Protein-protein Interactions Research Articles

Accurate Prediction of Essential Proteins Using Ensemble Machine Learning

Abstract Essential proteins are crucial for biological processes and can be identified through both experimental and computational methods. While experimental approaches are highly accurate, they often demand extensive time and resources. To address these challenges, we present a computational ensemble learning framework designed to identify essential proteins more efficiently. Our method begins by using node2vec to transform proteins in the Protein-Protein Interaction (PPI) network into continuous, low-dimensional vectors. We also extract a range of features from protein sequences, including graph-theory-based, information-based, compositional, and physiochemical attributes. Additionally, we leverage deep learning techniques to analyze high-dimensional Position-Specific Scoring Matrices (PSSMs) and capture evolutionary information. We then combine these features for classification using various machine learning algorithms. To enhance performance, we integrate the outputs of these algorithms through ensemble methods such as voting, weighted averaging, and stacking. This approach effectively addresses data imbalances and improves both robustness and accuracy. Our ensemble learning framework achieved an AUC of 0.948 and an accuracy of 0.9252, outperforming other computational methods. These results demonstrate the effectiveness of our approach in accurately identifying essential proteins and highlight its superior feature extraction capabilities.

Identification of hub genes and pathways in Uterine corpus endometrial carcinoma (UCEC): A comprehensive in silico study

BackgroundUterine corpus endometrial carcinoma (UCEC), derived from the endometrium, is the most common type of endometrial malignasis. This gynecological malignancy is very common all over the world, especially in developed countries and shows a potentially rising trend correlated with the increase in obese women. MethodsDifferentially Expressed Genes (DEGs) analysis was conducted on GSE7305 and GSE25628 datasets from the Gene Expression Omnibus (GEO). DEGs were identified using GEO2R (adjusted p-value <0.05, |logFC| > 1). Pathway analysis employed KEGG and Gene Ontology databases, while protein-protein interactions were analyzed using Cytoscape and Gephi. GEPIA was used for target gene validation. ResultsWe have identified 304 common DEGs and 78 hub genes using GEO and PPI analysis, respectively. The GO and KEGG pathways analysis revealed enrichment of DEGs in extracellular matrix structural constituent, extracellular space, cell adhesion, and ECM-receptor interaction. GEPIA analysis identified three genes, ENG, GNG4, and ECT2, whose expression significantly differed between normal and tumor samples. ConclusionThis analysis study identified the hub genes and associated pathways involved in the pathogenesis of UCEC. The identified hub genes exhibit remarkable potential as diagnostic biomarkers, providing a significant opportunity for early diagnosis and more effective therapeutic approaches for UCEC.

Qihuang Zhuyu Formula Modulates Mitochondrial Function to Inhibit Platelet Activation via Endocannabinoid Signaling Mediated by the SIRT1/PPARα Pathway

Ethnopharmacological relevanceDeveloping effective drugs is urgent for preventing platelet activation and atherosclerotic disease. Qihuang Zhuyu Formula (QHZYF) is a curative medical plants formula in clinic while its molecular mechanism remains to be further elucidated. Aim of the studyTo investigate how QHZYF, via the sirtuin 1 (SIRT1)/peroxisome proliferator-activated receptor alpha (PPARα) pathway, mediates the endocannabinoid system, regulates mitochondrial function, and inhibits platelet activation, thereby offering novel strategies for the prevention and treatment of cardiovascular diseases. MethodsThe chemical constituents of QHZYF were characterized by ultra-performance liquid chromatography tandem with quadrupole time-of-flight mass spectrometry (UPLC-Q/TOF-MS). For the in vivo experiments, an atherosclerosis rat model was developed. Platelet activation and endocannabinoid levels were assessed by ELISA, while the expression of PPARα was evaluated by immunofluorescence. Additionally, the expression of endocannabinoid-degrading enzymes was analyzed by Western blotting. In the in vitro studies, the protein-protein interaction between SIRT1 and PPARα was initially investigated using co-immunoprecipitation (Co-IP). Thereafter, platelets were co-cultured with human umbilical vein endothelial cells (HUVECs) stimulated by oxidized low-density lipoprotein (ox-LDL). The mitochondrial function of platelets was examined by flow cytometry. Platelet activation and endocannabinoid levels were quantified using ELISA, and the expression of PPARα and endocannabinoid-degrading enzymes was determined by Western blotting. Subsequently, QHZYF was incorporated into the aforementioned system, and the entire experimental protocol was replicated to explore how QHZYF influences platelet activation through the SIRT1/PPARα pathway-mediated endocannabinoid system. ResultsIn the in vivo experiments, it was observed that QHZYF significantly augmented the levels of SIRT1 and PPARα, concurrently with a decrease in the expression of endocannabinoid-degrading enzymes. This was paralleled by a rise in endogenous cannabinoid levels and a reduction in platelet activation, a process that was found to be regulated by SIRT1. The co-immunoprecipitation (Co-IP) analysis substantiated the cooperative interaction between SIRT1 and PPARα, underscoring their role in mediating the endocannabinoid system, regulating mitochondrial function, and consequently influencing platelet activation. In the in vitro studies, a co-culture system involving platelets and HUVECs stimulated with ox-LDL was employed. It was noted that the SIRT1/PPARα pathway mediates the endocannabinoid system in regulating mitochondrial function, which in turn affects platelet activation. The incorporation of QHZYF-containing serum into this system produced outcomes consistent with those observed in the in vivo experiments. These findings suggest that QHZYF operates by modulating the endocannabinoid system via the SIRT1/PPARα pathway, thereby controlling mitochondrial function and inhibiting platelet activation. ConclusionSIRT1 may mediate endogenous cannabinoid signaling through its interaction with PPARα, regulating mitochondrial function and subsequently influencing platelet activation. QHZYF effectively modulates the endocannabinoid system via the SIRT1/PPARα pathway, thereby inhibiting platelet activation.

Exploration and identification of diabetes targets in nursing: CDH1 and DVL1.

Diabetes is a chronic disease caused by absolute or relative insufficiency of insulin secretion and impaired insulin utilization. CDH1 and DVL1 role in diabetes and its nursing care is unclear. The diabetes dataset GSE21321 and GSE19790 profiles were downloaded from the gene expression omnibus (GEO) database. Perform differentially expressed genes (DEGs) screening, weighted gene co-expression network analysis (WGCNA), protein-protein interaction (PPI) network construction and analysis, functional enrichment analysis, gene set enrichment analysis (GSEA), immune infiltration analysis, and Comparative Toxicogenomics Database (CTD) analysis. Gene expression heat map was drawn. TargetScan was used to screen the miRNA that regulates central DEGs. 1983 DEGs were obtained. According to Gene Ontology (GO) analysis, they were mainly enriched in signal regulation, catenin complexes, and signal receptor binding. In Kyoto Encyclopedia of Gene and Genome (KEGG) analysis, they were mainly concentrated in the Rap1 signaling pathway, cAMP signaling pathway, and Hippo signaling pathway. The DEGs are mainly enriched in cell signaling, Wnt signaling vesicles, growth factor activity, and the interaction between neural active ligands and receptors. In the enrichment project of Metascape, BMP signaling pathways and cell population proliferation can be seen in the GO enrichment project. The soft threshold power in WGCNA is set to 5. A total of 15 modules were generated. Core gene expression heatmap showed that core genes (CTNNB1, CDH1, DVL1) were highly expressed in diabetes samples. CTD analysis showed thatCTNNB1, CDH1, DVL1were associated with weight gain, inflammation, and necrosis. CDH1 and DVL1 are highly expressed in diabetes and may become molecular targets for diabetes and its care.

Proteome-wide Mendelian randomization and functional studies uncover therapeutic targets for polycystic ovarian syndrome.

Polycystic ovarian syndrome (PCOS) is an endocrine syndrome that affects a large portion of women worldwide. This proteogenomic and functional study aimed to uncover candidate therapeutic targets for PCOS. We comprehensively investigated the causal association between circulating proteins and PCOS using two-sample Mendelian randomization analysis. Cis-protein quantitative trait loci were derived from six genome-wide association studies (GWASs) on plasma proteome. Genetic associations with PCOS were obtained from a large-scale GWAS meta-analysis, FinnGen cohort, and UK Biobank. Colocalization analyses were performed to prioritize the causal role of candidate proteins. Protein-protein interaction (PPI) and druggability evaluation assessed the druggability of candidate proteins. We evaluated the enrichment of tier 1 and 2 candidate proteins in individuals with PCOS and a mouse model and explored the potential application of the identified drug target. Genetically predicted levels of 65 proteins exhibited associations with PCOS risk, with 30 proteins showing elevated levels and 35 proteins showing decreased levels linked to higher susceptibility. PPI analyses revealed that FSHB, POSTN, CCN2, and CXCL11 interacted with targets of current PCOS medications. Eighty medications targeting 20 proteins showed their potential for repurposing as therapeutic targets for PCOS. EGLN1 levels were elevated in granulosa cells and the plasma of individuals with PCOS and in the plasma and ovaries of dehydroepiandrosterone (DHEA)-induced PCOS mouse model. As an EGLN1 inhibitor, administration of roxadustat in the PCOS mouse model elucidated the EGLN1-HIF1α-ferroptosis axis in inducing PCOS and validated its therapeutic effect in PCOS. Our study identifies candidate proteins causally associated with PCOS risk and suggests that targeting EGLN1 provides a promising treatment strategy.

Unravelling the Significance of Seed Proteomics: Insights into Seed Development, Function, and Agricultural Applications.

Seeds are essential for plant reproduction, ensuring species survival and dispersal while adapting to diverse environments throughout a plant's life. Proteomics has emerged as a powerful tool for deciphering the complexities of seed growth, germination, and stress responses. Advanced proteomic technologies enable the analysis of protein changes during germination, dormancy, and ageing, enhancing our understanding of seed lifespan and vitality. Recent studies have revealed detailed insights into metabolic processes and storage protein profiles across various plant species. This knowledge is crucial for improving seed storage, conserving quality, and maintaining viability. Additionally, it contributes to sustainable agriculture by identifying stress-responsive proteins and signalling pathways that can mitigate stress and enhance farming practices. This review highlights significant advancements in seed proteomics over the past decade, discussing critical discoveries related to storage proteins, protein interactions, and proteome modifications due to stress. It illustrates how these insights transform seed biology, boosting productivity, food security, and environmentally friendly practices. The review also identifies existing knowledge gaps and provides direction for future research, underscoring the need for continued interdisciplinary collaboration in this dynamic field.

Silibinin Induces Both Apoptosis and Necroptosis with Potential Anti-tumor Efficacy in Lung Cancer.

Lung cancer incidence is steadily on the rise, posing a growing threat to human health. The search for therapeutic drugs from natural active substance and elucidating their mechanism have been the focus of anti-tumor research. In our work, Silibinin (SiL) was chosen as a possible substance that could inhibit lung cancer. and its effects on inducing tumor cell death have been studied. CCK-8 analysis and morphological observation were used to assess the cytotoxic impacts of SiL on lung cancer cells in vitro. The alterations in mitochondrial membrane potential (MMP) and apoptosis rate of cells were detected by flow cytometry. The level of lactate dehydrogenase (LDH) release out of cells was measured. The expression changes of apoptosis or necroptosis-related proteins were detected using western blotting. Protein interactions among RIPK1, RIPK3 and MLKL were analyzed using the co-immunoprecipitation technique. In vivo, SiL was evaluated for its antitumor effects using LLC tumor-bearing mice with mouse lung cancer. With an increased dose of SiL, the proliferation ability of A549 cells was considerably inhibited, and the accompanying cell morphology changed. The results of flow cytometry showed that after SiL treatment, MMP levels decreased, and the proportion of cells undergoing apoptosis increased. The proteins associated with apoptosis were upregulated and activated. The amount of LDH released from the cells increased following SiL treatment, accompanied by augmented expression and phosphorylation levels of necroptosis-related proteins. The co-IP assay further confirmed necrosome formation induced by SiL. Furthermore, Necrosulfonamide (an MLKL inhibitor) increased the apoptotic rate of SiL-treated cells and aggravated the cytotoxic effect of SiL, indicating that necroptosis blockade could switch cell death to apoptosis and increase the inhibitory effect of SiL on A549 cells. In LLC-bearing mice, gastric administration of SiL significantly inhibited tumor growth. This study helped clarify the anti-tumor mechanism of SiL against lung cancer, elucidating its role in dual induction of apoptosis and necroptosis. In particular, necroptosis blockade could switch cell death to apoptosis and increase the inhibitory effect of SiL. Our work provided an experimental basis for the research on cell death induced by SiL and revealed its possible applications for improving the management of lung cancer.</p>.

Tetrahydrocurcumin targets TRIP13 inhibiting the interaction of TRIP13/USP7/c-FLIP to mediate c-FLIP ubiquitination in triple-negative breast cancer

IntroductionTriple-negative breast cancer (TNBC) has a high mortality rate and limited treatment options. Tetrahydrocurcumin (THC), a major metabolite of curcumin, has potential antitumor activities. However, the antitumor effects and mechanism of THC in TNBC remain elusive. ObjectivesTo investigate the mechanism of THC in combating TNBC by targeting TRIP13 to disrupt the interaction of the TRIP13/USP7/c-FLIP complex and mediate c-FLIP ubiquitination both in vitro and in vivo. MethodsApoptosis was measured by TUNEL and flow cytometry. Click chemistry-based target fishing, CETSA, DARTS, and SPR were used to identify direct target of THC. Protein interactions was examined using co-immunoprecipitation. The role of USP7 in THC-mediated c-FLIP ubiquitination was evaluated by in vitro deubiquitination assay. Human breast cancer clinical samples were employed to assess the expression of c-FLIP, TRIP13, and USP7. The impact of THC on USP7/TRIP13/c-FLIP was analyzed using co-immunoprecipitation, confocal microscopy, molecular docking and dynamics simulations. ResultsTHC effectively inhibits TNBC cell proliferation and tumor growth in vitro and in vivo without significant toxicity. Mechanistically, THC induces extrinsic apoptosis in TNBC primarily by promoting degradation of c-FLIP, a key negative regulator in the apoptotic pathway. Furthermore, utilizing click chemistry-based target fishing, we identified TRIP13, a component of the highly conserved AAA ATPase family, as a direct target of THC in combating TNBC. Interestingly, contrary to previous drug-target studies, the knockdown of TRIP13 further amplified the antitumor effects of THC. After in-depth investigation, it was revealed that TRIP13 forms a trimeric complex with USP7 and c-FLIP in TNBC cells. THC specifically targets TRIP13 to disrupt the interaction of TRIP13/USP7/c-FLIP, leading to the ubiquitination of c-FLIP, ultimately inducing extrinsic apoptosis. ConclusionsThese findings offer new insights into the novel molecular mechanisms of anti-TNBC effects of THC and present a promising targeted therapeutic strategy for TNBC.

The Dmrt1 gene: Identification and functional analysis in testicular development and spermatogenesis in the freshwater prawn, Macrobrachium nipponense

Products of the Dmrt gene family are known to harbor a zinc-finger DM domain and play crucial roles as transcription factors in various physiological processes, including sexual differentiation, gonadal development, and spermatogenesis. Despite their significance, research on the Dmrt family in Crustacea remains limited. In the present study, we identified a member of this gene family in the freshwater prawn Macrobrachium nipponense and designated it as MnDmrt1. We investigated its expression patterns across different tissues, potential target genes, and its influence on testicular development and protein interactions within the testes. Our findings revealed that MnDmrt1 encodes a protein composed of 252 amino acids that is predominantly expressed in the testes and localized in spermatogonia, spermatocytes, and spermatozoa. Silencing MnDmrt1 disrupts spermatogenesis and alters the expression levels of several key genes associated with testicular development, spermatogenesis, and sex reversal, such as Dmrt11E, Insulin receptor, and Masculinizer. Additionally, we identified 59 proteins that interact with MnDmrt1 in the testis using pull-down assays and liquid chromatography-tandem mass spectrometry. Notably, the eyestalk negatively regulates the expression level of MnDmrt1 in the testis. Collectively, these results underscore the essential role of MnDmrt1 in testicular development and spermatogenesis in M. nipponense.

Topological embedding and directional feature importance in ensemble classifiers for multi-class classification

Cancer is the second leading cause of disease-related death worldwide, and machine learning-based identification of novel biomarkers is crucial for improving early detection and treatment of various cancers. A key challenge in applying machine learning to high-dimensional data is deriving important features in an interpretable manner to provide meaningful insights into the underlying biological mechanismsWe developed a class-based directional feature importance (CLIFI) metric for decision tree methods and demonstrated its use for the The Cancer Genome Atlas proteomics data. The CLIFI metric was incorporated into four algorithms, Random Forest (RF), LAtent VAriable Stochastic Ensemble of Trees (LAVASET), and Gradient Boosted Decision Trees (GBDTs), and a new extension incorporating the LAVA step into GBDTs (LAVABOOST). Both LAVA methods incorporate topological information from protein interactions into the decision function.The different models' performance in classifying 28 cancers resulted in F1-scores of 92.6% (RF), 92.0% (LAVASET), 89.3% (LAVABOOST) and 85.7% (GBDT), with no method outperforming all others for individual cancer type prediction. The CLIFI metric enables visualisation of the model's decision-making functions. The resulting CLIFI value distributions indicated heterogeneity in the expression of several proteins (MYH11, ERα, BCL2) across different cancer types (including brain glioma, breast, kidney, thyroid and prostate cancer) aligning with the original raw expression data.In conclusion, we have developed an integrated, directional feature importance metric for multi-class decision tree-based classification models that facilitates interpretable feature importance assessment. The CLIFI metric can be combined with incorporating topological information into the decision functions of models to introduce inductive bias, enhancing interpretability.

Inhibitory Potential of the Truncated Isoforms on Glutamate Transporter Oligomerization Identified by Computational Analysis of Gene-Centric Isoform Maps.

Glutamate transporters play a key role in central nervous system physiology by maintaining excitatory neurotransmitter homeostasis. Biological assemblies of the transporters, consisting of cyclic homotrimers, emerge as a crucial aspect of glutamate transporter modulation. Hence targeting heteromerization promises an effective approach for modulator design. On the other hand, the dynamic nature of transcription allows for the generation of transporter isoforms in structurally distinct manners. The potential isoforms were identified through the analysis of computationally generated gene-centric isoform maps. The conserved features of isoform sequences were revealed by computational chemistry methods and subsequent structural analysis of AlphaFold2 predictions. Truncated isoforms were further subjected to a wide range of docking analyses, 50ns molecular dynamics simulations, and evolutionary coupling analyses. Energetic landscapes of isoform-canonical transporter complexes suggested an inhibitory potential of truncated isoforms on glutamate transporter bio-assembly. Moreover, isoforms that mimic the trimerization domain (in particular, TM2 helices) exhibited stronger interactions with canonical transporters, underscoring the role of transmembrane helices in isoform interactions. Additionally, self-assembly dynamics observed in truncated isoforms mimicking canonical TM5 helices indicate a potential protective role against unwanted interactions with canonical transporters. Our computational studies on glutamate transporters offer insights into the roles of alternative splicing on protein interactions and identifies potential drug targets for physiological or pathological processes.

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.

Metabolomics combined with network pharmacology revealed a paradigm for determining the mechanism underlying the metabolic action of Gegen Qinlian Decoction amelioration of ulcerative colitis in mice

Ulcerative colitis (UC) is a common disease of the digestive system that is challenging to treat. Gegen Qinlian Decoction (GQD), which is an ancient classic formula in Chinese medicine, is effective at alleviating the symptoms of UC, but comprehensive research on its mechanism of action has not been performed. Here, we explored the material basis and potential molecular mechanism underlying GQD-mediated protection against UC by integrated metabolomics and network pharmacology. First, differentially expressed metabolites were screened and identified via a metabolomics approach, and the metabolic pathway was analyzed via MetaboAnalyst. Second, a protein–protein interaction (PPI) network was constructed to identify hub genes that encode metabolic enzymes. Third, the differentially expressed metabolites were used to construct a compound-reaction-enzyme-gene network. Finally, the metabolites were compared with relevant active components for molecular docking, molecular dynamics (MD) simulation, and verification experiment. GQD intervention alleviated UC in mice and significantly inhibited metabolic dysfunction in mice with UC; specifically, GQD reversed the abnormal changes in metabolites in the colon and serum, and regulated the arachidonic acid metabolism, tryptophan metabolism, glycerophospholipid metabolism, and purine metabolism pathways. Further literature review and molecular docking analysis with targeted MD simulation and Poisson-Boltzmann surface area (MM-PBSA) analysis were performed, revealing that GQD may inhibit the disruption of arachidonic acid metabolism and tryptophan metabolism by suppressing PTGS2 and CYP450 protein expression; these results were verified by qRT-PCR, WB, and surface plasmon resonance (SPR) assays. Our experiments indicated that GQD alleviated UC in mice by systematically regulating arachidonic acid metabolism and tryptophan metabolism, supporting further research and the development of GQD as a novel drug for ameliorating UC.

Investigating the Mechanism of Banxia Xiexin Decoction in Treating Gastritis and Diabetes Mellitus through Network Pharmacology and Molecular Docking Analysis

Background: Banxia Xiexin decoration (BXD), a complex prescription in Traditional Chinese Medicine (TCM), clinically acts as a treatment for gastritis and diabetes while its mechanism of treatment remains unknown. Objection: This study aimed to explore the common mechanism of BXD in treating gastritis and diabetes based on network pharmacology and molecular docking technology. Methods: The seven Chinese herbal components and drug targets were collected from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) for gastritis and diabetes using GeneCards, DisGeNET, Comparative Toxicogenomics Database (CTD), and Online Mendelian Inheritance in Man (OMIM) databases. Common drug and disease targets were imported into the STRING data platform for protein-protein interaction (PPI) analysis, and Cytoscape 3.7.2 software for network topology analysis, and core targets were filtered. Results: There were 124 components, 249 targets, 449 targets for gastritis, and 4005 targets for diabetes. After mapping, 83 BXD targets for gastritis and diabetes were obtained, and the targets with high correlation were STAT 3, JUN, TNF, IL-6, etc. More relevant targets were involved in the cancer pathway, AGE-RAGE signaling pathway of diabetic complications, fluid shear stress, and atherosclerosis pathway. Conclusion: This study preliminarily reveals that BXD may play a role in the treatment of gastritis and diabetes mellitus through multi-components, multi-targets, and multi-pathways, and proposes some potential "component-target-pathway" hypotheses in light of previous reports.

Controlling the co-aggregation and gelation of cod-soy binary proteins based on partially/fully denatured soy proteins

Structured binary protein networks offer a pathway for designing gel-based foods with less ecological and economic effects. This study investigated the heat-mediated interaction and gelation kinetics of cod-soy mixed proteins at molecular level. Results indicated that denaturation degree of soy proteins was fundamental in determining the protein-protein interactions during heating. Considerable non-natural β-sheet was generated in the heterogeneous structures to initiate their aggregation behavior. Cod actomyosin comprising myosin heavy chains and actin mainly regulated their aggregation below 70 °C. At higher temperatures, the formation of large-sized and intermediary-sized aggregates was dominated by disulfide bond exchange between cod actomyosin and soy A-B aggregates (≤ 85 °C) or dissociated B subunits (> 85 °C). These aggregates were further evidenced as essential components to form gel networks with higher storage modulus (G'). These findings provide fundamental insights for designing gel-based products with desirable nutritional and textural properties based on plant-animal binary proteins.

Structure formation in high moisture extrudates produced from soy protein fractions varying in 7S/11S globulin ratio.

Soy proteins mainly comprise 7S and 11S globulins, which have distinct structural and physical properties. To investigate the impact of soy protein composition on structure formation during high moisture extrusion (HME), fractions enriched in 7S or 11S globulins were prepared and blended in different ratios for lab-scale HME processing. Extrudates prepared from the 11S globulin-enriched fraction were inhomogeneous, as opposed to all other extrudates. Differences in extrudate structure and texture by varying the raw material protein composition were limited. However, 11S globulin-enriched fraction based extrudate was mainly stabilized by disulfide bonds, while with increasing raw material 7S globulin content the importance of non-covalent interactions increased. Even after disrupting all (non-)covalent bonds, high MW aggregates were detected in all extrudates. Thus, the protein composition of soy protein ingredients clearly impacts the type of protein-protein interactions and bonds formed during HME processing. This may hold relevance for the occurrence of specific phenomena during HME, such as syneresis, or the digestibility of the obtained products, although this requires further investigation. Overall, the findings of this study have implications for the use of protein-rich ingredients, which may vary in protein composition as the result of biological variability or prior processing, in high moisture extrusion.

The landscape of intrinsically disordered proteins in Leishmania parasite: Implications for drug discovery

Proteins that lack three-dimensional structures are known as Intrinsically disordered proteins (IDPs). In this study, we aimed to identify intrinsically disordered proteins in the Leishmania donovani proteome using various predictors that can identify IDPs based on amino acid residues and charge hydropathy. Top identified IDPs are analyzed using STRING, PSP-Hunter, Deep Loc-2.0, and Alpha fold to understand the protein-protein interaction, phase separation, localization, and structural assessment of those proteins. From this study, we found that >50 % of Leishmania donovani proteome has proteins or regions of proteins that are intrinsically disordered with VSL2 score >0.5; most proteins interact with many other proteins with PPI enrichment p-value <1.0e-16. Few proteins, such as Protein phosphatase inhibitor, UMSBP, and Zinc knuckle, have redox-sensitive regions. Functional disorder profiles of identified IDPs showed MoRFs and predicted protein domains. HASPB, UTP11, Nucleolar protein 12, and UMSBP have a high probability of undergoing phase separation. Localization studies showed that most of these proteins are in the cytoplasm and nucleus. Our present study of identifying IDPs in Leishmania proteome yields significant information on druggable targets and can serve as a basis for further studies to identify unexplored pathways.

FBXO22 inhibits colitis and colorectal carcinogenesis by regulating the degradation of the S2448-phosphorylated form of mTOR

Inflammatory bowel disease (IBD) is a considerable threat to human health with a significant risk for colorectal cancer (CRC). However, currently, both the molecular pathogenesis and therapeutic treatment of IBD remain limited. In this report, using both systemic and intestinal epithelium-specific gene knockout mouse models, we demonstrate that FBXO22, a substrate receptor within the SKP1-Cullin 1-F-box family of E3 ubiquitin ligases, plays an inhibitory role in the Azoxymethane/Dextran Sodium Sulfate-induced colorectal inflammatory responses and CRC. FBXO22 targets the serine 2448-phosphorylated form of mammalian mechanistic target of rapamycin (pS2448-mTOR) for ubiquitin-dependent degradation. This proteolytic targeting effect is established based on multiple lines of evidence including the results of colon tissue immunoblots, analysis of cultured cells with altered abundance of FBXO22 by depletion or overexpression, comparison of protein decay rate, effects on mTOR substrates S6K1 and 4E-BP1, analysis of protein-protein interactions, phosphor-peptide binding and competition, as well as reconstituted and cellular ubiquitination. Finally, we have shown that mTOR inhibitor rapamycin (RAPA) was able to alleviate the effects of fbxo22 deletion on colorectal inflammatory response and CRC. These RAPA effects are correlated with the ability of RAPA to inhibit pS2448-mTOR, pS6K1, and p4E-BP1. Collectively, our data support a suppressive role for FBXO22 in colorectal inflammation signaling and CRC initiation by targeting pS2448-mTOR for degradation.

Identification and validation of miR-21 key genes in cervical cancer through an integrated bioinformatics approach

Cervical cancer is one of the most prevalent female reproductive cancers. miR-21 is a multi-target oncomiR that has shown its potential in regulating several cancers including colon, pancreatic, breast, prostate, ovarian, and cervical cancer. However, the signaling network of miR-21 remains underexplored, and only a limited number of miR-21 gene targets in cervical cancer have been reported. In this context, the present study was undertaken to evaluate the role of miR-21 in cervical cancer by combining in silico analysis with in vitro validation in cervical cancer cells. The miR-21 target genes were predicted using four different prediction tools: miRwalk, DIANA, miRDBs, and TargetScan. A total of 113 overlapping target genes, common in at least three of the prediction tools, were shortlisted and subjected to functional enrichment analysis. The analysis predicted that JAK-STAT, MAPK, neurotrophin, and Ras signaling pathways are significantly (p≤0.05) targeted by miR-21. The MCODE plugin identified the potential cluster in the protein-protein interaction network based on the highest degree of connectivity. After GEPIA2 validation of all 20 hub genes, NTF3, LIFR, and IL-6R were shortlisted for validation in cervical cancer cell lines. The results showed that NTF3, LIFR, and IL-6R were significantly upregulated in the miR-21 knockdown CaSki cell lines in 6.27, 1.92 and 1.71 folds (p≤0.01), respectively. Similarly, in HeLa cell lines expression of NTF3, LIFR, and IL-6R were overexpressed in 4,06, 5.65, 2.42 folds (p≤0.001), respectively. confirming the role of miR-21 in regulating the expression of these genes. Additionally, the knockdown of miR-21 significantly inhibited the secretion of matrix metalloproteinases by CaSki cells. These results highlight that miR-21 could be a potential therapeutic target for cervical cancer, although further preclinical and clinical studies are required to validate its role and efficacy.

Identification of immune-related hub genes in chronic obstructive pulmonary disease

ObjectiveAs a prevalent persistent respiratory disease, chronic obstructive pulmonary disease (COPD) is featured by airflow limitation and chronic inflammation. This study focused on the identification of immune-related hub genes in COPD. MethodsWe employed the GSE38974 dataset to analyze differentially expressed genes (DEGs) of COPD. Then, we obtained COPD immune-related DEGs (COPD-IMDEGs) based on the intersection of DEGs and immune-related genes. Subsequently, we carried out Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses on COPD-IMDEGs. We established a protein-protein interaction network based on COPD-IMDEGs. The hub genes were determined by utilizing the Maximal Clique Centrality method. We utilized receiver operating characteristic (ROC) curves to analyze the clinical significance of hub genes in COPD. In addition, potential drugs targeting hub genes were predicted based on interactions between hub gene-corresponding proteins and drugs. ResultsA total of 45 COPD-IMDEGs were obtained through differential analysis. Enrichment analyses showed that COPD-IMDEGs were associated with cytokines, growth factors, and receptor ligands. Ten COPD-IMDEGs were identified as hub genes. As shown by ROC curves, these genes had potential value in identifying COPD patients. Drug prediction results showed that simvastatin and other drugs targeted hub genes. ConclusionThis study analyzed the potential biological functions enriched by COPD-IMDEGs, identified ten genes as biological markers for diagnosing COPD, and predicted potential drugs for treating COPD.