Discovering peptides and computational investigations of a multiepitope vaccine target Mycobacterium tuberculosis

Mycobacterium tuberculosis(MTB)is the causative agent of tuberculosis(TB),a prevalent airborne infectious disease.Despite the availability of the Bacille Calmette-Guerin vaccine,its global efficacy remains modest,and tuberculosis persists as a significant global public health threat.Addressing this challenge and advancing towards the End MTB Strategy,we developed a multiepitope vaccine(MEV)based on immunoinformatics and compu-tational approaches.Immunoinformatics screening of MBT protein identified immune-dominant epitopes based on Major Histocompatibility Complex(MHC)allele binding,immunogenicity,antigenicity,allergenicity,toxicity,and cytokine inducibility.Selected epitopes were integrated into an MEV construct with adjuvant and linkers,forming a fully immunogenic vaccine candidate.Comprehensive analyses encompassed the evaluation of immunological and physicochemical properties,determination of tertiary structure,molecular docking with Toll-Like Receptors(TLR),molecular dynamics(MD)simulations for all atoms,and immune simulations.Our MEV comprises 534 amino acids,featuring 6 cytotoxic T lymphocyte,8 helper T lymphocyte,and 7 linear B lymphocyte epitopes,demonstrating high antigenicity and stability.Notably,molecular docking studies and triplicate MD simulations revealed enhanced interactions and stability of MEV with the TLR4 complex compared to TLR2.In addition,the immune simulation indicated the capacity to effectively induce elevated levels of an-tibodies and cytokines,emphasizing the vaccine’s robust immunogenic response.This study presents a promising MEV against TB,exhibiting favorable immunological and physicochemical attributes.The findings provide theoretical support for TB vaccine development.Our study aligns with the global initiative of the End MTB Strategy,emphasizing its potential impact on addressing persistent challenges in TB control.

Self-assembled multiepitope nanovaccine based on NoV P particles induces effective and lasting protection against H3N2 influenza virus

Current seasonal influenza vaccines confer only limited coverage of virus strains due to the frequent genetic and antigenic variability of influenza virus(IV).Epitope vaccines that accurately target conserved domains provide a promising approach to increase the breadth of protection;however,poor immunogenicity greatly hinders their application.The protruding(P)domain of the norovirus(NoV),which can self-assemble into a 24-mer particle called the NoV P particle,offers an ideal antigen presentation platform.In this study,a multiepitope nanovaccine displaying influenza epitopes(HMN-PP)was constructed based on the NoV P particle nanoplatform.Large amounts of HMN-PP were easily expressed in Escherichia coli in soluble form.Animal experiments showed that the adjuvanted HMN-PP nanovaccine induced epitope-specific antibodies and haemagglutinin(HA)-specific neutralizing antibodies,the antibodies could persist for at least three months after the last immunization.Furthermore,HMN-PP induced matrix protein 2 extracellular domain(M2e)-specific antibody-dependent cell-mediated cytotoxicity,CD4^(+)and CD8^(+)T-cell responses,a nucleoprotein(NP)-specific cytotoxic T lymphocyte(CTL)response.These results indicated that the combination of a multiepitope vaccine and self-assembled NoV P particles may be an ideal and effective vaccine strategy for highly variable viruses such as IV and SARS-CoV-2.

Decoding bovine coronavirus immune targets:an epitope informatics approach

Bovine coronavirus(BCoV)poses a significant threat to the global cattle industry,causing both respiratory and gastrointestinal infections in cattle populations.This necessitates the development of efficacious vaccines.While several inactivated and live BCoV vaccines exist,they are predominantly limited to calves.The immunization of adult cattle is imperative for BCoV infection control,as it curtails viral transmission to calves and ameliorates the impact of enteric and respiratory ailments across all age groups within the herd.This study presents an in silico methodology for devising a multiepitope vaccine targeting BCoV.The spike glycoprotein(S)and nucleocapsid(N)proteins,which are integral elements of the BCoV structure,play pivotal roles in the viral infection cycle and immune response.We constructed a remarkably effective multiepitope vaccine candidate specifically designed to combat the BCoV population.Using immunoinformatics technology,B-cell and T-cell epitopes were predicted and linked together using linkers and adjuvants to efficiently trigger both cellular and humoral immune responses in cattle.The in silico construct was characterized,and assessment of its physicochemical properties revealed the formation of a stable vaccine construct.After 3D modeling of the vaccine construct,molecular docking revealed a stable interaction with the bovine receptor bTLR4.Moreover,the viability of the vaccine’s high expression and simple purification was demonstrated by codon optimization and in silico cloning expression into the pET28a(+)vector.By applying immunoinformatics approaches,researchers aim to better understand the immune response to bovine coronavirus,discover potential targets for intervention,and facilitate the development of diagnostic tools and vaccines to mitigate the impact of this virus on cattle health and the livestock industry.We anticipate that the design will be useful as a preventive treatment for BCoV sickness in cattle,opening the door for further laboratory studies.

Integrating immunoinformatics and computational epitope prediction for a vaccine candidate against respiratory syncytial virus

Respiratory syncytial virus(RSV)poses a significant global health threat,especially affecting infants and the elderly.Addressing this,the present study proposes an innovative approach to vaccine design,utilizing immunoinformatics and computational strategies.We analyzed RSV's structural proteins across both subtypes A and B,identifying potential helper T lymphocyte,cytotoxic T lymphocyte,and linear B lymphocyte epitopes.Criteria such as antigenicity,allergenicity,toxicity,and cytokine-inducing potential were rigorously examined.Additionally,we evaluated the conservancy of these epitopes and their population coverage across various RSV strains.The comprehensive analysis identified six major histocompatibility complex class I(MHC-I)binding,five MHC-II binding,and three B-cell epitopes.These were integrated with suitable linkers and adjuvants to form the vaccine.Further,molecular docking and molecular dynamics simulations demonstrated stable interactions between the vaccine candidate and human Toll-like receptors(TLR4 and TLR5),with a notable preference for TLR4.Immune simulation analysis underscored the vaccine's potential to elicit a strong immune response.This study presents a promising RSV vaccine candidate and offers theoretical support,marking a significant advancement in vaccine development efforts.However,the promising in silico findings need to be further validated through additional in vivo studies.