STRING Database Research Articles

Identifying the Genetic Associations Between Diabetes Mellitus and the Risk of Vitiligo.

While increasing observational studies have suggested an association between diabetes mellitus (DM) and vitiligo, the causal relationship and possible mechanism remain unclear. Publicly accessible genome-wide association study (GWAS) was utilized to conduct a bidirectional two-sample Mendelian randomization (MR) analysis. GWAS data for diabetes and vitiligo were obtained from the UK Biobank Consortium (20203 cases and 388756 controls) and the current GWAS data with largest cases (GCST004785, 4680 cases and 39586 controls) for preliminary analysis, respectively. Inverse variance weighting (IVW) was used as the main analysis method. Several sensitivity analyses were utilized to test the pleiotropy or heterogeneity. To explore the possible mechanism of gene-generating effects represented by the final instrumental variables in the analysis, enrichment analysis was conducted using the DAVID and STRING database. IVW method showed a significant genetic causal association between DM and vitiligo (OR = 1.20, 95% CI: 1.08-1.33, PIVW = 0.0009). Diabetes subtype analysis showed that T2D (type 2 diabetes) were associated with an increased risk of vitiligo (OR = 1.13, 95% CI: 1.00-1.27, PIVW = 0.0432). Sensitivity analysis further confirmed the robustness of the results. The enrichment analysis revealed that the genetic inducing effects of diabetes mellitus on vitiligo were primarily about pancreatic secretion and protein digestion and absorption pathway. Our findings provide genetic evidence that there is a notable association between T2D and an elevated risk of vitiligo in European populations. This result may explain why the co-presentation of T2D and vitiligo is often seen in observational studies, and emphasize the significance of vigilant monitoring and clinical evaluations for vitiligo in individuals diagnosed with T2D. The aberrant glucose and lipid metabolism and the primary nutrient absorption disorder of vitiligo brought on by diabetes may be the potential mechanisms behind this association.

Protein Modifications During Early Embryo Development.

Infertility is a global reproductive health burden. Assisted reproductive technologies (ARTs) have been widely used to help patients become pregnant. Few embryos develop to the blastocyst stage with ARTs, leading to relatively low live birth rates. Protein modifications play crucial roles in nearly every aspect of cell biology, including reproductive processes. The aim of this study was to explore the characteristics of protein modifications during embryonic development. Proteomic data from humans and mice were acquired from the integrated proteome resources (iProX) of ProteomeXchange (PXD024267) and a tandem mass tag (TMT)-mass spectrometry dataset. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were applied for functional annotation. Protein-protein interactions (PPIs) of the modification-related genes were revealed by the STRING database. Modified proteins during mouse embryogenesis were visualized through heatmaps of hierarchically clustering using k-means. We identified modification-related proteins in human embryo development and characterized them through heatmaps, GO analysis, KEGG analysis, and PPI network analysis. We found that the 4-cell stage to the 8-cell stage might be the demarcation period for modification-related protein expression patterns during embryo development. Using quantitative mass spectrometry, we elucidated the methylation, acetylation, and ubiquitination events that occur during mouse embryogenesis to validate our findings in human embryonic development to some extent. The results of our study suggest that the posttranslational modifications (PTMs) of human preimplantation embryos might exhibit the same trends as those in mice to exert synergistic and fine-tuned regulatory effects during embryonic development.

The Mechanism by Which Cyperus rotundus Ameliorates Osteoarthritis: A Work Based on Network Pharmacology.

Cyperus rotundus (CR) is widely used in traditional Chinese medicine to prevent and treat a variety of diseases. However, its functions and mechanism of action in osteoarthritis (OA) has not been elucidated. Here, a comprehensive strategy combining network pharmacology, molecular docking, molecular dynamics simulation and in vitro experiments was used to address this issue. The bioactive ingredients of CR were screened in TCMSP database, and the potential targets of these ingredients were obtained through Swiss Target Prediction database. Genes in OA pathogenesis were collected through GeneCards, OMIM and DisGeNET databases. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed using DAVID database. STRING database and Cytoscape 3.10 software were used to construct "component-target-pathway" network, and predict the core targets affected by CR. The binding affinity between bioactive components and the core targets was evaluated by molecular docking and molecular dynamics simulation. The therapeutic activity of kaempferol on chondrocytes in inflammatory conditions was verified by in vitro experiments. Fifteen CR bioactive ingredients were obtained, targeting 192 OA-related genes. A series of biological processes, cell components, molecular functions and pathways were predicted to be modulated by CR components. The core targets of CR in OA treatment were AKT serine/threonine kinase 1 (AKT1), interleukin 1 beta (IL1B), SRC proto-oncogene, non-receptor tyrosine kinase (SRC), BCL2 apoptosis regulator (BCL2), signal transducer and activator of transcription 3 (STAT3), epidermal growth factor receptor (EGFR), hypoxia-inducible factor 1 subunit alpha (HIF1A), matrix metallopeptidase 9 (MMP9), estrogen receptor 1 (ESR1) and PPARG orthologs from vertebrates (PPARG), and the main bioactive ingredients of CR showed good binding affinity with these targets. In addition, kaempferol, one of the CR bioactive components, weakens the effects of IL-1β on the viability, apoptosis and inflammation of chondrocytes. Theoretically, CR has great potential to ameliorate the symptoms and progression of OA, via multiple components, multiple targets, and multiple downstream pathways.

Screening lncRNAs essential for cardiomyocyte proliferation by integrative profiling of lncRNAs and mRNAs associated with heart development

BackgroundThe proliferation potential of mammalian cardiomyocytes declines markedly shortly after birth. Both long non-coding RNAs (lncRNAs) and mRNAs demonstrate altered expression patterns during cardiac development. However, the role of lncRNAs in the cell cycle arrest of cardiomyocytes remains inadequately understood. MethodThe expression pattern of lncRNAs and mRNAs was analyzed in mouse hearts exhibiting varying regenerative potentials on postnatal days (P) 1, 7, and 28. Weighted correlation network analysis (WGCNA) was employed to elucidate the co-expression relationship between lncRNAs and mRNAs. Protein-protein interaction (PPI) network was built using the STRING database, and hub lncRNAs were identified by CytoHubba. Molecular Complex Detection (MCODE) was used to screen core modules of the PPI network in Cytoscape. Upstream lncRNAs and miRNAs which may regulate mRNAs were predicted using miRTarBase and AnnoLnc2, respectively. Myocardial infarction (MI) was induced by ligation of the left anterior descending coronary artery. ResultsCompared with the P1 heart, 618 mRNAs and 414 lncRNAs displayed.transcriptional changes in the P7 heart, while 2358 mRNAs and 1290 lncRNAs showed from P7 to P28. Gene Ontology (GO) analysis revealed that module 1 in the both comparisons was enriched in the mitotic cell cycle process. 2810408I11Rik and 2010110K18Rik were identified as hub lncRNAs and their effects on the proliferation of cardiomyocytes were verified in vitro. Additionally, four lncRNA-miRNA-mRNA regulatory axes were predicted to explain the mechanism by which 2810408I11Rik and 2010110K18Rik regulate cardiomyocyte proliferation. Notably, the overexpression of 2810408I11Rik enhances cardiomyocyte proliferation and heart regeneration in the adult heart following MI. ConclusionThis study systematically analyzed the landscape of lncRNAs and mRNAs at P1, P7, and P28. These findings may enhance our understanding of the framework for heart development and could have significant implications for heart regeneration.

Role of CENPL, DARS2, and PAICS in determining the prognosis of patients with lung adenocarcinoma.

Non-small cell lung cancer (NSCLC) accounts for about 85% of lung cancers, and is the leading cause of tumor-related death. Lung adenocarcinoma (LUAD) is the most prevalent subtype of NSCLC. Although significant progress of LUAD treatment has been made under multimodal strategies, the prognosis of advanced LUAD is still poor due to recurrence and metastasis. There is still a lack of reliable markers to evaluate the LUAD prognosis. This study aims to explore novel biomarkers and construct a prognostic model to predict the prognosis of LUAD patients. The Genomic Data Commons-The Cancer Genome Atlas-Lung Adenocarcinoma (GDC-TCGA-LUAD) dataset was downloaded from the University of California, Santa Cruz (UCSC) Xena browser. The GSE72094 and GSE13213 datasets and corresponding clinical information were downloaded from the Gene Expression Omnibus (GEO) database. By analyzing these datasets using DESeq2 R package and Limma R package, differentially expressed genes (DEGs) were found. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to analyze possible enrichment pathways. A protein-protein interaction (PPI) network was constructed to explore possible relationship among DEGs by using the STRING database. A survival analysis was performed to identify reliable prognostic genes using the Kaplan-Meier method. A multi-omics analysis was performed using the Gene Set Cancer Analysis (GSCA). The Tumor Immune Estimation Score (TIMER) database was used to analyze the association between prognostic genes and immune infiltration. A Spearman correlation analysis was conducted to examine the correlation between prognostic genes and drug sensitivity. A multivariate Cox regression was used to identify independent prognostic factors. Next, a nomogram was constructed using the rms R package. Finally, the expressions of aspartyl-tRNA synthetase 2 (DARS2) and phosphoribosyl aminoimidazole carboxylase (PAICS) were detected using immunohistochemistry (IHC). We screened out 30 DEGs prior to functional enrichment and PPI network analysis revealing potential enrichment pathways and interactions of these DEGs. Then survival analysis revealed the CENPL, DARS2, and PAICS expression was negatively correlated with LUAD prognosis. Additionally, multi-omics analysis showed CENPL, DARS2, and PAICS expressions were significantly higher in LUAD tissues than normal tissues. CENPL, DARS2, and PAICS were all up-regulated in late stage and M1 stage. Correlation analysis indicated CENPL, DARS2, and PAICS may not be associated with activation or suppression of immune cells. Drug sensitivity analysis revealed many potentially effective drugs and small molecule compounds. Moreover, we successfully constructed a robust and stable nomogram by combining the DARS2 and PAICS expression with other clinicopathological variables. Finally, IHC results showed DARS2 and PAICS were significantly up-regulated in LUAD. The CENPL, DARS2, and PAICS expression was negatively correlated with LUAD prognosis. A prognostic model, which integrated DARS2, PAICS, and other clinicopathological variables, was able to effectively predict LUAD patients prognosis.

Transcriptomic Profiling of Primary Microglia: Effects of miR-19a-3p and miR-19b-3p on Microglia Activation.

Neuropathic pain resulting from spinal cord injury (SCI) is a significant secondary health issue affecting around 60% of individuals with SCI. After SCI, activation of microglia, the immune cells within the central nervous system, leads to neuroinflammation by producing pro-inflammatory cytokines and affects neuropathic pain. This interplay between inflammation and pain contributes to the persistent and intense pain experienced by many individuals with SCI. MicroRNAs (miRs) have been critical regulators of neuroinflammation. Previous research in our laboratory has revealed upregulation levels of circulating miR-19a and miR-19b in individuals with SCI with neuropathic pain compared to those without pain. In this study, we treated primary microglial cultures from mice with miR-19a and miR-19b for 24 h and conducted RNA sequencing analysis. Our results showed that miR-19a and miR-19b up- and downregulate different genes according to the volcano plots and the heatmaps. miR-19a and miR-19b regulate inflammation through distinct signaling pathways. The results showed that miR-19a promotes inflammation via toll-like receptor signaling, TNF signaling, and cytokine-cytokine receptor interactions, while miR-19b increases inflammatory responses through the PI3K-Akt signaling pathway, focal adhesion, and extracellular matrix receptor interactions. The protein-protein interaction (PPI) networks used the STRING database to identify transcription factors associated with genes up- or downregulated by miR-19a and miR-19b. Key transcription factors, such as STAT1, STAT2, and KLF4 for miR-19a, and Nr4a1, Nr4a2, and Nr4a3 for miR-19b, were identified and revealed their roles in regulating neuroinflammation. This study demonstrates that miR-19a and miR-19b modulate diverse patterns of gene expression, regulate inflammation, and induce inflammatory responses in microglia.

Bioinformatics analysis of the antigenic epitopes of L7/L12 protein in the B- and T-cells active against Brucella melitensis.

The objective is to analyse the physicochemical properties, spatial structure and protein-protein interactions (PPIs) of L7/L12 protein using bioinformatics methods and predict their B- and T-cell epitopes to lay a theoretical foundation for developing a novel multiepitope vaccine (MEV). The National Center for Biotechnology Information (NCBI) database was searched for the amino acid sequences of L7/L12 from Brucella melitensis. In addition, the online softwares, ProtParam and ProtScale, were used to predict the physicochemical properties: NetPhos3.1 and CD-search to predict the phosphorylation sites and conserved domains; SOMPA and SWISS-MODEL to predict the secondary and tertiary structures; the STRING database to analyse the PPIs; and the IEDB, ABCpred, SVMTrip and SYFPEITHI databases to predict the B- and T-cell epitopes. L7/L12 was docked to Toll-like receptor 4 (TLR4), B-cell receptor (BCR), Major histocompatibility complex I-T cell receptor (MHC I-TCR) and MHC II-TCR complexes, respectively, and the binding ability of L7/L12 to the targeted receptors was tested. L7/L12, consisting of 124 amino acids, was determined to be a stable, intracellular, hydrophilic protein containing 6 phosphorylation sites and ribosomal protein-related conserved domains. α-helices accounted for 70.16 %, β-turns for 2.42 %, extended strands for 8.87 % and irregular coils for 18.55 % of the secondary structure. The PPIs indicated that L7/L12 was involved in the constitution of ribosomes and regulating the accuracy of the translation process. Three B-cells, two cytotoxic T lymphocytes and three helper T lymphocyte epitopes were finally screened by comparing multiple databases. L7/L12 binds to TLR4, BCR, MHC I-TCR and MHC II-TCR complexes and forms stable hydrogen bonds, respectively. L7/L12, which governs the translation curate of proteins, possesses several potentially advantageous epitopes, laying a theoretical foundation for designing MEVs.

Identification of genes contributing to attenuation of rat model of galactose-induced cataract by pyruvate.

Cataracts are a disease that reduces vision due to opacity formation of the lens. Diabetic cataracts occur at young age and progress relatively quickly, so the development of effective treatment has been awaited. Several studies have shown that pyruvate inhibits oxidative stress and glycation of lens proteins, which contribute to onset of diabetic cataracts. However, detailed molecular mechanisms have not been revealed. In this study, we attempted to reduce galactose-induced opacity by pyruvate with rat ex vivo model. Rat lenses were extracted and cultured in galactose-containing medium to induce lens opacity. After opacity had developed, continued culturing with pyruvate in the medium resulted in a reduction of lens opacity. Subsequently, we conducted microarray analysis to investigate the genes that contribute to the therapeutic effect. We performed quantitative expression measurements using RT-qPCR for extracted genes that were upregulated in cataract-induced lenses and downregulated in pyruvate-treated lenses, resulting in the identification of 34 candidate genes. Functional analysis using the STRING database suggests that metallothionein-related factors (Mt1a, Mt1m, and Mt2A) and epithelial-mesenchymal transition-related factors (Acta2, Anxa1, Cd81, Mki67, Timp1, and Tyms) contribute to the therapeutic effect of cataracts.

Potential molecular mechanisms of Danggui-Shaoyao-San in the treatment of melasma based on network pharmacology with molecular docking

Although Danggui-Shaoyao-San (DSS) is frequently used in China to treat melasma, its underlying mechanism still needs to be better understood. Our aim is to determine the mechanism behind DSS in treating melasma through network pharmacology (NP). The DSS active compounds alongside corresponding target genes are identified by accessing the TCMSP database and SwissTargetPrediction. Melasma-associated targets are retrieved from the GeneCards, DisGeNet, Durgbanks, OMIM, and TTD databases. Next, we build a component-target association network via Cytoscape software while generating a protein-protein interaction network utilizing the STRING database. Subsequently, both core target genes and active compounds are determined. Through the DAVID database and Bioinformatics tools, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses are conducted. Lastly, the CB-Dock2 server is deployed to conduct molecular docking (MOD). The results manifest that alisol B, cerevisterol, and Wallichilide, among others, are active compounds in DSS, while PTGS2, ESR1, and ESR2 are core target genes. Both GO and KEGG analyses showcase that the potential core drug components modulate pathways in cancer, chemical carcinogenesis-receptor activation, calcium, relaxin, and estrogen signaling by exerting their effects on biological processes. These processes include negative gene expression regulation as well as positive regulation of both cytosolic calcium ion concentration and transcription from the RNA polymerase II promoter, thereby playing an anti-melasma pharmacological role. The MOD displays that core target genes have good binding activity with the active compounds. To conclude, NP demonstrates that DSS can serve as an innovative medication for treating melasma.

Elucidating gastric cancer mechanisms and therapeutic potential of Adociaquinone A targeting EGFR: A genomic analysis and Computer Aided Drug Design (CADD) approach.

Gastric cancer predominantly adenocarcinoma, accounts for over 85% of gastric cancer diagnoses. Current therapeutic options are limited, necessitating the discovery of novel drug targets and effective treatments. The Affymetrix gene expression microarray dataset (GSE64951) was retrieved from NCBI-GEO data normalization and DEGs identification was done by using R-Bioconductor package. Gene Ontology (GO) analysis of DEGs was performed using DAVID. The protein-protein interaction network was constructed by STRING database plugin in Cytoscape. Subclusters/modules of important interacting genes in main network were extracted by using MCODE. The hub genes from in the network were identified by using Cytohubba. The miRNet tool built a hub gene/mRNA-miRNA network and Kaplan-Meier-Plotter conducted survival analysis. AutoDock Vina and GROMACS MD simulations were used for docking and stability analysis of marine compounds against the 5CNN protein. Total 734 DEGs (507 up-regulated and 228 down-regulated) were identified. Differentially expressed genes (DEGs) were enriched in processes like cell-cell adhesion and ATP binding. Eight hub genes (EGFR, HSPA90AA1, MAPK1, HSPA4, PPP2CA, CDKN2A, CDC20, and ATM) were selected for further analysis. A total of 23 miRNAs associated with hub genes were identified, with 12 of them targeting PPP2CA. EGFR displayed the highest expression and hazard rate in survival analyses. The kinase domain of EGFR (PDBID: 5CNN) was chosen as the drug target. Adociaquinone A from Petrosia alfiani, docked with 5CNN, showed the lowest binding energy with stable interactions across a 50 ns MD simulation, highlighting its potential as a lead molecule against EGFR. This study has identified crucial DEGs and hub genes in gastric cancer, proposing novel therapeutic targets. Specifically, Adociaquinone A demonstrates promising potential as a bioactive drug against EGFR in gastric cancer, warranting further investigation. The predicted miRNA against the hub gene/proteins can also be used as potential therapeutic targets.

Decoding the mechanism of Qingjie formula in the prevention of COVID-19 based on network pharmacology and molecular docking

Traditional Chinese medicine (TCM) has played a positive role in preventing and controlling the coronavirus disease 2019 (COVID-19) epidemic. Qingjie formula (QJF) developed to prevent COVID-19 is widely used in Wenzhou, Zhejiang province, China. However, the biological active ingredients of QJF and their specific mechanisms for preventing COVID-19 remain unclear. The study focused on exploring the pharmacological mechanism of QJF for the prevention of COVID-19 based on network pharmacology and molecular docking. The active ingredients of QJF were screened by TCMSP database. Databases such as Genecards and Swiss Target Prediction predicted potential targets of QJF against COVID-19. The “drug-active ingredient-potential target” network was constructed by Cytoscape software. We used STRING database to construct the protein-protein interaction (PPI) network. Enrichment of biological functions and signaling pathways were analyzed by using the DAVID database and R language. Then AutoDock Vina and Python software were used for molecular docking of hub targets and active ingredients. 147 active ingredients interacted with 316 potential targets of COVID-19. A PPI network consisting of 30 hub genes was constructed, and the top 10 hub genes were ALB, AKT1, TP53, TNF, IL6, VEGFA, IL1B, CASP3, JUN and STAT3. The results of GO analysis showed that these targets were mainly enriched in cell responses to oxidative stress, chemical stress, and other functions. KEGG analysis revealed that viral protein interactions with cytokines (e.g., human cytomegalovirus infection), endocrine resistance pathways (e.g., AGE-RAGE signaling pathway), PI3K-Akt signaling pathway, and lipid and atherosclerosis signaling pathway were the major signaling pathways. Moreover, the core active ingredients of QJF had good binding affinity with hub genes by molecular docking. QJF plays an important role in the prevention of COVID-19 by regulating host immune inflammatory response and oxidative stress response, inhibiting virus, improving immune function, regulating the hypoxia-cytokine storm, and inhibiting cell migration.

Network Pharmacology and Experimental Verification: SanQi-DanShen Treats Coronary Heart Disease by Inhibiting the PI3K/AKT Signaling Pathway.

To employee network pharmacology to predict the components and pathways of SanQi-DanShen (SQDS) in treating coronary heart disease, followed by in vitro experiments to validate the molecular mechanism of SQDS in treating coronary heart disease. We sourced the active ingredients and targets of Panax notoginseng and Danshen from the Traditional Chinese Medicine Systems Pharmacology database. Coronary heart disease related genes were retrieved from the OMIM, Genecards, and Therapeutic Target databases. Using Cytoscape 3.7.2 software, we constructed a network diagram illustrating the components and targets of SQDS. The associated targets were then imported into the STRING database to build a protein-protein interaction network. The Metascape database and WeChat software were utilized for Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses. Lastly, we performed molecular docking between the key components and related targets using AutoDock Vina. To validate the potential mechanism of SQDS in treating coronary heart disease, we established an acute coronary heart disease rat model via tail vein injection of pituitrin. Network pharmacology analysis revealed that 65 active ingredients and 167 targets of SQDS are implicated in the treatment of coronary heart disease. The key targets identified include AKT1, TNF, TP53, IL6, and VEGFA. Notably, the PI3K/AKT signaling pathway emerged as the primary pathway. Furthermore, animal experiments showed that, compared to the model group, SQDS significantly reduced levels of TNF-α, IL-6, Bax, and cardiac troponin I, while increasing Bcl-2 content. It also notably suppressed the expression of p-PI3K and p-AKT, thereby offering protection to myocardial tissue. Through the integrated approach of network pharmacology and molecular docking, we have established that SQDS exerts a multi-component, multi-target, and multi-pathway synergistic therapeutic effect on coronary heart disease. Its mechanism may involve the inhibition of the PI3K/AKT signaling pathway and the reduction of inflammatory factor expression.

Network pharmacology and experimental validation reveals the potential therapeutic effects of Polygonum cuspidatum against odontogenic keratocyst

This study aimed to explore active ingredients in Polygonum cuspidatum with potential effects on odontogenic keratocysts (OKCs) using network pharmacological approach and bioinformatic gene analysis. The active ingredients and targets of P. cuspidatum were selected from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) database, and the ingredient–target network was constructed using Cytoscape software. Differentially expressed genes (DEGs) of OKC were selected and Gene Ontology (GO) enrichment analysis were performed through bioinformatic analysis using Gene Expression Omnibus (GEO) dataset GSE38494. The STRING database platform was used to draw protein–protein interaction network diagram, then the hub gene analysis was performed by Cytoscape software. AutoDock Vina software was used to perform molecular docking verification of the effects of the active ingredients on potential core targets. Finally, we use OKC nude animal model to testify the potential effects of P. cuspidatum. Ten active ingredients of P. cuspidatum were obtained. A total of 205 drug targets and 38 potential core targets of P. cuspidatum were confirmed in OKCs. The hub genes included PPARG, SPP1, COL3A1, MMP2, HMOX1, CCL2, CXCL10, VCAM1, RUNX2 and IRF1. Molecular docking showed that the key active ingredients including luteolin and quercetin which exhibited good docking activity with key target proteins (VCAM1, HMOX1 and MMP2). GO enrichment revealed that the pathways of P. cuspidatum acting on OKCs included the response to toxic substance, response to nutrient levels and response to xenobiotic stimulus. P. cuspidatum treatment in OKC could significantly down-regulate COL3A1 and MMP2 expressions in vivo and vitro. Our study indicated that P. cuspidatum is a potential therapeutic candidate for OKCs.

Investigating the MicroRNA 10b Regulatory Network: A Bioinformatic Approach to Transcription Factor Binding and Cancer Implications.

miR-10b, that stands for microRNA 10 in bovine serum protein refers to a subgroup of small molecules belonging to the body especially involved in physiological processes with regard cancers initiation and progression as well cellular differentiation. An understanding of the regulation miR-10b along with identification of its corresponding transcription factors (TFs) that bind to the so-called mirR-10b Regulated-DNA Sequence (MRDS) as well discovering potential targets serves a powerful tool not only in elucidation but also pharmacological arsenal targeting miRNAs. In this work, two bioinformatics databases (JASPAR and PROMO) were used to suggest the putative TFs that can interact with miR-10b MRDS. Most interestingly, among the set of TFs common to both databases were a number have previously associated with histone modification. Since the function of miR-10b is well known, we focused only on TFs with documented associations to regulation by this particular miRNA. These TFs were E2F1, P53, SP1 and NFKB. In an attempt to investigate the regulatory network of TFs involved TFs associated with miR-10b, STRING database was utilized to study the interactions among the identified TFs and their functional enrichments. Through this analysis, we found important Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways linked with different kinds of cancer, the transcriptional regulation, and gene expression. This study aims to provide an inclusive analysis of TFs that control miR-10b by applying bioinformatics predictions and validate these findings over existing literature evidence. This method will deepen our knowledge towards miR-10b regulatory network and its implications in cancer biology and eventually discovering new treatment interventions.

Evolution of the regulatory subunits for the heteromeric acetyl-CoA carboxylase.

The committed step for de novo fatty acid (FA) synthesis is the ATP-dependent carboxylation of acetyl-coenzyme A catalysed by acetyl-CoA carboxylase (ACCase). In most plants, ACCase is a multi-subunit complex orthologous to prokaryotes. However, unlike prokaryotes, the plant and algal orthologues are comprised both catalytic and additional dedicated regulatory subunits. Novel regulatory subunits, biotin lipoyl attachment domain-containing proteins (BADC) and carboxyltransferase interactors (CTI) (both three-gene families in Arabidopsis) represent new effectors specific to plants and certain algal species. The evolutionary history of these genes in autotrophic eukaryotes remains elusive, making it an ongoing area of research. Analyses of potential protein-protein and co-occurrence interactions, informed by gene network patterns using the STRING database, in Arabidopsis thaliana and Chlamydomonas reinhardtii unveil intricate gene associations with ACCase, suggesting a complex interplay between FA synthesis and other cellular processes. Among both species, a higher number of co-expressed genes was identified in Arabidopsis, indicating a wider potential regulatory network of ACCase in plants. This review investigates the extent to which these genes arose in autotrophic eukaryotes and provides insights into their evolutionary trajectory. This article is part of the theme issue 'The evolution of plant metabolism'.

Network Pharmacology and Molecular Docking to Explore the Mechanism of Action of Danxiong Huoxue Tablets for the Prevention and Treatment of Heterotopic Ossification

Background: Danxiong Huoxue tablets have been used clinically to prevent and treat Heterotopic Ossification (HO) after total hip arthroplasty, but its therapeutic mechanism is not clear. background: Danxiong Huoxue Tablets has been used clinically to prevent and treat heterotopic ossification (HO) after total hip arthroplasty, but its therapeutic mechanism is not clear. Objectives: This study investigated the potential mechanism of action of Danxiong Huoxue tablets against HO using network pharmacology and molecular docking methods. Methods: The TCMID and SymMap databases and the existing literature were used to screen the active ingredients and targets of Danxiong Huoxue tablets, and the targets of heterotopic ossification were obtained from Gene Cards, DisGeNET, and PharmGkb databases. The PPI network diagram was constructed using the String database and Cytoscape 3.9.1 software. Finally, the core targets were analyzed by GO and KEGG enrichment and validated by molecular docking. Results: A total of 39 active ingredients and 328 corresponding targets of Danxiong Huoxue tablets were identified, which were enriched in signaling pathways, such as PI3K/Akt and MAPK. Molecular docking verified that there was good binding activity between the core targets and the corresponding components. Conclusion: Danxiong Huoxue tablets may prevent and treat HO by acting on key targets, such as SRC, AKT1, JUN, and TNF, and regulating the PI3K/Akt signaling pathway and MAPK signaling pathway.

Network Pharmacology and in vitro Experimental Verification on Intervention of Oridonin on Non-Small Cell Lung Cancer.

To explore the key target molecules and potential mechanisms of oridonin against non-small cell lung cancer (NSCLC). The target molecules of oridonin were retrieved from SEA, STITCH, SuperPred and TargetPred databases; target genes associated with the treatment of NSCLC were retrieved from GeneCards, DisGeNET and TTD databases. Then, the overlapping target molecules between the drug and the disease were identified. The protein-protein interaction (PPI) was constructed using the STRING database according to overlapping targets, and Cytoscape was used to screen for key targets. Molecular docking verification were performed using AutoDockTools and PyMOL software. Using the DAVID database, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were conducted. The impact of oridonin on the proliferation and apoptosis of NSCLC cells was assessed using cell counting kit-8, cell proliferation EdU image kit, and Annexin V-FITC/PI apoptosis kit respectively. Moreover, real-time quantitative PCR and Western blot were used to verify the potential mechanisms. Fifty-six target molecules and 12 key target molecules of oridonin involved in NSCLC treatment were identified, including tumor protein 53 (TP53), Caspase-3, signal transducer and activator of transcription 3 (STAT3), mitogen-activated protein kinase kinase 8 (MAPK8), and mammalian target of rapamycin (mTOR). Molecular docking showed that oridonin and its key target molecules bind spontaneously. GO and KEGG enrichment analyses revealed cancer, apoptosis, phosphoinositide-3 kinase/protein kinase B (PI3K/Akt), and other signaling pathways. In vitro experiments showed that oridonin inhibited the proliferation, induced apoptosis, downregulated the expression of Bcl-2 and Akt, and upregulated the expression of Caspase-3. Oridonin can act on multiple targets and pathways to exert its inhibitory effects on NSCLC, and its mechanism may be related to upregulating the expression of Caspase-3 and downregulating the expressions of Akt and Bcl-2.

Mechanistic Exploration of Smilax glabra Roxb. in Osteoarthritis: Insights from Network Pharmacology, Molecular Docking, and In Vitro Validation.

Background: Arthritis, a debilitating joint disease, remains a significant global health burden. This study uncovers the therapeutic potential of the medicinal plant Smilax glabra Roxb. (SGR) in attenuating progression of disease by modulating immune responses. Methods: Through computational approaches, key bioactive compounds in SGR were identified by using freely available databases: TCMSP, TCMID, HIT2.0, HERB, and INPUT in order to elucidate their underlying mechanisms of action. Therapeutic targets for the disease have been retrieved by TTD, GeneCard, and OMIM databases. The STRING database was used to analyze the protein-protein interactions (PPI) of intersecting genes. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to reveal the functional roles of genes. Mcule was used for molecular docking and binding affinity of compounds and targets were evaluated by DeepPurpose model. ALP activity, cell viability assay, TRAP staining were also performed. Results: A total of 14 active SGR compounds with 59 common targets for arthritis have been identified. These targets have a major role in controlling biological processes such as wound healing, oxygen responses, and chemical stimuli. Molecular docking by Mcule platform demonstrated that quercetin and β-sitosterol showed higher binding energy affinities with TNF, TP53, PTGS2, and JUN as compared to other targets. To explore the complex relationship between compounds and targets, pre-trained Davis and KIBA models were used to predict the affinity values of selected compounds. In MC3T3-E1 cells, ALP activity was significantly increased and bone marrow macrophages (BMM) showed a low number of TRAP-positive cells in SGR-treated cells. Conclusions: Our findings demonstrate that SGR effectively inhibits/regulates inflammatory responses, prevents cartilage degradation, promotes bone regeneration, and can be used as a promising candidate for the development of novel arthritis treatment.

Investigating the molecular mechanisms between type 1 diabetes and mild cognitive impairment using bioinformatics analysis, with a focus on immune response

The immune system is involved in the development and progression of several diseases. Type 1 diabetes mellitus (T1DM), an autoimmune disorder, influences the progression of several other conditions; however, the link between T1DM and mild cognitive impairment (MCI) remains unclear. This study investigated the underlying immune response mechanisms that contribute to the development and progression of T1DM and MCI. Microarray datasets for MCI (GSE63060) and T1DM (GSE30208) were retrieved from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified using the limma package. To explore the functional implications of these DEGs, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were conducted using ClusterProfiler. Protein–protein interaction networks for the DEGs were constructed using the STRING database and visualized using Cytoscape. The Molecular Complex Detection algorithm was used to analyze DEGs. Immune cell infiltration in patients with T1DM and MCI was analyzed using the xCell method. Gene set enrichment analysis was used to gain in-depth insights into the functional characteristics of T1DM and MCI. Immune-related genes were obtained from the GeneCards and ImmPort databases. Machine learning algorithms were used to identify potential hub genes associated with immunity for T1DM and MCI diagnosis, and the diagnostic value was assessed using the receiver operating characteristic curve. The identified genes were validated using quantitative polymerase chain reaction. In the T1DM and MCI datasets, 610 DEGs showed consistent trends, of which 232 and 378 were upregulated and downregulated, respectively. Immune response analysis revealed significant changes in the immune cells associated with MCI and T1DM. Using immune-related genes, DEGs, and machine learning techniques, we identified CD3D in the MCI and T1DM groups. We observed a gradual decline in the cognitive function of mice with T1DM as the disease progressed. CD3D expression increased with increasing disease severity; CD3D primarily affected CD4+ T cells. This study revealed a complex interaction between T1DM and MCI, providing novel insights into the intricate relationship between immune dysregulation and cognitive impairment and expanding our understanding of these two interconnected disorders. These findings will facilitate the development of therapeutic interventions and identification of potential therapeutic targets.

Colchicine, serotobenine, and kinobeon A: novel therapeutic compounds in Carthamus tinctorius L. for the management of diabetes

Diabetes, a global health concern, poses increasing mortality risks. The pathogenesis of diabetes involves multiple mechanisms, with oxidative stress being one of the key contributors. As synthetic drugs have various side effects, which can be minimized by using herbal plants. This study focuses on the In vitro antioxidant potential, α-amylase inhibition potential, identification of bioactive compounds, and hub genes in diabetes treatment mechanism by using C. tinctorius Extraction of C. tinctorious lead and flower was performed using different solvents (Distilled water, methanol, chloroform, and Dimethyl ether). After extraction different concentrations range from 25–200 mg/mL) was made and checked against activities. The antioxidant potential was assessed using 2, 2-diphenyl-1-picrylhydrazyl (DPPH), total phenolic contents (TPC), and total antioxidant capacity (TAC) assays, while antidiabetic activity was evaluated through α-amylase inhibition assay. Phytochemicals was identified by GC–MS analysis, followed by ADMET screening and network pharmacology analysis using Swiss Target Prediction, Gene Card, DesGeNet, DAVID, STRING, Cytoscape, and drug revitalization databases. Results revealed positive correlations with DPPH, TAC, and TPC. Methanol extract exhibited the highest inhibitory concentration. Screening of 46 compounds was performed by studying their pharmacokinetic properties which revealed 9 compounds effective against 204 diabetes targets. Moreover, their network analysis identified four hub genes, including AKT1, JUN, EGFR, and MMP9. These genes found highly associated with drugs like Colchicine and Serotobenine. Revitalization analysis also highlighted four genes (EGFR, PTGS2, AKT1, and MMP9) strongly correlated with FDA-approved drugs. The study suggests C. tinctorius methanol extract is a potential source for novel drugs.Graphical