Search Results (243)

Tubastraea coccinea and T. tagusensis, commonly known as sun corals, are two species of stony corals (Scleractinia, Dendrophylliidae) native to the Indo-Pacific region (T. coccinea) and the Galapagos Islands (T. tagusensis), respectively. They are considered highly invasive species, particularly in the Western Atlantic Ocean, due to high adaptability to various ecological conditions and notable resilience. Given their demonstrated invasiveness, it is important to delve into their physiology and the molecular bases supporting their resilience. However, to date, only a few molecular tools are available for the study of these organisms. The primary objective of the present study was the development of an efficient RNA extraction protocol for Tubastraea coccinea and T.a tagusensis samples collected off Ilha Grande Bay, Rio de Janeiro (Brazil). The quantity of isolated RNA was evaluated using NanoDrop, while its purity and quality were determined by evaluating the A260/A280 and A260/230 ratios. Subsequently, based on genes known for T. coccinea, two housekeeping genes and seven stress response-related genes were isolated and characterized, for the first time for both species, using a molecular approach. An interactomic analysis was also conducted, which revealed functional interactions among these genes. This study represents the first report on gene networks in Tubastraea spp., opening new perspectives for understanding the chemical ecology and the cellular mechanisms underlying the invasiveness of these species. The results obtained will be useful for ecological conservation purposes, contributing to the formulation of strategies to limit their further expansion. Full article

Severe COVID-19 disproportionately impacts patients with comorbidities such as type 1 diabetes (T1D), type 2 diabetes (T2D), obesity (OBCD), cardiovascular disease (CVD), hypertension (HTN), and cerebrovascular disease (CeVD), affecting 10–30% of cases. This study elucidates shared molecular mechanisms by identifying common hub genes and genetic variants across these conditions using an integrative bioinformatics approach. We curated 5463 COVID-19-related genes from DisGeNET, GeneCards, T-HOD, and other databases, comparing them with gene sets for T1D (324 genes), T2D (497), OBCD (835), CVD (1756), HTN (837), and CeVD (1421). Functional similarity analysis via ToppGene, hub gene prediction with cytoHubba, and Cytoscape-based protein–protein interaction networks identified four hub genes—CCL2, IL6, IL10, and TLR4—consistently shared across all conditions (p < 1.0 × 10⁻⁵). Enrichr-based gene ontology and KEGG analyses revealed cytokine signaling and inflammation as key drivers of COVID-19 cytokine storms. Polymorphisms like IL6 rs1800795 and TLR4 rs4986790 contribute to immune dysregulation, consistent with previous genomic studies. These genes suggest therapeutic targets, such as tocilizumab for IL6-driven inflammation. While computational, requiring biochemical validation, this study illuminates shared pathways, advancing prospects for precision medicine and multi-omics research in high-risk COVID-19 populations. Full article

Background: Deficiency of IL-36 Receptor Antagonist (DITRA) is a rare monogenic autoinflammatory disease, characterized by dysregulation of IL-36 signaling and phenotypically classified as a subtype of generalized pustular psoriasis. Objectives: This study aimed to explore the role of potentially coding and non-coding RNAs (ncRNAs) in the IL36RN interactome to identify putative pathogenic mechanisms, biomarkers, and therapeutic targets for DITRA. Methods: A systems biology approach was applied using the STRING database to construct the IL36RN protein–protein interaction network. Key ncRNA interactions were identified using RNAInter. The networks were visualized and analyzed with Cytoscape v3 and the CytoHubba plugin to identify central nodes and interaction hubs. Pathway enrichment analysis was then performed to determine the biological relevance of candidate ncRNAs and genes. Results: Analysis identified thirty-eight ncRNAs interacting with the IL36RN network, including six lncRNAs and thirty-two miRNAs. Of these, thirty-three were associated with key DITRA-related signaling pathways, while five remain to be validated. Additionally, seven protein-coding genes were highlighted, with three (TINCR, PLEKHA1, and HNF4A) directly implicated in biological pathways related to DITRA. Many of the identified ncRNAs have prior associations with immune-mediated diseases, including psoriasis, supporting their potential relevance in DITRA pathogenesis. Conclusions: This study provides novel insights into the ncRNA-mediated regulation of IL36RN and its network in the context of DITRA. The findings support the potential utility of specific ncRNAs and genes, such as TINCR, PLEKHA1, and HNF4A, as key genomic elements warrant further functional characterization to confirm their mechanistic roles and may inform biomarker discovery and targeted therapeutic development in DITRA. Full article

HSP110 is a ubiquitous chaperone contributing to proteostasis. It has a disaggregation activity and can refold denatured proteins. It can regulate fundamental signaling pathways involved in oncogenesis, such as Wnt/β-catenin, NF-κB and STAT3 signaling pathways. In gastric and colorectal cancer, HSP110 has been detected in the nucleus, and nuclear expression has been associated with the resistance of cells to 5-FU chemotherapy. Nuclear translocation of HSP110 is promoted by the exposure of cells to DNA-damaging agents. In a previous work, we demonstrated that nuclear HSP110 participates in the NHEJ DNA repair pathway by facilitating the recruitment of DNA-PKcs to Ku70/80 heterodimers at the site of DNA double-strand breaks. In the present work, analysis of HSP110s’ nuclear interactome revealed an enrichment of components from SWI/SNF chromatin remodeling complexes. We demonstrate that HSP110 is strongly associated with chromatin in temozolomide- and oxaliplatin-treated cells and directly interacts with the core subunit SMARCC2, thereby facilitating the assembly of SWI/SNF complexes. This work expands upon the role of HSP110, which regulates not only proteostasis but also the assembly of critical nuclear macromolecular complexes involved in the adaptive stress response. Full article

Insulin-degrading enzyme is a zinc metalloprotease that degrades low-molecular-weight substrates, including insulin. Ubiquitous expression, high evolutionary conservation, upregulation of Ide in stress situations, and literature findings suggest a broader function of Ide in cell physiology and protein homeostasis that remains to be elucidated. We used proteomics and transcriptomics approaches to search for leads related to a broader role of Ide in protein homeostasis. We combined an analysis of the proteome and single-cell transcriptome of Ide^+/+ and Ide^−/− pancreatic islet cells with an examination of the interactome of human cytosolic Ide using proximity biotinylation. We observe an upregulation of pathways related to RNA processing, translation and splicing in Ide^+/+ relative to Ide^−/− islet cells. Corroborating these results and providing a potential mechanistic explanation, proximity biotinylation reveals interaction of Ide with several subunits of CCR4-NOT, a key mRNA deadenylase regulating gene expression “from birth to death”. We propose a speculative model in which human and murine Ide cooperate with CCR4-NOT to control protein expression in proteotoxic and metabolic stress situations through cooperation between their deadenylase and protease functions. Full article

Parkinson’s disease (PD) is a complex neurodegenerative disorder lacking effective disease-modifying treatments. In this study, we integrated large-scale protein–protein interaction networks with a multi-modal graph neural network (GNN) to identify and prioritize multi-target drug repurposing candidates for PD. Network analysis and advanced clustering methods delineated functional modules, and a novel Functional Centrality Index was employed to pinpoint key nodes within the PD interactome. The GNN model, incorporating molecular descriptors, network topology, and uncertainty quantification, predicted candidate drugs that simultaneously target critical proteins implicated in lysosomal dysfunction, mitochondrial impairment, synaptic disruption, and neuroinflammation. Among the top hits were compounds such as dithiazanine, ceftolozane, DL-$\alpha$-tocopherol, bromisoval, imidurea, medronic acid, and modufolin. These findings provide mechanistic insights into PD pathology and demonstrate that a polypharmacology approach can reveal repurposing opportunities for existing drugs. Our results highlight the potential of network-based deep learning frameworks to accelerate the discovery of multi-target therapies for PD and other multifactorial neurodegenerative diseases. Full article

KRAS mutations are major drivers of human cancers, yet how distinct mutations rewire protein interactions and metabolic pathways to promote tumorigenesis remains poorly understood. To address this, we systematically mapped the protein interaction networks of wild-type KRAS and three high-frequency oncogenic mutants (G12C, G12D, and G12V) using TurboID proximity labeling coupled with quantitative proteomics. Bioinformatic analysis revealed mutant-specific binding partners and metabolic pathway alterations, including significant enrichment in insulin signaling, reactive oxygen species regulation, and glucose/lipid metabolism. These changes collectively drive tumor proliferation and immune evasion. Comparative analysis identified shared interactome shifts across all mutants: reduced binding to LZTR1, an adaptor for KRAS degradation, and enhanced recruitment of LAMTOR1, a regulator of mTORC1-mediated growth signaling. Our multi-dimensional profiling establishes the first comprehensive map of KRAS-mutant interactomes and links specific mutations to metabolic reprogramming. These findings provide mechanistic insights into KRAS-driven malignancy and highlight LZTR1 and LAMTOR1 as potential therapeutic targets. The study further lays a foundation for developing mutation-specific strategies to counteract KRAS oncogenic signaling. Full article

This research proposes to systematically investigate the cardioprotective mechanisms of Pericarpium Trichosanthis injection (PTI) against acute myocardial ischemia through an integrated approach combining ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) constituent profiling, UNIFI database-assisted component identification, network pharmacology-guided target prediction, molecular docking verification, and in vivo experimental validation. The multimodal methodology is designed to comprehensively uncover the therapeutic benefits and molecular pathways underlying this traditional Chinese medicine formulation. Methods: UPLC-Q-TOF/MS and the UNIFI database were used in conjunction with a literature review to screen and validate the absorbed components of PTI. Using network pharmacology, we constructed protein-protein interaction (PPI) networks for pinpointing prospective therapeutic targets. In addition, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to identify potential signaling pathways. In vivo experiments were conducted to investigate the mechanisms by which PTI ameliorated isoproterenol-induced myocardial injury in rats. All animal experiments have adhered to ARRIVE guidelines. Results: UPLC-Q-TOF/MS revealed 11 core active components in PTI. Network pharmacology prioritization identified pseudoaspidin, ciryneol C, cynanoside M, daurinol, and n-butyl-β-D-fructopyranoside as central bioactive constituents within the compound-target interaction network. Topological analysis of the protein interactome highlighted AKT1, EGFR, MMP9, SRC, PTGS2, STAT3, BCL2, CASP3, and MAPK3 as the most interconnected nodes with the highest betweenness centrality. Pathway enrichment analysis established the PI3K/Akt signaling cascade as the principal mechanistic route for PTI’s cardioprotective effects. Molecular docking simulations demonstrated high-affinity interactions between characteristic components (e.g., cynanoside M, darutigenol) and pivotal targets including PTGS2, MAPK3, CASP3, and BCL2. In vivo investigations showed PTI treatment markedly attenuated myocardial tissue degeneration and collagen deposition (p < 0.05), normalized electrocardiographic ST-segment deviations, and suppressed pro-inflammatory cytokine production (IL-6, TNF-α). The formulation concurrently reduced circulating levels of cardiac injury indicators (LDH, cTnI) and oxidative stress parameters (ROS, MDA), Regarding apoptosis regulation, PTI reduced Bax, caspase-3, and caspase-9, while elevating Bcl-2 (p < 0.05), effectively inhibiting myocardial cell apoptosis with all therapeutic outcomes reaching statistical significance. These findings highlight PTI’s protective effects against myocardial injury through multi-target modulation of inflammation, oxidation, and apoptosis. Conclusions: PTI exerts its therapeutic effects in treating acute myocardial ischemia by regulating and suppressing inflammatory responses, and inhibiting cardiomyocyte apoptosis. Full article

Background/Objectives: The MAST kinases are ancient AGC kinases associated with many human diseases, such as cancer, diabetes, and neurodevelopmental disorders. We set out to describe the origins and diversification of MAST kinases from a structural and bioinformatic perspective to inform future research directions. Methods: We investigated MAST-lineage kinases using database and sequence analysis. We also estimate the functional consequences of disease point mutations on protein stability by integrating predictive algorithms and AlphaFold. Results: Higher-order organisms often have multiple MASTs and a single MASTL kinase. MAST proteins conserve an AGC kinase domain, a domain of unknown function 1908 (DUF), and a PDZ binding domain. D. discoideum contains MAST kinase-like proteins that exhibit a characteristic insertion within the T-loop but do not conserve DUF or PDZ domains. While the DUF domain is conserved in plants, the PDZ domain is not. The four mammalian MASTs demonstrate tissue expression heterogeneity by mRNA and protein. MAST1-4 are likely regulated by 14-3-3 proteins based on interactome data and in silico predictions. Comparative ΔΔG estimation identified that MAST1-L232P and G522E mutations are likely destabilizing. Conclusions: We conclude that MAST and MASTL kinases diverged from the primordial MAST, which likely operated in both biological niches. The number of MAST paralogs then expanded to the heterogeneous subfamily seen in mammals that are all likely regulated by 14-3-3 protein interaction. The reported pathogenic mutations in MASTs primarily represent alterations to post-translational modification topology in the DUF and kinase domains. Our report outlines a computational basis for future work in MAST kinase regulation and drug discovery. Full article

Background/Objectives: Non-small cell lung cancer (NSCLC) is the most common type of cancer, with lung adenocarcinoma (LUAD) as the predominant subtype. Despite advancements in targeted therapies, many NSCLC patients still experience poor outcomes due to treatment resistance and disease progression. Genomic instability (GI), a hallmark of cancer, defined as the increased tendency of DNA mutations and alterations, is closely linked to cancer initiation, progression, and resistance to therapy. Emerging evidence suggests that long non-coding RNAs (lncRNAs)—molecules longer than 200 nucleotides that do not encode proteins but regulate gene expression—play critical roles in cancer biology and are associated with GI. However, the relationship between GI and lncRNA expression in LUAD remains poorly understood. Methods: In this study, we analyzed the transcript profiles of lncRNAs and mRNAs from LUAD samples in The Cancer Genome Atlas (TCGA) database and classified them based on their Homologous Recombination Deficiency (HRD) score. The HRD score is an unweighted sum of three independent DNA-based measures of genomic instability: loss of heterozygosity, telomeric allelic imbalance, and large-scale transitions. We then performed a differential gene expression analysis to identify lncRNAs and mRNAs that were either upregulated or downregulated in samples with high HRD scores compared to those with low HRD scores. Following this, we conducted a correlation analysis to assess the significance of the association between HRD scores and the expression of both lncRNAs and mRNAs. Results: We identified 30 differentially expressed lncRNAs and 200 mRNAs associated with genomic instability. Using an RNA interactome database from sequencing experiments, we found evidence of interactions between GI-associated lncRNAs (GI-lncRNAs) and GI-associated mRNAs (GI-mRNAs). Further investigation showed that some GI-lncRNAs play regulatory and functional roles in LUAD and other diseases. We also found that GI-lncRNAs have potential as prognostic biomarkers, particularly when integrated with HRD stratification. The expression of specific GI-lncRNAs was associated with primary therapy response and immune infiltration in LUAD. Additionally, we identified existing drugs that could modulate GI-lncRNAs, offering potential therapeutic strategies to address GI in LUAD. Conclusions: Our findings suggest that GI-associated lncRNAs could serve as valuable biomarkers for LUAD prognosis and therapeutic response. Furthermore, modulating these lncRNAs presents potential treatment avenues to address genomic instability in LUAD. Full article

BCL2 is a critical regulator of intrinsic and extrinsic pathways of apoptosis that have been implicated in cancer progression and therapeutic resistance. In this study, the protein–protein interactions (PPIs) of BCL2 with potential binding partners and their role in cancer was investigated. A comprehensive PPI network for BCL2 has been generated by using the Protein Interactions Network Analysis (PINA) platform to identify key interactors. To further investigate the network, Molecular Operating Environment (MOE), Search Tool for the Retrieval of Interacting Genes (STRING), Residue Interaction Network Generation (RING), and the gProfiler server were used. Docking and Molecular Dynamics (MD) simulations were performed by using HDOCK and Gromacs to analyze the binding dynamics and stability of protein complexes. The BCL2 interactome revealed that three key interactors (p53, RAF1, and MAPK1) are involved in cancer-related processes. Docking studies highlighted BCL2 residues such as ASP111, ASP140, ARG107, and ARG146 that were predominantly involved in multiple hydrogen bonds, ionic interactions, and van der Waals contacts, highlighting conserved binding sites that play critical roles in the stability and specificity of protein–protein interactions. MD simulations (200 ns) of the BCL2-p53 complex showed that the RMSD was increased, suggesting the suppression of BCL2’s anti-apoptotic activity by p53. The RMSD for BCL2-RAF1 was also increased, showing protein domain structural rearrangements that enhance BCL2 anti-apoptotic activity. The BCL2-MAPK1 complex revealed structural, distinct flexibility patterns and dynamic hydrogen bonding interactions. These findings provide valuable insights into the molecular dynamics by which BCL2 modulates apoptosis and its potential as a promising therapeutic in cancer and apoptosis-related diseases. Full article

Aquaporins are transmembrane proteins that mediate the transport of water, as well as various ions and molecules. In plants, they play a critical role in numerous processes, including stress adaptation, nutrition, cellular communication, and transpiration. Therefore, understanding the function and interactions of these proteins with others—known as interactomes—is of significant agronomic and biological interest. This study aims to analyse the interactome of all aquaporins in Arabidopsis thaliana L. using two distinct databases, STRING and BioGRID. After analysing both interactomes, a wide range of interactions were identified between each aquaporin and a diverse array of proteins, including nutrient transporters for ammonium, potassium, phosphorus, sulphur, copper, and sugars; proteins related to responses to abiotic stresses; proteins mediating vesicle membrane fusion, such as synaptobrevins and syntaxins; ubiquitinases; kinases; and other transmembrane proteins. These extensive connections further underscore the critical importance of aquaporins in numerous biological processes, positioning them as central modulators and integration points for cellular and systemic responses in plants. Full article

The gut microbiome, a complex ecosystem of microorganisms, plays a pivotal role in human health and disease. The gut microbiome’s influence extends beyond the digestive system to various organs, and its imbalance is linked to a wide range of diseases, including cancer and neurodevelopmental, inflammatory, metabolic, cardiovascular, autoimmune, and psychiatric diseases. Despite its significance, the interactions between gut bacteria and human proteins remain understudied, with less than 20,000 experimentally validated protein interactions between the host and any bacteria species. This study addresses this knowledge gap by predicting a protein–protein interaction network between gut bacterial and human proteins. Using statistical associations between Pfam domains, a comprehensive dataset of over one million experimentally validated pan-bacterial–human protein interactions, as well as inter- and intra-species protein interactions from various organisms, were used for the development of a machine learning-based prediction method to uncover key regulatory molecules in this dynamic system. This study’s findings contribute to the understanding of the intricate gut microbiome–host relationship and pave the way for future experimental validation and therapeutic strategies targeting the gut microbiome interplay. Full article

Background/Objectives: Alopecia is a hair disorder with a significant impact on quality of life, and its incidence has been increasing in recent years. Current therapeutic options are limited and may cause adverse side effects, highlighting the need to develop safer and more effective formulations. Therefore, the objective of this study was to evaluate the effect of a formulation based on the bioactive fraction of Bacopa procumbens (BFNB), conjugated with gold nanoparticles, on hair growth through the modulation of apoptosis in C57BL/6 mice. Methods: The potential biological activities of the secondary metabolites of B. procumbens present in BFNB were analyzed in silico. In vivo experiments evaluated the expression of pro-apoptotic markers p53, caspase 3-p11, caspase 9-p10, and Bax, as well as anti-apoptotic marker Bcl-2, through Western blotting. Immunohistochemistry further assessed the expression and localization of some of these markers. Additionally, molecular docking and interactomic analyses were performed, complemented by functional enrichment, to explore molecular pathways modulated by the evaluated proteins. Results: In silico analyses suggested that BFNB metabolites are involved in the modulation of hair growth, hair fragility, and apoptosis. This finding was supported by in vivo experiments in mice, where BFNB significantly decreased the expression of p53, caspase 3-p11, caspase 9-p10, and Bax while increasing Bcl-2 levels. Immunohistochemistry showcased a reduction in pro-apoptotic markers in dermal and follicular bulb cells. Furthermore, molecular docking studies identified BFNB metabolites as potential direct modulators of these key proteins, strengthening evidence of their role in apoptotic regulation. The interactomic analysis highlighted 50 proteins associated with apoptosis, and functional enrichment underscored key processes such as p53 signaling, regulation of the apoptosome, and mitochondrial membrane involvement in the intrinsic apoptosis mechanism, among other pathways. Conclusions: This study demonstrates that BFNB effectively modulates apoptosis through key molecular mechanisms, highlighting its potential as an innovative therapy for promoting hair growth. Full article

The highly contagious FMDV is the agent responsible for foot-and-mouth disease, significantly impacting animals with cloven hooves and incurring substantial economic losses globally. The FMDV genome, composed of single-stranded RNA, consists of approximately 8500 nucleotides and harbors a single open reading frame (ORF) encoding both structural and non-structural proteins vital for the virus’s pathogenicity and replication. BHK-21 (baby hamster kidney) cells are the optimal cell line for FMDV culture due to their robust viral replication ability and high infection susceptibility. The insufficient elucidation of the host response to FMDV hampers progress towards the establishment of precise therapeutic interventions. To fill this void in understanding, samples from FMDV-challenged and control BHK-21 cells were systematically procured, with comprehensive transcriptome sequencing subsequently undertaken to delineate the gene expression landscapes of each group. A total of 4018 differentially expressed genes were identified, of which 2044 were downregulated and 1974 were upregulated. The data indicate that FMDV infection significantly enhances transcription initiation in BHK-21. According to GO and KEGG enrichment analysis, FMDV affects a number of immune-related processes as well as the movement of chemicals within cells. In the analysis of the protein–protein interaction network, Fos, Flt3lg, Rpl22l1, Ifi35, Ep300, and Rps16 emerged as pivotal hub proteins, underscoring their significant roles within the cellular interactome. The RT-qPCR experiment of Lgfb5, Ler2, Vgll3, and Ahr verified that the DEGs’ expression profiles matched the results of the RNA-seq investigation. The study’s findings have enhanced our understanding of the molecular pathways underlying FMDV pathogenesis and host interactions. Furthermore, the identification of key genes could serve as potential targets for therapeutic strategies and diagnostic tools, thereby enhancing control measures for livestock foot-and-mouth disease and mitigating its economic impact. Full article