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Although the disease caused by chikungunya virus (CHIKV) is of great interest to public health organizations around the world, there are still no authorized antivirals for its treatment. Previously, dihalogenated anti-CHIKV compounds derived from L-tyrosine (dH-Y) were identified as being effective against in vitro infection by this virus, so the objective of this study was to determine the mechanisms of its antiviral action. Six dH-Y compounds (C1 to C6) dihalogenated with bromine or chlorine and modified in their amino groups were evaluated by different in vitro antiviral strategies and in silico tools. When the cells were exposed before infection, all compounds decreased the expression of viral proteins; only C4, C5 and C6 inhibited the genome; and C1, C2 and C3 inhibited infectious viral particles (IVPs). Furthermore, C1 and C3 reduce adhesion, while C2 and C3 reduce internalization, which could be related to the in silico interaction with the fusion peptide of the E1 viral protein. Only C3, C4, C5 and C6 inhibited IVPs when the cells were exposed after infection, and their effect occurred in late stages after viral translation and replication, such as assembly, and not during budding. In summary, the structural changes of these compounds determine their mechanism of action. Additionally, C3 was the only compound that inhibited CHIKV infection at different stages of the replicative cycle, making it a compound of interest for conversion as a potential drug.

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COVID-19, caused by the SARS-COV-2 virus, induces numerous immunological reactions linked to the severity of the clinical condition of those infected. The surface Spike protein (S protein) present in Sars-CoV-2 is responsible for the infection of host cells. This protein presents a high rate of mutations, which can increase virus transmissibility, infectivity, and immune evasion. Therefore, we propose to evaluate, using immunoinformatic techniques, the predicted epitopes for the S protein of seven variants of Sars-CoV-2. MHC class I and II epitopes were predicted and further assessed for their immunogenicity, interferon-gamma (IFN-γ) inducing capacity, and antigenicity. For B cells, linear and structural epitopes were predicted. For class I MHC epitopes, 40 epitopes were found for the clades of Wuhan, Clade 2, Clade 3, and 20AEU.1, Gamma, and Delta, in addition to 38 epitopes for Alpha and 44 for Omicron. For MHC II, there were differentially predicted epitopes for all variants and eight equally predicted epitopes. These were evaluated for differences in the MHC II alleles to which they would bind. Regarding B cell epitopes, 16 were found in the Wuhan variant, 14 in 22AEU.1 and in Clade 3, 15 in Clade 2, 11 in Alpha and Delta, 13 in Gamma, and 9 in Omicron. When compared, there was a reduction in the number of predicted epitopes concerning the Spike protein, mainly in the Delta and Omicron variants. These findings corroborate the need for updates seen today in bivalent mRNA vaccines against COVID-19 to promote a targeted immune response to the main circulating variant, Omicron, leading to more robust protection against this virus and avoiding cases of reinfection. When analyzing the specific epitopes for the RBD region of the spike protein, the Omicron variant did not present a B lymphocyte epitope from position 390, whereas the epitope at position 493 for MHC was predicted only for the Alpha, Gamma, and Omicron variants.

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INTRODUCTION: Breast cancer is one of the main causes of death in women. Luminal tumors A and B show good response with hormonal treatments, tumors that overexpress HER-2 can be treated with monoclonal antibodies, whereas triple negative tumors have few treatments available because they present low or absent expression of hormone receptors and HER-2, in addition, they present worse tumor progression. Syndecans are heparan sulfate proteoglycans that have the function of interacting with growth factors, cytokines, and extracellular matrix, thus modulating important processes in tumor progression. OBJECTIVE: Analyze the expression of syndecan-4 in different subtypes of breast tumors. METHODS: Bioinformatics is a useful tool for the study of new biomarkers. In the present study, the TCGA database (514 patients) and Metabric (1,898 patients) were analyzed using the cBioportal software. Gene expression data were analyzed by RNA-Seq and Microarray from biopsies of breast tumors. RESULTS: An alteration in syndecan-4 gene expression was observed among the different subtypes of breast tumors. Patients with a triple-negative tumor had decreased expression for syndecan-4 in both databases. CONCLUSION: Syndecan-4 is a potential biomarker for breast tumor prognosis since decreased expression of syndecan-4 is related to triple-negative breast cancer.

INTRODUÇÃO: O câncer de mama corresponde a uma das principais causas de morte em mulheres. Os tumores luminais A e B apresentam boa resposta com tratamentos hormonais, os tumores que superexpressam HER-2 podem ser tratados com anticorpos monoclonais, já os tumores triplo-negativos apresentam poucos tratamentos disponíveis por apresentarem expressão baixa ou ausente dos receptores hormonais e HER-2, além de pior progressão tumoral. Os sindecans são proteoglicanos de heparam sulfato que tem função de interagir com fatores de crescimento, citocinas e matriz extracelular, modulando assim processos importantes na progressão tumoral. OBJETIVO: Analisar a expressão o sindecam-4 nos diferentes subtipos de tumores de mama. MÉTODOS: A bioinformática vem se mostrando útil para estudo de novos biomarcadores. No presente estudo, foi analisado o banco de dados TCGA (514 pacientes) e Metabric (1898 pacientes) utilizando o software cBioportal. Foram analisados os dados de expressão gênica por RNA-Seq e Microarray. RESULTADOS: Foi verificada alteração de expressão gênica do sindecam-4 entre os diferentes subtipos de tumores de mama. Pacientes com tumor triplo-negativo tiveram a expressão diminuída para sindecam-4 em ambos os bancos de dados. CONCLUSÃO: Foi verificado que sindecam-4 parece ser um potencial biomarcador em tumores de mama, a expressão diminuída de sindecam-4 parece estar relacionada a um pior prognóstico.

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OBJECTIVE: One of the techniques that has gained much attention is the in vitro maturation of oocytes for patients who use assisted reproduction techniques. However, its results are still inferior to controlled ovarian stimulation methodologies. Understanding the maturation mechanisms based on analyses can help improve this methodology's results. The work aims to identify the central genes differentially expressed in oocytes after in vitro maturation in the germinal vesicle and metaphase II stages. METHODS: This work is a computational analysis. The entire search will be conducted using the Gene Expression Omnibus (GEO) database. To carry out and obtain the data present in the work, an advanced research search was carried out in the GEO database within the period from January 1, 2013, to January 1, 2023. A total of 27 genomic data were available in the GEO database, of which only two were used. RESULTS: Two datasets were identified on the Gene Expression Omnibus database platform: registration data GSE158802 and GSE95477. From the analysis, we identified five downregulated and thirty-six upregulated genes; the central genes that correlated with the main gene proteins found were CLTA and PANK1. CONCLUSIONS: There was a differential regulation of gene expression. The most central ones are related to energy capture.

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Gastric cancer (GC) ranks fifth globally in cancer diagnoses and third for cancer-related deaths. Chemotherapy with 5-fluorouracil (5-FU), a primary treatment, faces challenges due to the development of chemoresistance. Tumor microenvironment factors, including C-C motif chemokine receptor 3 (CCR3), can contribute to chemoresistance. The present study evaluated the effect of CCR3 receptor inhibition using the antagonist SB 328437 and the molecular dynamics of this interaction on resistance to 5-FU in gastric cancer cells. The 5-FU-resistant AGS cell line (AGS R-5FU) demonstrated notable tolerance to higher concentrations of 5-FU, with a 2.6-fold increase compared with the parental AGS cell line. Furthermore, the mRNA expression levels of thymidylate synthase (TS), a molecular marker for 5-FU resistance, were significantly elevated in AGS R-5FU cells. CCR3 was shown to be expressed at significantly higher levels in these resistant cells. Combining SB 328437 with 5-FU resulted in a significant decrease in cell viability, particularly at higher concentrations of 5-FU. Furthermore, when SB 328437 was combined with 5-FU at a high concentration, the relative mRNA expression levels of CCR3 and TS decreased significantly. Computational analysis of CCR3 demonstrated dynamic conformational changes, especially in extracellular loop 2 region, which indicated potential alterations in ligand recognition. Docking simulations demonstrated that SB 328437 bound to the allosteric site of CCR3, inducing a conformational change in ECL2 and hindering ligand recognition. The present study provides comprehensive information on the molecular and structural aspects of 5-FU resistance and CCR3 modulation, highlighting the potential for therapeutic application of SB 328437 in GC treatment.

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Background: Hypersensitivity pneumonitis (HP) is an inflammatory disorder affecting lung parenchyma and often evolves into fibrosis (fHP). The altered regulation of genes involved in the pathogenesis of the disease is not well comprehended, while the role of microRNAs in lung fibroblasts remains unexplored. Methods: We used integrated bulk RNA-Seq and enrichment pathway bioinformatic analyses to identify differentially expressed (DE)-miRNAs and genes (DEGs) associated with HP lungs. In vitro, we evaluated the expression and potential role of miR-155-5p in the phenotype of fHP lung fibroblasts. Loss and gain assays were used to demonstrate the impact of miR-155-5p on fibroblast functions. In addition, mir-155-5p and its target TP53INP1 were analyzed after treatment with TGF-ß, IL-4, and IL-17A. Results: We found around 50 DEGs shared by several databases that differentiate HP from control and IPF lungs, constituting a unique HP lung transcriptional signature. Additionally, we reveal 18 DE-miRNAs that may regulate these DEGs. Among the candidates likely associated with HP pathogenesis was miR-155-5p. Our findings indicate that increased miR-155-5p in fHP fibroblasts coincides with reduced TP53INP1 expression, high proliferative capacity, and a lack of senescence markers compared to IPF fibroblasts. Induced overexpression of miR-155-5p in normal fibroblasts remarkably increases the proliferation rate and decreases TP53INP1 expression. Conversely, miR-155-5p inhibition reduces proliferation and increases senescence markers. TGF-ß, IL-4, and IL-17A stimulated miR-155-5p overexpression in HP lung fibroblasts. Conclusion: Our findings suggest a distinctive signature of 53 DEGs in HP, including CLDN18, EEF2, CXCL9, PLA2G2D, and ZNF683, as potential targets for future studies. Likewise, 18 miRNAs, including miR-155-5p, could be helpful to establish differences between these two pathologies. The overexpression of miR-155-5p and downregulation of TP53INP1 in fHP lung fibroblasts may be involved in his proliferative and profibrotic phenotype. These findings may help differentiate and characterize their pathogenic features and understand their role in the disease.

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OBJECTIVE: The present study combined transcriptomic data and computational techniques based on gene expression signatures to identify novel bioactive compounds or FDA-approved drugs for the management of Bipolar Disorder (BD). METHODS: Five transcriptomic datasets, comprising a total of 165 blood samples from BD case-control, were selected from the Gene Expression Omnibus repository (GEO). The number of subjects varied from 6 to 60, with a mean age ranging from 35 to 48, with a gender variation between them. Most of the patients were on pharmacological treatment. Master Regulator Analysis (MRA) and Gene Set Enrichment Analysis (GSEA) were performed to identify statistically significant genes between BD and HC and their association with the mood states of BD. Additionally, existing molecules with the potential to reverse the transcriptomic profiles of disease-altered regulons in BD were identified using the LINCS and cMap databases. RESULTS: MRA identified 59 potential MRs candidates modulating the regulatory units enriched with genes altered in BD, while the GSEA identified 134 enriched genes, and a total of 982 regulons had their activation state determined. Both analyses showed genes exclusively associated with mania, depression, or euthymia, and some genes were common between the three mood states. We identified bioactive compounds and licensed drug candidates, including antihypertensives and antineoplastics, as promising candidates for treating BD. Nevertheless, experimental validation is essential to authenticate these findings in subsequent studies. CONCLUSION: Although preliminary, our data provides some insights regarding the biological patterns of BD into distinct mood states and potential therapeutic targets. The combined transcriptomic and bioinformatics strategy offers a route to advance drug discovery and personalized medicine by tapping into gene expression information.

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Antimicrobial peptides (AMPs) are promising cationic and amphipathic molecules to fight antibiotic resistance. To search for novel AMPs, we applied a computational strategy to identify peptide sequences within the organisms' proteome, including in-house developed software and artificial intelligence tools. After analyzing 150.450 proteins from eight proteomes of bacteria, plants, a protist, and a nematode, nine peptides were selected and modified to increase their antimicrobial potential. The 18 resulting peptides were validated by bioassays with four pathogenic bacterial species, one yeast species, and two cancer cell-lines. Fourteen of the 18 tested peptides were antimicrobial, with minimum inhibitory concentrations (MICs) values under 10 µM against at least three bacterial species; seven were active against Candida albicans with MICs values under 10 µM; six had a therapeutic index above 20; two peptides were active against A549 cells, and eight were active against MCF-7 cells under 30 µM. This study's most active antimicrobial peptides damage the bacterial cell membrane, including grooves, dents, membrane wrinkling, cell destruction, and leakage of cytoplasmic material. The results confirm that the proposed approach, which uses bioinformatic tools and rational modifications, is highly efficient and allows the discovery, with high accuracy, of potent AMPs encrypted in proteins.

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BACKGROUND AND OBJECTIVES: Changes in RHD generate variations in protein structure that lead to antigenic variants. The classical model divides them into quantitative (weak and Del) and qualitative (partial D). There are two types of protein antigens: linear and conformational. Computational biology analyses the theoretical assembly of tertiary protein structures and allows us to identify the 'topological' differences between isoforms. Our aim was to determine the theoretical antigenic differences between weak RhD variants compared with normal RhD based on structural analysis using bioinformatic techniques. MATERIALS AND METHODS: We analysed the variations in secondary structures and hydrophobicity of RHD*01, RHD*01W.1, W2, W3, RHD*09.03.01, RHD*09.04, RHD*11, RHD*15 and RHD*21. We then modelled the tertiary structure and calculated their probable antigenic regions, intra-protein interactions, displacement and membrane width and compared them with Rhce. RESULTS: The 10 proteins are similar in their secondary structure and hydrophobicity, with the main differences observed in the exofacial coils. We identified six potential antigenic regions: one that is unique to RhD (R3), one that is common to all D (R6), three that are highly variable among RhD isoforms (R1, R2 and R4), one that they share with Rhce (R5) and two that are unique to Rhce (Ra and Rbc). CONCLUSION: The alloimmunization capacity of these subjects could be explained by the variability of the antigen pattern, which is not necessarily recognized or recognized with lower intensity by the commercially available antibodies, and not because they have a lower protein concentration in the membrane.

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Parkinson's disease (PD) is among the most prevalent neurodegenerative disorders, affecting over 10 million people worldwide. The protein encoded by the SNCA gene, alpha-synuclein (ASYN), is the major component of Lewy body (LB) aggregates, a histopathological hallmark of PD. Mutations and posttranslational modifications (PTMs) in ASYN are known to influence protein aggregation and LB formation, possibly playing a crucial role in PD pathogenesis. In this work, we applied computational methods to characterize the effects of missense mutations and PTMs on the structure and function of ASYN. Missense mutations in ASYN were compiled from the literature/databases and underwent a comprehensive predictive analysis. Phosphorylation and SUMOylation sites of ASYN were retrieved from databases and predicted by algorithms. ConSurf was used to estimate the evolutionary conservation of ASYN amino acids. Molecular dynamics (MD) simulations of ASYN wild-type and variants A30G, A30P, A53T, and G51D were performed using the GROMACS package. Seventy-seven missense mutations in ASYN were compiled. Although most mutations were not predicted to affect ASYN stability, aggregation propensity, amyloid formation, and chaperone binding, the analyzed mutations received relatively high rates of deleterious predictions and predominantly occurred at evolutionarily conserved sites within the protein. Moreover, our predictive analyses suggested that the following mutations may be possibly harmful to ASYN and, consequently, potential targets for future investigation: K6N, T22I, K34E, G36R, G36S, V37F, L38P, G41D, and K102E. The MD analyses pointed to remarkable flexibility and essential dynamics alterations at nearly all domains of the studied variants, which could lead to impaired contact between NAC and the C-terminal domain triggering protein aggregation. These alterations may have functional implications for ASYN and provide important insight into the molecular mechanism of PD, supporting the design of future biomedical research and improvements in existing therapies for the disease.

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Multiple drug-resistant fungal species are associated with the development of diseases. Thus, more efcient drugs for the treatment of these aetiological agents are needed. Rondonin is a peptide isolated from the haemolymph of the spider Acanthoscurria rondoniae. Previous studies have shown that this peptide has antifungal activity against Candida sp. and Trichosporon sp. strains, acting on their genetic material. However, the molecular targets involved in its biological activity have not yet been described. Bioinformatics tools were used to determine the possible targets involved in the biological activity of Rondonin. The PharmMapper server was used to search for microorganismal targets of Rondonin. The PatchDock server was used to perform the molecular docking. UCSF Chimera software was used to evaluate these intermolecular interactions. In addition, the I-TASSER server was used to predict the target ligand sites. Then, these predictions were contrasted with the sites previously described in the literature. Molecular dynamics simulations were conducted for two promising complexes identifed from the docking analysis. Rondonin demonstrated consistency with the ligand sites of the following targets: outer membrane proteins F (id: 1MPF) and A (id: 1QJP), which are responsible for facilitating the passage of small molecules through the plasma membrane; the subunit of the favoprotein fumarate reductase (id: 1D4E), which is involved in the metabolism of nitrogenous bases; and the ATP-dependent Holliday DNA helicase junction (id: 1IN4), which is associated with histone proteins that package genetic material. Additionally, the molecular dynamics results indicated the stability of the interaction of Rondonin with 1MPF and 1IN4 during a 10 ns simulation. These interactions corroborate with previous in vitro studies on Rondonin, which acts on fungal genetic material without causing plasma membrane rupture. Therefore, the bioprospecting methods used in this research were considered satisfactory since they were consistent with previous results obtained via in vitro experimentation.

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The emergence of antibiotic-resistant pathogens generates impairment to human health. U1-SCTRX-lg1a is a peptide isolated from a phospholipase D extracted from the spider venom of Loxosceles gaucho with antimicrobial activity against Gram-negative bacteria (between 1.15 and 4.6 μM). The aim of this study was to suggest potential receptors associated with the antimicrobial activity of U1-SCTRX-lg1a using in silico bioinformatics tools. The search for potential targets of U1-SCRTX-lg1a was performed using the PharmMapper server. Molecular docking between U1-SCRTX-lg1a and the receptor was performed using PatchDock software. The prediction of ligand sites for each receptor was conducted using the PDBSum server. Chimera 1.6 software was used to perform molecular dynamics simulations only for the best dock score receptor. In addition, U1-SCRTX-lg1a and native ligand interactions were compared using AutoDock Vina software. Finally, predicted interactions were compared with the ligand site previously described in the literature. The bioprospecting of U1-SCRTX-lg1a resulted in the identification of three hundred (300) diverse targets (Table S1), forty-nine (49) of which were intracellular proteins originating from Gram-negative microorganisms (Table S2). Docking results indicate Scores (10,702 to 6066), Areas (1498.70 to 728.40) and ACEs (417.90 to – 152.8) values. Among these, NAD + NH3-dependent synthetase (PDB ID: 1wxi) showed a dock score of 9742, area of 1223.6 and ACE of 38.38 in addition to presenting a Normalized Fit score of 8812 on PharmMapper server. Analysis of the interaction of ligands and receptors suggests that the peptide derived from brown spider venom can interact with residues SER48 and THR160. Furthermore, the C terminus (– 7.0 score) has greater affinity for the receptor than the N terminus (– 7.7 score). The molecular dynamics assay shown that free energy value for the protein complex of – 214,890.21 kJ/mol, whereas with rigid docking, this value was – 29.952.8 sugerindo that after the molecular dynamics simulation, the complex exhibits a more favorable energy value compared to the previous state. The in silico bioprospecting of receptors suggests that U1-SCRTX-lg1a may interfere with NAD + production in Escherichia coli, a Gram-negative bacterium, altering the homeostasis of the microorganism and impairing growth.

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Resumo Fundamento O infarto do miocárdio com elevação do segmento ST (IAMCSST) é uma das principais causas de doenças cardiovasculares fatais, que têm sido a principal causa de mortalidade em todo o mundo. O diagnóstico na fase inicial beneficiaria a intervenção clínica e o prognóstico, mas ainda falta a exploração dos biomarcadores do IAMCSST. Objetivos Neste estudo, conduzimos uma análise bioinformática para identificar potenciais biomarcadores cruciais no progresso do IAMCSST. Métodos Obtivemos GSE59867 para pacientes com IAMCSST e doença arterial coronariana estável (DACE). Genes diferencialmente expressos (GDEs) foram selecionados com o limiar de -log2fold change- > 0,5 e p < 0,05. Com base nesses genes, conduzimos análises de enriquecimento para explorar a relevância potencial entre genes e para rastrear genes centrais. Posteriormente, os genes centrais foram analisados para detectar miRNAs relacionados e DAVID para detectar fatores de transcrição para análise posterior. Finalmente, o GSE62646 foi utilizado para avaliar a especificidade dos GDEs, com genes demonstrando resultados de AUC superiores a 75%, indicando seu potencial como candidatos a biomarcadores. Posteriormente, os genes centrais foram analisados para detectar miRNAs relacionados e DAVID para detectar fatores de transcrição para análise posterior. Finalmente, o GSE62646 foi utilizado para avaliar a especificidade dos GDEs, com genes demonstrando resultados de AUC superiores a 75%, indicando seu potencial como candidatos a biomarcadores. Resultados 133 GDEs entre DACE e IAMCSST foram obtidos. Em seguida, a rede PPI de GDEs foi construída usando String e Cytoscape, e análises posteriores determinaram genes centrais e 6 complexos moleculares. A análise de enriquecimento funcional dos GDEs sugere que as vias relacionadas à inflamação, metabolismo e imunidade desempenham um papel fundamental na progressão de DACE para IAMCSST. Além disso, foram previstos miRNAs relacionados, has-miR-124, has-miR-130a/b e has-miR-301a/b regularam a expressão do maior número de genes. Enquanto isso, a análise dos fatores de transcrição indica que EVI1, AML1, GATA1 e PPARG são os genes mais enriquecidos. Finalmente, as curvas ROC demonstram que MS4A3, KLRC4, KLRD1, AQP9 e CD14 exibem alta sensibilidade e especificidade na previsão de IAMCSST. Conclusões Este estudo revelou que imunidade, metabolismo e inflamação estão envolvidos no desenvolvimento de IAMCSST derivado de DACE, e 6 genes, incluindo MS4A3, KLRC4, KLRD1, AQP9, CD14 e CCR1, poderiam ser empregados como candidatos a biomarcadores para IAMCSST.

Abstract Background ST-segment elevation myocardial infarction (STEMI) is one of the leading causes of fatal cardiovascular diseases, which have been the prime cause of mortality worldwide. Diagnosis in the early phase would benefit clinical intervention and prognosis, but the exploration of the biomarkers of STEMI is still lacking. Objectives In this study, we conducted a bioinformatics analysis to identify potential crucial biomarkers in the progress of STEMI. Methods We obtained GSE59867 for STEMI and stable coronary artery disease (SCAD) patients. Differentially expressed genes (DEGs) were screened with the threshold of -log2fold change- > 0.5 and p <0.05. Based on these genes, we conducted enrichment analysis to explore the potential relevance between genes and to screen hub genes. Subsequently, hub genes were analyzed to detect related miRNAs and DAVID to detect transcription factors for further analysis. Finally, GSE62646 was utilized to assess DEGs specificity, with genes demonstrating AUC results exceeding 75%, indicating their potential as candidate biomarkers. Results 133 DEGs between SCAD and STEMI were obtained. Then, the PPI network of DEGs was constructed using String and Cytoscape, and further analysis determined hub genes and 6 molecular complexes. Functional enrichment analysis of the DEGs suggests that pathways related to inflammation, metabolism, and immunity play a pivotal role in the progression from SCAD to STEMI. Besides, related-miRNAs were predicted, has-miR-124, has-miR-130a/b, and has-miR-301a/b regulated the expression of the largest number of genes. Meanwhile, Transcription factors analysis indicate that EVI1, AML1, GATA1, and PPARG are the most enriched gene. Finally, ROC curves demonstrate that MS4A3, KLRC4, KLRD1, AQP9, and CD14 exhibit both high sensitivity and specificity in predicting STEMI. Conclusions This study revealed that immunity, metabolism, and inflammation are involved in the development of STEMI derived from SCAD, and 6 genes, including MS4A3, KLRC4, KLRD1, AQP9, CD14, and CCR1, could be employed as candidate biomarkers to STEMI.

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La ivermectina demostró importantes acciones antivirales ante varios virus con genoma de ARN, inclusive contra el SARS-CoV-2. Este fármaco inhibe la actividad del heterodímero importina α/ß1, sin embargo, se desconoce los blancos específicos de interacción de la molécula. Objetivos: analizar in silico los blancos de interacción de la ivermectina en interacción con la estructura de la importina α humana, utilizando la estrategia del acoplamiento molecular. Métodos: se realizaron simulaciones del acoplamiento utilizando un modelo semiflexible y el algoritmo Broyden-Fletcher-Goldfarb-Shanno entre las estructuras de ivermectina y la importina α. Resultados: los datos obtenidos revelan una mayor afinidad de interacción de la ivermectina a la región mayor de unión (armadillo ARM2-ARM4) de las importinas α humanas, con energías de unión favorables de -9,5 a -8,0 kcal.mol-1. Los aminoácidos activos de importancia en las uniones fueron el Triptófano, Asparagina y Arginina, los cuales también son fundamentales para el reconocimiento de secuencias NLS (secuencias de localización nuclear) de las proteínas virales. También se registró afinidades por los dominios H1-ARM5, H2-ARM6 y H2-ARM7, con energía de unión de -7,5 kcal.mol-1. Conclusiones: los hallazgos demuestran que la ivermectina presenta afinidades de unión favorables a la región mayor de unión (ARM2-ARM4) de las importinas a el cual es un sitio importante de unión a proteínas virales.

Ivermectin has demonstrated significant antiviral actions against several RNA-genome viruses, including SARS-CoV-2. This drug inhibits the activity of the α/ß1 importin heterodimer; however, the specific interaction targets of the molecule are unknown yet. Objectives: to analyze in silico the interaction targets of ivermectin interacting with the human α-importin structure using the molecular docking strategy. Methods: simulations of the molecular docking were carried out using a semi-flexible model and the Broyden-Fletcher-Goldfarb- Shanno algorithm between the structures of ivermectin and importin α. Results: data obtained reveal a higher interaction affinity of ivermectin to the major binding region (armadillo ARM2-ARM4) of human importins α, with favorable binding energies of -9,5 to -8,0 kcal.mol-1. The active amino acids of importance in the bindings were Tryptophan, Asparagine and Arginine, which are also critical for the recognition of NLS sequences (nuclear location sequences) of viral proteins. Affinities for H1-ARM5, H2-ARM6 and H2-ARM7 domains were also recorded, with binding energy of -7,5 kcal.mol-1. Conclusions: the findings demonstrate that ivermectin exhibits favorable binding affinities to the major binding region (ARM2-ARM4) of importins a which is an important viral protein binding site.

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Cardiovascular diseases (CVDs) are the leading cause of death worldwide and are heavily influenced by genetic factors. Genome-wide association studies have mapped >90% of CVD-associated variants within the noncoding genome, which can alter the function of regulatory proteins, such as transcription factors (TFs). However, due to the overwhelming number of single-nucleotide polymorphisms (SNPs) (>500,000) in genome-wide association studies, prioritizing variants for in vitro analysis remains challenging. In this work, we implemented a computational approach that considers support vector machine (SVM)-based TF binding site classification and cardiac expression quantitative trait loci (eQTL) analysis to identify and prioritize potential CVD-causing SNPs. We identified 1535 CVD-associated SNPs within TF footprints and putative cardiac enhancers plus 14,218 variants in linkage disequilibrium with genotype-dependent gene expression in cardiac tissues. Using ChIP-seq data from two cardiac TFs (NKX2-5 and TBX5) in human-induced pluripotent stem cell-derived cardiomyocytes, we trained a large-scale gapped k-mer SVM model to identify CVD-associated SNPs that altered NKX2-5 and TBX5 binding. The model was tested by scoring human heart TF genomic footprints within putative enhancers and measuring in vitro binding through electrophoretic mobility shift assay. Five variants predicted to alter NKX2-5 (rs59310144, rs6715570, and rs61872084) and TBX5 (rs7612445 and rs7790964) binding were prioritized for in vitro validation based on the magnitude of the predicted change in binding and are in cardiac tissue eQTLs. All five variants altered NKX2-5 and TBX5 DNA binding. We present a bioinformatic approach that considers tissue-specific eQTL analysis and SVM-based TF binding site classification to prioritize CVD-associated variants for in vitro analysis.

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This article explores the progressive integration of -omics methods, including genomics, metabolomics, and proteomics, into sports research, highlighting the development of the concept of "sportomics." We discuss how sportomics can be used to comprehend the multilevel metabolism during exercise in real-life conditions faced by athletes, enabling potential personalized interventions to improve performance and recovery and reduce injuries, all with a minimally invasive approach and reduced time. Sportomics may also support highly personalized investigations, including the implementation of n-of-1 clinical trials and the curation of extensive datasets through long-term follow-up of athletes, enabling tailored interventions for athletes based on their unique physiological responses to different conditions. Beyond its immediate sport-related applications, we delve into the potential of utilizing the sportomics approach to translate Big Data regarding top-level athletes into studying different human diseases, especially with nontargeted analysis. Furthermore, we present how the amalgamation of bioinformatics, artificial intelligence, and integrative computational analysis aids in investigating biochemical pathways, and facilitates the search for various biomarkers. We also highlight how sportomics can offer relevant information about doping control analysis. Overall, sportomics offers a comprehensive approach providing novel insights into human metabolism during metabolic stress, leveraging cutting-edge systems science techniques and technologies.

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The current sweeteners available are very efficient in providing sweet taste. However, they are associated with several chronic diseases. Some glycoproteins, such as miraculins, are extremely interesting from a biotechnological point of view because they perform the bitter into sweet taste modifying function excellently, in addition to being safer as food. In contrast, purifying and synthesizing these proteins represents a major challenge for the food industry, as these proteins are large and complex molecules, which would make the final product expensive and economically unviable. In this context, emerging techniques from computational biology and molecular modelling have been promoting a remarkable revolution in protein bioengineering. Bioinspired peptides can provide many possibilities in sweeteners development through rational design. Once these peptides are smaller molecules than an entire protein, its synthesis on a large scale tends to be much easier and more economical, besides presenting a potential for better bioavailability in the organism. The techniques discussed here allow, through sophisticated pipelines and algorithms, to perform the rational design of mimetic peptides and with smaller size, which can carry out the activation of sweet taste of miraculins and to be more viable for industrial production. In this review, the premises and tools for the elaboration of synthetic peptides bioinspired in proteins with sweetening activity that mimic this action will be emphasized.Communicated by Ramaswamy H. Sarma.

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Heterogeneity plays an important role in diversifying neural responses to support brain function. Adult neurogenesis provides the dentate gyrus with a heterogeneous population of granule cells (GCs) that were born and developed their properties at different times. Immature GCs have distinct intrinsic and synaptic properties than mature GCs and are needed for correct encoding and discrimination in spatial tasks. How immature GCs enhance the encoding of information to support these functions is not well understood. Here, we record the responses to fluctuating current injections of GCs of different ages in mouse hippocampal slices to study how they encode stimuli. Immature GCs produce unreliable responses compared to mature GCs, exhibiting imprecise spike timings across repeated stimulation. We use a statistical model to describe the stimulus-response transformation performed by GCs of different ages. We fit this model to the data and obtain parameters that capture GCs' encoding properties. Parameter values from this fit reflect the maturational differences of the population and indicate that immature GCs perform a differential encoding of stimuli. To study how this age heterogeneity influences encoding by a population, we perform stimulus decoding using populations that contain GCs of different ages. We find that, despite their individual unreliability, immature GCs enhance the fidelity of the signal encoded by the population and improve the discrimination of similar time-dependent stimuli. Thus, the observed heterogeneity confers the population with enhanced encoding capabilities.

Assuntos

RESUMO

Mayaro (MAYV), Saint Louis encephalitis (SLEV), and Oropouche (OROV) viruses are neglected members of the three main families of arboviruses with medical relevance that circulate in the Amazon region as etiological agents of outbreaks of febrile illnesses in humans. As enveloped viruses, MAYV, SLEV, and OROV largely depend on their class II fusion proteins (E1, E, and Gc, respectively) for entry into the host cell. Since many aspects of the structural biology of such proteins remain unclear, the present study aimed at physicochemically characterizing them by an in silico approach. The complete amino acid sequences of MAYV E1, SLEV E, and OROV Gc proteins derived by conceptual translation from annotated coding regions in the reference sequence genome of the respective viruses were obtained from the NCBI Protein database in the FASTA format and then submitted to the ClustalO, Protcalc, Pepstats, Predator, Proscan, PCprof, Phyre2, and 3Drefine web servers for the determination of sequence identities, the estimation of residual properties, the prediction of secondary structures, the identification of potential post-translational modifications, the recognition of antigenic propensities, and the modeling/refinement of three-dimensional structures. Sequence identities were 20.44%, 18.82%, and 13.70% between MAYV/SLEV, SLEV/OROV, and MAYV/OROV fusion proteins, respectively. As for the residual properties, MAYV E1 and SLEV E proteins showed a predominance of the non-polar profile (56% and 55% of the residues, respectively), whereas the OROV Gc protein showed a predominance of the polar profile (52% of the residues). Regarding predicted secondary structures, MAYV E1 and SLEV E proteins showed fewer alpha-helices (16.51% and 15.17%, respectively) than beta-sheets (21.79% and 25.15%, respectively), while the opposite was observed in the OROV Gc protein (20.39% alpha-helices and 12.14% beta-sheets). Regarding post-translational modifications, MAYV E1, SLEV E, and OROV Gc proteins showed greater relative potential for protein kinase C phosphorylation, N-myristoylation, and casein kinase II phosphorylation, respectively. Finally, antigenic propensities were higher in the N-terminus half than in the C-terminus half of these three proteins, whose three-dimensional structures revealed three distinctive domains. In conclusion, MAYV E1 and SLEV E proteins were found to share more physicochemical characteristics with each other than the OROV Gc protein, although they are all grouped under the same class of viral fusion proteins.