Search Results (229)

Avian influenza A viruses (IAVs) pose a persistent threat to the poultry industry, causing substantial economic losses. Although traditional vaccines have helped reduce the disease burden, they typically rely on multivalent antigens, emphasize humoral immunity, and require intensive production. This study aimed to establish a genetically matched host–cell system to evaluate antigen-specific immune responses and identify conserved CD8+ T cell epitopes in avian influenza viruses. To this end, we developed an MHC class I genotype (B21)-matched host (Lohmann VALO SPF chicken) and cell vector (DF-1 cell line) model. DF-1 cells were engineered to express the hemagglutinin (HA) gene of clade 2.3.4.4b H5N1 either transiently or stably, and to stably express the matrix 1 (M1) and nucleoprotein (NP) genes of A/chicken/South Korea/SL20/2020 (H9N2, Y280-lineage). Following prime-boost immunization with HA-expressing DF-1 cells, only live cells induced strong hemagglutination inhibition (HI) and virus-neutralizing (VN) antibody titers in haplotype-matched chickens. Importantly, immunization with DF-1 cells transiently expressing NP induced stronger IFN-γ production than those expressing M1, demonstrating the platform’s potential for differentiating antigen-specific cellular responses. CD8+ T cell epitope mapping by mass spectrometry identified one distinct MHC class I-bound peptide from each of the HA-, M1-, and NP-expressing DF-1 cell lines. Notably, the identified HA epitope was conserved in 97.6% of H5-subtype IAVs, and the NP epitope in 98.5% of pan-subtype IAVs. These findings highlight the platform’s utility for antigen dissection and rational vaccine design. While limited by MHC compatibility, this approach enables identification of naturally presented epitopes and provides insight into conserved, functionally constrained viral targets. Full article

The glucagon-like peptide-1 receptor (GLP-1R), which belongs to the class B1 G protein-coupled receptor (GPCR) family, is an important target for treatment of metabolic disorders, including type 2 diabetes and obesity. The growing interest in GLP-1R-based therapies is driven by the development of various functional agonists as well as the huge commercial market. Thus, understanding the structural details of ligand-induced signaling are important for developing improved GLP-1R drugs. Here, we investigated the conformational dynamics of the receptor in complex with a selection of prototypical functional agonists, including CHU-128 (small molecule-biased), danuglipron (small molecule balanced), and Peptide 19 (peptide balanced), which exhibit unique, distinct binding modes and induced helix packing. Furthermore, our all-atom molecular dynamics (MD) simulations revealed atomic feature how different those ligands led to signaling pathway preference. Our findings offer valuable insights into the mechanistic principle of GLP-1R activation, which are helpful for the rational design of next-generation GLP-1R drug molecules. Full article

Background: Peptides are a class of molecules that can be presented as good antimicrobials and with mechanisms that avoid resistance, and the design of peptides with good activity can be complex and laborious. The study of their quantitative structure–activity relationships through machine learning algorithms can shed light on a rational and effective design. Methods: Information on the antimicrobial activity of peptides was collected, and their structures were characterized by molecular descriptors generation to design regression and classification models based on machine learning algorithms. The contribution of each descriptor in the generated models was evaluated by determining its relative importance and, finally, the antimicrobial activity of new peptides was estimated. Results: A structured database of antimicrobial peptides and their descriptors was obtained, with which 56 machine learning models were generated. Random Forest-based models showed better performance, and of these, regression models showed variable performance (R² = 0.339–0.574), while classification models showed good performance (MCC = 0.662–0.755 and ACC = 0.831–0.877). Those models based on bacterial groups showed better performance than those based on the entire dataset. The properties of the new peptides generated are related to important descriptors that encode physicochemical properties such as lower molecular weight, higher charge, propensity to form alpha-helical structures, lower hydrophobicity, and higher frequency of amino acids such as lysine and serine. Conclusions: Machine learning models allowed to establish the structure–activity relationships of antimicrobial peptides. Classification models performed better than regression models. These models allowed us to make predictions and new peptides with high antimicrobial potential were proposed. Full article

Antimicrobial resistance (AMR) has emerged as one of the most pressing global health challenges of our time. Alarming projections of increasing mortality from resistant infections highlight the urgent need for innovative solutions. While many candidates have shown promise in preliminary studies, they often encounter challenges in terms of efficacy and safety during clinical translation. This review examines cutting-edge approaches to combat AMR, with a focus on engineered antimicrobial peptides, functionalized nanoparticles, and advanced genomic therapies, including Clustered Regularly Interspaced Short Palindromic Repeats-associated proteins (CRISPR-Cas systems) and phage therapy. Recent advancements in these fields are critically analyzed, with a focus on their mechanisms of action, therapeutic potential, and current limitations. Emphasis is given to strategies targeting biofilm disruption and quorum sensing interference, which address key mechanisms of resistance. By synthesizing current knowledge, this work provides researchers with a comprehensive framework for developing next-generation antimicrobials, highlighting the most promising approaches for overcoming AMR through rational drug design and targeted therapies. Ultimately, this review aims to bridge the gap between experimental innovation and clinical application, providing valuable insights for developing effective and resistance-proof antimicrobial agents. Full article

The emergence of multidrug-resistant pathogens has driven the development of novel antimicrobial peptides (AMPs) as therapeutic alternatives. Lactolisterin LBU (LBU) is a bacteriocin with promising activity against Gram-positive bacteria, including Staphylococcus aureus. In this study, we designed and evaluated a panel of amino acid variants of LBU to investigate domain–activity relationships and improve activity. Peptides were commercially synthesized, and their effect was evaluated for minimal inhibitory concentration (MIC), minimal bactericidal concentration (MBC), hemolytic activity, cytotoxicity, in vivo toxicity, and virulence modulation. AlphaFold3 structural prediction of LBU revealed a four-helix topology with amphipathic and hydrophobic segments. Helical wheel projections identified helices I and IV as amphipathic, suggesting their potential involvement in membrane interaction and activity. Glycine-to-alanine substitutions at helix I markedly increased antimicrobial activity but altered toxicity profiles. In contrast, changes at helix junctions and kinks reduced antimicrobial activity. We also showed differential regulation of virulence genes upon sub-MIC treatment. Overall, rational substitution enabled identification of residues critical for activity and toxicity, providing insights into therapeutic tuning of lactolisterin-based peptides. Full article

Viruses use a range of sophisticated strategies to evade detection by cytotoxic T-lymphocytes (CTLs) within host cells. Beyond elaborating dedicated viral proteins that disrupt the MHC class I antigen-presentation machinery, some viruses possess intrinsic, cis-acting genome-encoded elements that interfere with antigen processing and display. These protein features, including G-quadruplex motifs, repetitive peptide sequences, and rare-codon usage, counterintuitively limit production of proteins critical to virus survival, particularly during latency. By slowing viral protein synthesis, these features reduce antigen production and proteosomal degradation, ultimately limiting the generation of peptides for MHC I presentation. These built-in evasion tactics enable viruses to remain “invisible” to CTLs during latency. While these primary sequence intrinsic immune evasion (PSI) mechanisms are well-described in select herpesviruses, emerging evidence suggests that they may also play a critical role in RNA viruses. How these proteins are made, rather than what they functionally target, determines their immune evasion properties. Understanding PSI mechanisms could rationally inform the design of engineered viral antigens with altered or removed evasion elements to restore antigen CTL priming and activation. Such vaccine strategies have the potential to enhance immune recognition, improve clearance of chronically infected cells, and contribute to the treatment of persistent viral infections and virus-associated cancers. Full article

Gramicidin S (GS), an antimicrobial peptide (AMP), exhibits broad-spectrum activity against bacteria and cancer cells but is limited in clinical use due to its cytotoxicity toward eukaryotic cells. Lipid-based delivery systems may overcome this limitation; in this study, we proposed and tested simple and promising lipid formulations, including dipalmitoylphosphatidylcholine (DPPC), cardiolipin (CL), and cholesterol (CHOL). We evaluated the interactions of these lipid membranes with GS by assessing membrane fluidity, dielectric permittivity, dielectric losses, dielectric relaxation frequency, and static dielectric constant. Among these, membrane fluidity and dielectric permittivity were the most sensitive to GS, showing significant changes in the formulation containing 90 mol% DPPC and 10 mol% CHOL when exposed to 20 μM GS. Notably, although membrane fluidity changed in a dose-dependent manner following GS binding, the liposomes still supported relatively high GS concentrations—up to 80 μM—which is important for future high-dose GS applications. Additionally, we performed preliminary cytotoxicity tests comparing free GS with liposome-carried GS using the tested lipid compositions and observed a significant reduction in GS-associated toxicity on L929 cell line. This study provides new insights into GS–membrane interactions and supports the rational design of AMP nanocarriers for biomedical applications. Full article

Antimicrobial peptides (AMPs) represent a powerful support to conventional antibiotics in addressing the global challenge of antimicrobial resistance (AMR). Their broad-spectrum antimicrobial activity and unique mechanisms of action enable diverse potential applications, including combating multidrug-resistant pathogens, immune modulation, and cancer therapy. Their clinical implementation is hindered by challenges such as toxicity, instability, and high production costs. Recent advances in AMP design, optimization, and delivery mechanisms such as nanoparticle conjugation and rational engineering have enhanced their efficacy, stability, and specificity. Integrating AMPs into precision medicine and combining them with existing therapies promises to overcome current limitations. With ongoing advancements, AMPs have the potential to redefine infection management and possibly other medical problems. Full article

Phage display has advanced the discovery of peptides that selectively bind to a wide variety of cell surface molecules, offering new modalities to modulate disease-related protein–protein interactions (PPIs). These cell-binding peptides occupy a unique pharmaceutical space between small molecules and large biologics, and their growing popularity has opened up new avenues for targeting cell surface proteins that were previously considered undruggable. This work provides an overview of methods for identifying cell-selective peptides using phage display combinatorial libraries, covering in vitro, ex vivo, and in vivo biopanning approaches. It addresses key considerations in library design, including the peptide conformation (linear vs. cyclic) and length, and highlights examples of clinically approved peptides developed through phage display. It also discusses the on-phage chemical cyclization of peptides to overcome the limitations of genetically encoded disulfide bridges and emphasizes advances in combining next-generation sequencing (NGS) with phage display to improve peptide selection and analysis workflows. Furthermore, due to the often suboptimal binding affinity of peptides identified in phage display selections, this article discusses affinity maturation techniques, including random mutagenesis and rational design through structure–activity relationship (SAR) studies to optimize initial peptide candidates. By integrating these developments, this review outlines practical strategies and future directions for harnessing phage display in targeting challenging cell surface proteins. Full article

The increasing circulation of multi-drug-resistant pathogens, coupled with the sluggish development of new antibiotics, is weakening our capacity to combat human infections, resulting in elevated death tolls. To address this worldwide crisis, antimicrobial peptides (AMPs) are viewed as promising substitutes or adjuvants for combating bacterial infections caused by multidrug-resistant organisms. Here, the antimicrobial activity and structural characterization of a novel 13-amino acid cationic peptide named RKW (RKWILKWLRTWKK-NH2), designed based on known AMPs sequences and the identification of a key tryptophan-rich structural motif, were described. RKW displayed a broad-spectrum and potent antimicrobial and antibiofilm activity against Gram-positive and Gram-negative pathogens, including ESKAPE bacteria and fungi with minimal inhibitory concentrations (MBC) ranging from 5 µM to 20 μM. Structural results by fluorescence and Circular Dichroism (CD) spectroscopy revealed that the peptide was folded into a regular α-helical conformation in a membrane-like environment, remaining stable in a wide range of pH and temperature for at least 48 h of incubation. Furthermore, RKW showed low toxicity in vitro against mammalian fibroblast cells, indicating its potential as a promising candidate for the development of new antimicrobial or antiseptic strategies. Full article

Hydrogels are ECM-mimicking three-dimensional (3D) networks that are widely used in biomedical applications; however, conventional natural and synthetic polymer-based hydrogels present limitations such as poor mechanical strength, limited bioactivity, and low reproducibility. Self-assembling peptides (SAPs) offer a promising alternative, as they can form micro- and nanostructured hydrogels through non-covalent interactions and allow precise control over their biofunctionality, mechanical properties, and responsiveness to biological cues. Through rational sequence design, SAPs can be engineered to exhibit tunable mechanical properties, controlled degradation rates, and multifunctionality, and can dynamically regulate assembly and degradation in response to specific stimuli such as pH, ionic strength, enzymatic cleavage, or temperature. Furthermore, SAPs have been successfully incorporated into conventional hydrogels to enhance cell adhesion, promote matrix remodeling, and provide a more physiologically relevant microenvironment. In this review, we summarize recent advances in SAP-based hydrogels, particularly focusing on their novel biofunctional properties such as anti-inflammatory, antimicrobial, and anticancer activities, as well as bioimaging capabilities, and discuss the mechanisms by which SAP hydrogels function in biological systems. Full article

Dengue virus (DENV) remains a critical global health challenge, with no approved antiviral treatments currently available. The growing prevalence of DENV infections highlights the urgent need for effective therapeutics. Antiviral peptides (AVPs) have gained significant attention due to their potential to inhibit viral replication. However, traditional drug discovery methods are often time-consuming and resource-intensive. Advances in artificial intelligence, particularly deep generative models (DGMs), offer a promising approach to accelerating AVP discovery. This report provides a comprehensive assessment of the role of DGMs in identifying novel AVPs for DENV. It presents an extensive survey of existing antimicrobial and AVP datasets, peptide sequence feature representations, and the integration of DGMs into computational peptide design. Additionally, in vitro and in silico screening data from previous studies highlight the therapeutic potential of AVPs against DENV. Variational autoencoders and generative adversarial networks have been extensively documented in the literature for their applications in AVP generation. These models have demonstrated a remarkable capacity to generate diverse and structurally viable compounds, significantly expanding the repertoire of potential antiviral candidates. Additionally, this report assesses both the strengths and limitations of DGMs, providing valuable insights for guiding future research directions. As a data-driven and scalable framework, DGMs offer a promising avenue for the rational design of potent AVPs targeting DENV and other emerging viral pathogens, contributing to the advancement of next-generation therapeutic strategies. Full article

Signal peptides (SPs) are short amino acid sequences located at the N-terminus of nascent proteins and are widely present across various life forms. They play crucial roles in protein synthesis, transmembrane transport, and intracellular signal transduction. With the rapid advancement of bioinformatics, studies have revealed that the functions of SPs are far more complex than previously understood. In recombinant protein expression systems, the rational design and optimization of SPs are essential for enhancing the expression efficiency and secretion level of exogenous proteins. Meanwhile, the application value of SPs in vaccine development has attracted increasing attention. This review summarizes the structural characteristics, functional mechanisms, and applications of SPs in recombinant protein production and SP-based vaccines. It also discusses their biological roles, the significance of engineering optimization strategies, and the current challenges, aiming to provide theoretical support and practical guidance for improving recombinant protein yield and advancing SP-based vaccine development. Full article

Autophagy plays a central role in cellular degradation and recycling pathways involving the formation of autophagosomes from cellular components. The Atg8 protein family, particularly LC3, is essential to this process, and dysregulation has been implicated in many diseases (including cancer). Furthermore, therapeutic strategies targeting Atg8 proteins like LC3 can be advanced by exploiting the expanding knowledge of the “LC3 interacting region” (LIR) domain to develop inhibitory ligands. Here, we report a computational approach to design novel peptides that inhibit LC3B. The LIR domain of a known LC3B binder (the FYCO1 peptide) was used as a starting point to design new peptides with unnatural amino acids and conformational restraints. Accomplishing molecular dynamics simulations and binding free energy calculations on the complex of peptide–LC3B, new promising FYCO1 analogs were selected. These peptides were synthesized and investigated by biophysical and biological experiments. Their ability to affect cellular viability was determined in different cancer cell lines (prostate cancer, breast cancer, lung cancer, and melanoma). In addition, the ability to inhibit autophagy and enhance the apoptotic activity of Docetaxel was evaluated in PC-3 prostate cancer cells. In conclusion, this research presents a rational approach to designing and developing LC3B inhibitors based on the FYCO1-LIR domain. The designed peptides hold promise as potential therapeutic agents for cancer and as tools for further elucidating the role of LC3B in autophagy. Full article

Proline-rich antimicrobial peptides (PrAMPs) primarily exert their antimicrobial effects intracellularly, inhibiting protein synthesis. B7-005, a synthetic 16-amino acid PrAMP, has a broader antimicrobial spectrum compared to native counterparts, despite shorter PrAMPs typically exhibiting reduced activity. This study aimed to enhance B7-005’s potency by extending it with 6 or 11 amino acids derived from the C-terminal sequences of cetacean Tur1A and Lip1 PrAMPs, as well as bovine Bac7(1-35). Six chimeric derivatives were evaluated for antimicrobial and bactericidal potency, cytotoxicity, bacterial membrane permeabilization, and in vitro inhibition of protein synthesis. Extending B7-005 with sequences from other PrAMPs increased its activity against most ESKAPE+E pathogens, reducing minimum inhibitory concentration (MIC) values by 2- to 8-fold, with notable differences among bacterial species, without increasing cytotoxicity toward the A549 cell line. All chimeras retained the ability to inhibit protein synthesis in Escherichia coli and to modestly perturb the E. coli membranes like B7-005. These novel chimeric PrAMPs, particularly the 22-mer derivatives, hold promise for developing new antimicrobial agents. The study also highlights variability in bacterial responses to PrAMPs and underscores how minor sequence differences can significantly impact efficacy against specific microorganisms. PrAMPs thus represent a valuable scaffold to rationally design derivatives targeting high-priority pathogens. Full article