK signaling pathway. Next, we identified a total of five Hub genes using Cytoscape software: TNF, AKT1, MAPK3, IL6 and CASP3. Both animal experiments and molecular docking techniques demonstrated that lycopene can effectively regulate the expression of Hub genes. Finally, our constructed TF-Hub gene and miRNA-Hub gene regulatory network provide a theoretical basis for further regulation of Hub genes in follow-up. ConclusionsThis study suggests that lycopene is a promising option in mitigating renal IRI. Lycopene may exert protective effects by inhibiting the MAPK signaling pathway.