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Results for “Reverse vaccinology”

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PubMed2026

Computational prediction of a multi-epitope Human Metapneumovirus vaccine candidate through integrated reverse vaccinology and pan-genomic approaches.

Human metapneumovirus (HMPV) is a primary cause of global respiratory infections yet no approved vaccine currently exists. This study computationally predicts a multi-epitope vaccine candidate using a diverse dataset of 65 HMPV sequences spanning five continents. Following the screening of lead proteins for antigenicity and virulence, fifteen highly conserved MHC-I, MHC-II and B-cell epitopes were prioritized. These were integrated with a putative L7/L12 adjuvant using optimized AAY, GPGPG, and KK linkers to design three constructs (HMPV_V1-V3). Structural validation identified HMPV-V2 as the lead candidate that exhibits a Z-score of-5.24 and 87.7% of residues in favored Ramachandran regions indicating excellent stereochemical quality and structural stability. In silico docking indicated a strong predicted binding affinity between HMPV-V2 and the TLR4 receptor (energy: -969.2). Immune simulations predicted a robust adaptive response characterized by high IgG1 titers, memory B-cell maturation, and a Th1-dominant cytokine profile. Furthermore, molecular dynamics simulations suggested exceptional structural integrity for HMPV-V2, maintaining a low RMSD of 8.213 and RMSF of 0.737 throughout the simulation. Optimized in silico cloning into the pET28a (+) vector indicated a high potential for protein expression in E. coli systems. While these findings provide a theoretically grounded blueprint for vaccine development, this study is entirely computational and lacks experimental validation. Further in vitro and in vivo testing is required to confirm the actual safety and immunogenicity of the proposed candidate.

Metapneumovirus↗

PubMed2026

Leptospira-host interactions: advancing next-generation vaccines and diagnostics.

SUMMARYLeptospirosis, a widespread zoonotic disease caused by pathogenic Leptospira species, remains a major public health challenge, particularly in tropical and subtropical regions. Despite advances in understanding Leptospira biology and pathogenesis, effective disease control continues to be limited by the lack of rapid, early diagnostics, and broadly protective vaccines. This review comprehensively examines recent progress in deciphering Leptospira-host interactions, with emphasis on key virulence factors, immune-evasion mechanisms, and host immune responses that influence disease outcomes. Particular focus is placed on the molecular and cellular basis of adhesion, invasion, immune modulation, and persistent colonization. We further discuss the limitations of current vaccines and diagnostic approaches, and highlight how emerging technologies, including pan-genomics, proteomics, reverse vaccinology, immunoinformatics, and omics-based antigen discovery, are facilitating the development of next-generation vaccines and diagnostics. Finally, we outline major translational challenges and future perspectives for improving clinical management, surveillance, and prevention of leptospirosis. The concepts discussed in this review may also provide broader insights into vaccine and diagnostic development for other zoonotic bacterial infections.

Humans↗

PubMed2025

Multi-criteria decision making and its application to in silico discovery of vaccine candidates for Toxoplasma gondii.

Vaccine discovery against eukaryotic parasites is not trivial and few exist. Reverse vaccinology is an in silico vaccine discovery approach, designed to identify vaccine candidates from the thousands of protein sequences encoded by a target genome. Previously, we produced the Vacceed bioinformatics pipeline for identification of parasite membrane and excreted/secreted proteins that were likely be exposed to the hosts immune system. More recently, we improved upon machine learning as the final decision-making process to identify parasite proteins that induce a protective response in an animal model. Subsequently, we combined Vacceed with metrics on B and T cell epitope types to produce a new in silico discovery workflow. In this study we extend this in silico workflow to the developability of proteins as vaccines by the incorporation of metrics on the physicochemical properties of proteins. To demonstrate this process, every Toxoplasma gondii protein was ranked in its capacity to provide exposure to the immune system (Vacceed exposure score), presence of epitopes and solubility characteristics by several multicriteria decision making (MCDM) tools (such as TOPSIS, VIKOR and MABAC). A consensus rank was subsequently generated from the results of these tools using a variety of aggregate ranking methods. Levels of uncertainty in the aggregate protein rankings was assessed by conformal interval prediction in association with a machine learning model. Several of the top ranked proteins identified by this approach were novel, uncharacterized membrane transporters or proteins associated with RNA metabolism. In conclusion, MCDM automated the decision making using well known algorithms while conformal prediction intervals varied significantly across the 8000+ proteins of T. gondii. Highly ranked proteins (e.g. the top 100) typically generated low prediction intervals, providing high levels of confidence in their ranks.

Toxoplasma↗

PubMed2026

Integrated immunoinformatics for the design of novel multi-epitope vaccine and identification of new drug targets against Stenotrophomonas maltophilia, a multidrug-resistant superbug.

BACKGROUND: Stenotrophomonas maltophilia is a multidrug-resistant opportunistic pathogen causing severe hospital-acquired infections, especially in immunocompromised patients. The absence of an effective vaccine and rising antibiotic resistance underscore the need for novel interventions. This study employed an integrated reverse vaccinology and computational analyses to identify new immunogenic targets, design a multi-epitope vaccine (MEV), and propose potential drug targets. METHODS: A comprehensive immunoinformatics pipeline was employed to assess antigenicity, allergenicity, human similarity, and physicochemical properties of S. maltophilia proteins. Both B- and T-cell epitopes were screened; however, only the top B-cell epitopes were selected for MEV construction, given the extracellular nature of S. maltophilia. MEV-TLR interactions were analyzed through molecular docking and dynamics simulations. In parallel, cytoplasmic proteins were screened via a subtractive genomics approach to identify essential, non-human homologous, and non-microbiome-similar proteins, which were further evaluated for druggability and interaction networks to propose novel therapeutic targets. RESULTS: From a total of 4111 proteins, seven potential immunogenic targets were identified: GspD (WP_108270537.1), FhuE (WP_049451370.1), fimbrial protein (WP_012479122.1), TonB-dependent receptor (WP_169448402.1), TolC family protein (WP_108270106.1), autotransporter beta-barrel OMP (WP_169448945.1), and a hypothetical protein (WP_005407892.1). Subsequently, an MEV was designed using five immunogenic epitopes derived from four of these targets: WP_005407892.1 (ADQDSSNM), WP_049451370.1 (SGKAEQ and GEESKTPS), WP_108270537.1 (GVTSTQSDSERT), and WP_169448945.1 (RELGGDRNE). Molecular docking and molecular dynamics simulations demonstrated strong, stable, and feasible interactions between the MEV and TLR-2 and TLR-4 receptors. Moreover, nine novel drug targets were predicted for S. maltophilia, providing new therapeutic insights. CONCLUSION: The designed MEV and identified immunogenic targets represent promising vaccine candidates against S. maltophilia. Further in vitro and in vivo studies are essential to confirm their safety, immunogenicity, and protective efficacy. Additionally, subtractive genomics analysis revealed nine novel, non-homologous drug targets, offering safer and more specific therapeutic avenues.

Drug targets↗

PubMed2026

An immunoinformatics-based multi-epitope vaccine candidate confers cross-protection against two Actinobacillus pleuropneumoniae serovars.

Porcine contagious pleuropneumonia (PCP) is caused by Actinobacillus pleuropneumoniae (APP) and inflicts heavy economic losses on the swine industry. However, existing inactivated vaccines provide limited cross-protection, highlighting the need for improved vaccine strategies. In this study, we combined pangenome analysis with subtractive proteomics to screen the APP core genome and identified 11 potential antigens. Seven of them showed immunoreactivity by ELISA and Western blotting. These antigens, together with the ApxI-III toxins, were used for T and B cell epitope prediction. On this basis, a multi-epitope fusion protein MVAPP was constructed. In silico molecular docking with swine immune receptors and immune simulations suggested that MVAPP has the potential to induce immune responses. In the mouse model, that MVAPP elicited specific antibody responses, shifted the splenic T-cell subset distribution toward CD4+ T cells, and provided partial protection against challenge with strains from two serovars. In conclusion, MVAPP represents a potential multi-epitope vaccine candidate for further development against APP.

Animals↗