Applying Immunoinformatics Methods to Identify Potential T and B Cell Epitopes in the CagA Protein of Helicobacter pylori

Background and Aim: Helicobacter pylori is not only identified as a leading cause of chronic active gastritis and peptic ulcer disease in humans, but also it is considered as a risk factor for the development of gastric adenocarcinoma and MALT lymphoma. This study aims to predict specific epitopes for the utility of designing peptide vaccine against H. pylori infection by targeting invasive, virulent and membrane associated proteins CagA. Materials and Methods: In the present study, various immunoinformatics approaches have been applied to design a potential epitope-based vaccine against H. pylori infection. For prediction of linear epitopes, the sequence of CagA was submitted to ABCpred, BCPREDS, Bcepred, Bepipred and Ellipro servers. DiscoTope 2.0 and B-pred servers were also used for the prediction of conformational epitopes. In addition, prediction of T-cell epitopes was carried out by CTLPred. Results: The obtained results demonstrated 277 conformational B-Cell epitopes in addition to predicted high score linear B and T cell epitopes in CagA protein. Conclusion: These predicted epitopes might be used to design a vaccine against H. pylori and thus, could be validated in model hosts to verify their efficacy as vaccine

Vaccine Development

Vaccination is the most effective and scientifically based means of protection against infectious diseases, especially in this era of the COVID-19 pandemic. This book examines several issues related to the development of vaccines against viral, bacterial, and parasitic infections

A novel design of multi-epitope based vaccine against Escherichia coli

Background: Multi-valent based vaccines have advantage over conventional vaccines because of its multi-faceted action targeted at antigen; thereby raising hope of a more sustained actions against allergens. Escherichia coli (E. coli) is a bacterium that is commonly found in the gut of humans and warm-blooded animals. An increasing number of outbreaks are associated with the consumption of fruits and vegetables (including sprouts, spinach, lettuce, coleslaw, and salad) thereby contamination may be due to contact with faeces from domestic or wild animals at some stages during cultivation or handling. Due to the reported increase in resistance to antibiotics used for Escherichia coli control; an effective vaccine is a would-be alternative of proven interest. Hence, a need for a rational, strategic, and efficient vaccine candidate against E.coli is of paramount necessity by the use of the most current bioinformatics tools to achieve this task. Method: In this study, immunoinformatics tools mined from diverse molecular databases were used  for a novel putative epitope based oral vaccine against E.coli. The prospective vaccine proteins were carefully screened and validated to achieve a high thorough-put three-dimensional protein structure. The eventual propsective vaccine candidate proteins was evaluated for its non-allergenicity, antigenicity, solubility, appropriate molecular weight testing and isoelectric point evaluation. Conclusion: The resultant vaccine candidate could serve as a promising anti-E.coli vaccine candidate. Immunoinformatics is a new field over pharmaco-therapeutics; this newest technology should continue to be a rescue from age-long traditional approach in vaccine developments

Time for T? Immunoinformatics Addresses Vaccine Design for Neglected Tropical and Emerging Infectious Diseases

Vaccines have been invaluable for global health, saving lives and reducing healthcare costs, while also raising the quality of human life. However, newly emerging infectious diseases (EID) and more well-established tropical disease pathogens present complex challenges to vaccine developers; in particular, neglected tropical diseases, which are most prevalent among the world\u27s poorest, include many pathogens with large sizes, multistage life cycles and a variety of nonhuman vectors. EID such as MERS-CoV and H7N9 are highly pathogenic for humans. For many of these pathogens, while their genomes are available, immune correlates of protection are currently unknown. These complexities make developing vaccines for EID and neglected tropical diseases all the more difficult. In this review, we describe the implementation of an immunoinformatics-driven approach to systematically search for key determinants of immunity in newly available genome sequence data and design vaccines. This approach holds promise for the development of 21st century vaccines, improving human health everywhere

In silico design of a multi-epitope vaccine against HPV16/18

Background Cervical cancer is the fourth most common cancer affecting women and is caused by human Papillomavirus (HPV) infections that are sexually transmitted. There are currently commercially available prophylactic vaccines that have been shown to protect vaccinated individuals against HPV infections, however, these vaccines have no therapeutic effects for those who are previously infected with the virus. The current study's aim was to use immunoinformatics to develop a multi-epitope vaccine with therapeutic potential against cervical cancer. Results In this study, T-cell epitopes from E5 and E7 proteins of HPV16/18 were predicted. These epitopes were evaluated and chosen based on their antigenicity, allergenicity, toxicity, and induction of IFN-gamma production (only in helper T lymphocytes). Then, the selected epitopes were sequentially linked by appropriate linkers. In addition, a C-terminal fragment of Mycobacterium tuberculosis heat shock protein 70 (HSP70) was used as an adjuvant for the vaccine construct. The physicochemical parameters of the vaccine construct were acceptable. Furthermore, the vaccine was soluble, highly antigenic, and non-allergenic. The vaccine's 3D model was predicted, and the structural improvement after refinement was confirmed using the Ramachandran plot and ProSA-web. The vaccine's B-cell epitopes were predicted. Molecular docking analysis showed that the vaccine's refined 3D model had a strong interaction with the Toll-like receptor 4. The structural stability of the vaccine construct was confirmed by molecular dynamics simulation. Codon adaptation was performed in order to achieve efficient vaccine expression in Escherichia coli strain K12 (E. coli). Subsequently, in silico cloning of the multi-epitope vaccine was conducted into pET-28a ( +) expression vector. Conclusions According to the results of bioinformatics analyses, the multi-epitope vaccine is structurally stable, as well as a non-allergic and non-toxic antigen. However, in vitro and in vivo studies are needed to validate the vaccine's efficacy and safety. If satisfactory results are obtained from in vitro and in vivo studies, the vaccine designed in this study may be effective as a therapeutic vaccine against cervical cancer

Bacterium-like particles derived from probiotics: progress, challenges and prospects

Bacterium-like particles (BLPs) are hollow peptidoglycan particles obtained from food-grade Lactococcus lactis inactivated by hot acid. With the advantage of easy preparation, high safety, great stability, high loading capacity, and high mucosal delivery efficiency, BLPs can load and display proteins on the surface with the help of protein anchor (PA), making BLPs a proper delivery system. Owning to these features, BLPs are widely used in the development of adjuvants, vaccine carriers, virus/antigens purification, and enzyme immobilization. This review has attempted to gather a full understanding of the technical composition, characteristics, applications. The mechanism by which BLPs induces superior adaptive immune responses is also discussed. Besides, this review tracked the latest developments in the field of BLPs, including Lactobacillus-derived BLPs and novel anchors. Finally, the main limitations and proposed breakthrough points to further enhance the immunogenicity of BLPs vaccines were discussed, providing directions for future research. We hope that further developments in the field of antigen delivery of subunit vaccines or others will benefit from BLPs

Designing a novel multi‑epitope vaccine against Ebola virus using reverse vaccinology approach

Ebola virus (EBOV) is a dangerous zoonotic infectious disease. To date, more than 25 EBOV outbreaks have been documented, the majority of which have occurred in Central Africa. The rVSVG-ZEBOV-GP vaccine (ERVEBO), a live attenuated vaccine, has been approved by the US Food and Drug Administration (FDA) to combat EBOV. Because of the several drawbacks of live attenuated vaccines, multi-epitope vaccines probably appear to be safer than live attenuated vaccines. In this work, we employed immunoinformatics tools to design a multi-epitope vaccine against EBOV. We collected sequences of VP35, VP24, VP30, VP40, GP, and NP proteins from the NCBI database. T-cell and linear B-cell epitopes from target proteins were identified and tested for antigenicity, toxicity, allergenicity, and conservancy. The selected epitopes were then linked together in the vaccine's primary structure using appropriate linkers, and the 50S ribosomal L7/L12 (Locus RL7 MYCTU) sequence was added as an adjuvant to the vaccine construct's N-terminal. The physicochemical, antigenicity, and allergenicity parameters of the vaccine were all found to be satisfactory. The 3D model of the vaccine was predicted, refined, and validated. The vaccine construct had a stable and strong interaction with toll-like receptor 4 (TLR4) based on molecular docking and molecular dynamic simulation (MD) analysis. The results of codon optimization and in silico cloning revealed that the proposed vaccine was highly expressed in Escherichia coli (E. coli). The findings of this study are promising; however, experimental validations should be carried out to confirm these findings

Developing a multi-epitope vaccine candidate to combat porcine epidemic diarrhea virus and porcine deltacoronavirus co-infection by employing an immunoinformatics approach

Coinfection of porcine epidemic diarrhea virus (PEDV) and porcine deltacoronavirus (PDCoV) is common in pig farms, but there is currently no effective vaccine to prevent this co-infection. In this study, we used immunoinformatics tools to design a multi-epitope vaccine against PEDV and PDCoV co-infection. The epitopes were screened through a filtering pipeline comprised of antigenic, immunogenic, toxic, and allergenic properties. A new multi-epitope vaccine named rPPMEV, comprising cytotoxic T lymphocyte-, helper T lymphocyte-, and B cell epitopes, was constructed. To enhance immunogenicity, the TLR2 agonist Pam2Cys and the TLR4 agonist RS09 were added to rPPMEV. Molecular docking and dynamics simulation were performed to reveal the stable interactions between rPPMEV and TLR2 as well as TLR4. Additionally, the immune stimulation prediction indicated that rPPMEV could stimulate T and B lymphocytes to induce a robust immune response. Finally, to ensure the expression of the vaccine protein, the sequence of rPPMEV was optimized and further performed in silico cloning. These studies suggest that rPPMEV has the potential to be a vaccine candidate against PEDV and PDCoV co-infection as well as a new strategy for interrupting the spread of both viruses

Immunoinformatics and Computer-Aided Drug Design as New Approaches against Emerging and Re-Emerging Infectious Diseases

Infectious diseases are initiated by small pathogenic living germs that are transferred from person to person by direct or indirect contact. Recently, different newly emerging and reemerging infectious viral diseases have become greater threats to human health and global stability. Investigators can anticipate epidemics through the advent of numerous mathematical tools that can predict specific pathogens and identify potential targets for vaccine and drug design and will help to fight against these challenges. Currently, computational approaches that include mathematical and essential tools have unfolded the way for a better understanding of newly originated emerging and re-emerging infectious disease, pathogenesis, diagnosis, and treatment option of specific diseases more easily, where immunoinformatics plays a crucial role in the discovery of novel peptides and vaccine candidates against the different viruses within a short time. Computational approaches include immunoinformatics, and computer-aided drug design (CADD)-based model trained biomolecules that offered reasonable and quick implementation approaches for the modern discovery of effective viral therapies. The essence of this review is to give insight into the multiple approaches not only for the detection of infectious diseases but also profound how people can pick appropriate models for the detection of viral therapeutics through computational approaches

Application of built-in adjuvants for epitope-based vaccines

Several studies have shown that epitope vaccines exhibit substantial advantages over conventional vaccines. However, epitope vaccines are associated with limited immunity, which can be overcome by conjugating antigenic epitopes with built-in adjuvants (e.g., some carrier proteins or new biomaterials) with special properties, including immunologic specificity, good biosecurity and biocompatibility, and the ability to vastly improve the immune response of epitope vaccines. When designing epitope vaccines, the following types of built-in adjuvants are typically considered: (1) pattern recognition receptor ligands (i.e., toll-like receptors); (2) virus-like particle carrier platforms; (3) bacterial toxin proteins; and (4) novel potential delivery systems (e.g., self-assembled peptide nanoparticles, lipid core peptides, and polymeric or inorganic nanoparticles). This review primarily discusses the current and prospective applications of these built-in adjuvants (i.e., biological carriers) to provide some references for the future design of epitope-based vaccines