Protein and Peptide Letters最新文献

Background: There have been great efforts in vaccine design against HIV-1 since 1981. Various approaches have been investigated, including optimized delivery systems and effective adjuvants to enhance the efficacy of selective antigen targets. In this study, we evaluated the efficiency of IMT-P8 and LDP12 cell penetrating peptides in eliciting immune responses against HIV-1 Nef-MPER-V3 fusion protein as an antigen candidate. Moreover, the potency of HP91 and HSP27 was compared as an adjuvant in female BALB/c mice through different regimens.

Methods: For this purpose, the recombinant Nef-MPER-V3, IMT-P8-Nef-MPER-V3 and LDP-Nef- MPER-V3 proteins were generated on a large scale. After mice immunization with different regimens, the secretion of antibodies, cytokines and granzyme B was evaluated by ELISA.

Results: Our results demonstrated that immunized mice receiving the Nef-MPER-V3 linked to IMT-P8 exhibited significantly higher levels of IgG compared to other groups. The IMT-P8-Nef- MPER-V3 with the Hp91 group showed the highest level of humoral response, which was significantly stronger than the LDP12 formulation using the same antigen (LDP-Nef-MPER-V3). Additionally, the combination of IMT-P8-Nef-MPER-V3 with either Hp91 or Hsp27 resulted in robust induction of IFN-γ compared to the LDP-Nef-MPER-V3 group. Furthermore, cytotoxic T lymphocyte (CTL) activation and proliferation assays indicated that IMT-P8 served as a more effective CPP, particularly when used in conjunction with the Hp91 adjuvant Conclusion: Altogether, the data indicated that Nef-MPER-V3 antigen in different formulations was effective in eliciting immune responses. This fusion protein has the high potency to induce both immunity arms, specifically when incorporated with IMT-P8, which showed priority to LDP12. Moreover, HP91 resulted in a greater humoral and cellular immune activation compared to HSP27. These findings suggest the potential of IMT-P8 as a superior delivery system for enhancing immune responses in vaccine development.

Background: Aloperine (ALO) is an important active ingredient in the traditional Chinese medicinal plant Sophora alopecuroides L and has a significant autophagy-stimulating effect. The effect of ALO on cytotoxicity caused by UVB radiation in skin fibroblasts and the potential mechanism remains unclear.

Objective: The present study aimed to assess the effect of ALO on UVB-induced damage in skin fibroblasts and investigate its possible mechanism.

Methods: Cell viability, cytotoxicity, caspase-Glo 3/7 activity, apoptosis, and protein expression were measured in UVB-treated skin fibroblasts in the presence or absence of ALO. Autophagy inhibitors (chloroquine and bafilomycin A1) and TFE3 siRNA transfection were used to elucidate the potential mechanisms further.

Results: These data demonstrate that ALO attenuated cell viability inhibition, apoptosis, cytotoxicity, and alterations in autophagy-related proteins caused by UVB exposure in skin fibroblasts. ALO stimulates autophagy activation and TFE3 nuclear localization in UVB-treated skin fibroblasts. Furthermore, treatment with autophagy inhibitors and TFE3 siRNA reversed the effects of ALO on UVB-treated skin fibroblasts.

Conclusion: These results suggest that ALO protects skin fibroblasts against UVB-induced cytotoxicity by stimulating TFE3/Beclin-1-mediated autophagy.

Despite significant research efforts, Alzheimer's disease (AD), the primary cause of dementia in older adults worldwide, remains a neurological challenge for which there are currently no effective therapies. There are substantial financial, medical, and personal costs associated with this condition.Important pathological features of AD include hyperphosphorylated microtubule-associated protein Tau, the formation of amyloid β (Aβ) peptides from amyloid precursor protein (APP), and continuous inflammation that ultimately results in neuronal death. Important histological markers of AD, amyloid plaques, and neurofibrillary tangles are created when Aβ and hyperphosphorylated Tau build-up. Nevertheless, a thorough knowledge of the molecular players in AD pathophysiology is still elusive. Recent studies have shown how noncoding RNAs (ncRNAs), including microRNAs (miRNAs), long noncoding RNAs (lncRNAs), and circular RNAs (circRNAs), regulate gene expression at the transcriptional and posttranscriptional levels in a variety of diseases, including AD. There is increasing evidence to support the involvement of these ncRNAs in the genesis and progression of AD, making them promising as biomarkers and therapeutic targets. As a result, therapeutic approaches that target regulatory ncRNAs are becoming more popular as potential means of preventing the progression of AD. This review explores the posttranscriptional relationships between ncRNAs and the main AD pathways, highlighting the potential of ncRNAs to advance AD treatment. In AD, ncRNAs, especially miRNAs, change expression and present potential targets for therapy. MiR-346 raises Aβ through APP messenger Ribonucleic Acid (mRNA), whereas miR-107 may decrease Aβ by targeting beta-site amyloid precursor protein cleaving enzyme 1 (BACE1). They are promising early AD biomarkers due to their stability in cerebrospinal fluid (CSF) and blood. Furthermore, additional research is necessary to determine the role that RNA fragments present in AD-related protein deposits play in AD pathogenesis.

Cancer is a deadly disease that has claimed millions of lives worldwide. Traditional cancer treatments, such as chemotherapy and radiation, have been used for many years but have become less favored due to drug resistance, lack of tumor selectivity, high costs, and various side effects, such as fatigue and hair loss. Many studies have reported that animal venoms, such as those from snakes, scorpions, and bees, contain bioactive peptides that can be synthesized into anti-- cancer peptides (ACPs), which offer a potential alternative to traditional cancer therapies. Apitherapy is an area of growing interest for the development of new cancer treatments using bee venom, which is a complex mixture of biologically active peptides, enzymes, bioactive amines, and nonpeptide components that have been found to have anti-cancer properties. By leveraging these bioactive peptides, researchers could develop ACPs that are more targeted towards cancer cells, reducing the risk of adverse side effects and improving patient outcomes. The use of bee venom components in targeting cancer could provide a more selective, effective, and affordable approach to cancer therapy. While further research is needed, the potential benefits of using bee venom components in cancer therapy are significant and could help improve the lives of cancer patients worldwide. This study aims to review the components of bee venom as potential cancer treatments.

Amidst the rising global burden of neurodegenerative diseases, such as Alzheimer's and Parkinson's diseases, there is an urgent need for novel therapeutic strategies to combat these debilitating conditions. These diseases are characterized by progressive neural dysfunction leading to cognitive impairments, for which current therapeutic strategies remain palliative at best. Recently, the discovery of ferroptosis, a novel cell death mode that is different from apoptosis and autophagy, has opened new avenues in the field of cognitive research. With in-depth research on ferroptosis, the clinical significance of iron homeostasis disorders and lipid peroxidation in the occurrence, development, and treatment of neurodegenerative diseases are gradually becoming apparent. This study aims to elucidate the roles of ferroptosis in the context of neurodegeneration and to explore its potential as a therapeutic target. By unraveling the intricate relationship between iron homeostasis disorders, oxidative damage, and lipid metabolism disturbances in these diseases, new intervention targets are revealed. It offers a new dimension to the management of neurocognitive impairments in Alzheimer's and Parkinson's diseases. The implications of these findings extend beyond just Alzheimer's and Parkinson's diseases. They also have relevance with other neurological conditions characterized by oxidative stress and iron dysregulation. This review contributes to increased knowledge of ferroptosis and provides a foundational understanding that could lead to the development of innovative therapeutic strategies. Ultimately, it may alleviate the development of neurodegenerative diseases and improve cognitive function by preventing ferroptosis, which has not only academic significance but also potential clinical significance.

Immunoproteomics is the branch of proteomics with an emphasis on the study of functional peptides and proteins related to the immune system. Combining proteomics techniques with immunological research aims to uncover the complex interactions of proteins involved in immune responses. This review discusses the methods, applications, and recent advancements in immunoproteomics, highlighting its critical role in understanding immune responses, discovering biomarkers, and developing vaccines and therapeutics. This study offers a comprehensive exploration of the methodologies, applications, and advancements within immunoproteomics. Techniques such as mass spectrometry, antibody-based assays, and computational analysis are pivotal in unraveling the complexities of the immune system at the protein level. Immunoproteomics finds diverse applications in biomarker discovery, vaccine development, autoimmune disease research, infectious disease diagnostics, and cancer immunotherapy. Challenges, including data integration, sample heterogeneity, and biomarker validation, persist, necessitating innovative approaches and interdisciplinary collaborations. In the future, immunoproteomics will likely play a major role in expanding our knowledge of immune-related diseases and accelerating the creation of targeted and precise immunotherapies.

Background: The abnormal expression of small G protein signaling modulator 2 (SGSM2) is related to the occurrence of thyroid cancer and breast cancer. However, the role of SGSM2 in uveal melanoma (UVM) is unclear.

Objects: To elucidate this ambiguity, our study utilized bioinformatics analysis and experimental validation.

Methods: The expression of SGSM2 was detected in UVM cell lines through quantitative real-- time PCR (qRT-PCR). We utilized the Cancer Genome Atlas (TCGA) database to assess the relationship between SGSM2 expression and clinical characteristics, as well as its prognostic significance in UVM. Furthermore, the study examined potential regulatory networks involving SGSM2 in relation to immune infiltration, immune checkpoint genes, microsatellite instability (MSI), and drug sensitivity in UVM. The study also examined SGSM2 expression in UVM single-cell sequencing data.

Results: SGSM2 was highly expressed in UVM cell lines. Moreover, elevated levels of SGSM2 in UVM patients were significantly linked to poorer overall survival (OS) (p < 0.001), progress- free survival (PFS) (p < 0.001), and disease-specific survival (DSS) (p < 0.001). Additionally, SGSM2 expression was identified as an independent prognostic factor in UVM patients (p < 0.001). SGSM2 was associated with several pathways, including the calcium signaling pathway, natural killer cell-mediated cytotoxicity, cell adhesion molecules (CAMs), and others. The study revealed that SGSM2 expression in UVM is linked to immune infiltration, immune checkpoint genes, and MSI. Additionally, a significant inverse correlation was observed between SGSM2 expression and the compounds GSK690693, TL-2-105, PHA-793887, Tubastatin A, and SB52334 in UVM patients.

Conclusion: SGSM2 may not only serve as an important indicator for prognostic assessment. Still, it may also be a key target for the development of new therapeutic approaches, providing new perspectives on the treatment of UVM patients.

Objective: This study aimed to identify novel proteins involved in retinoic acid (RA)-induced embryonic cleft palate development.

Method: The palate tissues of the control and RA-treated E14.5 were dissected and subjected to iTRAQ-based proteomic analysis.

Results: Differential expression analysis identified 196 significantly upregulated and 149 downregulated considerably proteins in RA-induced palate tissues. Comprehensive Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis revealed the significant involvement of cytoplasmic translation, ribosome biogenesis, glycolysis/gluconeogenesis, and glutathione metabolism pathways in cleft palate pathogenesis triggered by RA. In particular, ribosome-related pathways were highly enriched, while glycolysis was disrupted. Protein-protein interaction analysis, facilitated by the STRING database, revealed a tightly interconnected network of differentially expressed proteins. Further analysis using the cytoHubba plugin in Cytoscape identified ten hub proteins, including Eif4a1, Gapdh, Eno1, Imp3, Rps20, Rps27a, Eef2, Hsp90ab1, Rpl19, and Rps16, indicating their potential roles in RA-induced cleft palate development, and thus positioning them as potential biomarkers for cleft palate.

Conclusion: These findings provide valuable insights into the proteomic changes associated with RA-induced cleft palate and shed light on key pathways and proteins that can contribute significantly to the pathogenesis of this congenital condition.

The study of large protein sets (proteomics) involved in the immunological reaction is known as immunoproteomics. The methodology of immunoproteomics plays a major role in identifying possible vaccine candidates that could protect against pathogenic infection. The study of immunogenic proteins that are expressed during the outset of infection is the focus of the crosstalk between proteomics and immune protection antigens utilizing serum. Peptide presentation by MHC provides the new 'window' into changes that occur in the cell. Thus, there is strong, intense pressure on the pathogen that has been mutated in such an unusual manner that it can bypass the MHC peptide presentation by the MHC molecule. The pathogen's ability to evade the immune system is strongly restricted by the two unique distinct properties of MHC molecules, i.e., polygenic and polymorphic properties. MHC-I restriction epitope identification has traditionally been accomplished using genetic motif prediction. The study of immune system proteins and their interactions is the main emphasis of the specialist field of immunoproteomics within proteomics. Methodologies include mass spectrometry (MS), SRM assay, MALDI-TOF, Chromatography, ELISA, 2DG PAGE, and bioinformatics tools. Challenges are the complexity of the immune system, protein abundance and dynamics, sample variability, post-translational modifications (PTMs), and data integration. Current advancements are enhanced mass spectrometry techniques, single-cell proteomics, artificial intelligence and machine learning, advanced protein labeling techniques, integration with other omics technologies, and functional proteomics. However, the recently emerging field of immunoproteomics has more promising possibilities in the field of peptide-based vaccines and virus-like particle vaccines. The importance of immunoproteomics technologies and methodologies, as well as their use in the field of vaccinomics, are the main topics of this review. Here, we have discussed immunoproteomics in relation to a step towards the future of vaccination.

Several key functions of plants, such as photosynthesis, nutrient transport, disease resistance, and abiotic tolerance, are manifested by several classes of proteins. Prediction of 3- dimensional (3-D) structures of proteins and their working mechanisms can have a profound impact on plant proteomics research and could help improve key agricultural traits in crop plants. This review aims to present the current status of plant protein structure determination and discuss the way forward. Most experimentally proven protein structures are available only for the model plant Arabidopsis thaliana. Most of the key crop plants have only a few hundred or fewer experimentally proven 3-D structures. Fewer than 1% of the protein sequences in the majority of plants have had their 3D structures experimentally determined, and A. thaliana is the sole plant with the highest percentage of 1.4 % of protein sequences with experimentally determined structures. AI-based protein structure prediction tool AlphaFold has predicted models of several thousand proteins for many crop plants. In AlphaFold predicted protein models, soybean has the highest percentage (65%) of its UniProt protein sequences with predicted models, and a few other crop plants have also a considerable percentage of its UniProt sequences with AlphaFold predicted models. AlphaFold might help predict models and bridge the gap in plant structure determination studies. Protein structure information might lead to engineering key residues to improve the agronomical performance of crop plants.