Designing an efficient multi-epitope oral vaccine against Helicobacter pylori using immunoinformatics and structural vaccinology approaches

Immunoinformatics-Aided Design and Evaluation of a Potential Multi-Epitope Vaccine against Klebsiella Pneumoniae

Klebsiella pneumoniae is an opportunistic gram-negative bacterium that causes nosocomial infection in healthcare settings. Despite the high morbidity and mortality rate associated with these bacterial infections, no effective vaccine is available to counter the pathogen. In this study, the pangenome of a total of 222 available complete genomes of K. pneumoniae was explored to obtain the core proteome. A reverse vaccinology strategy was applied to the core proteins to identify four antigenic proteins. These proteins were then subjected to epitope mapping and prioritization steps to shortlist nine B-cell derived T-cell epitopes which were linked together using GPGPG linkers. An adjuvant (Cholera Toxin B) was also added at the N-terminal of the vaccine construct to improve its immunogenicity and a stabilized multi-epitope protein structure was obtained using molecular dynamics simulation. The designed vaccine exhibited sustainable and strong bonding interactions with Toll-like receptor 2 and Toll-like receptor 4. In silico reverse translation and codon optimization also confirmed its high expression in E. coli K12 strain. The computer-aided analyses performed in this study imply that the designed multi-epitope vaccine can elicit specific immune responses against K. pneumoniae. However, wet lab validation is necessary to further verify the effectiveness of this proposed vaccine candidate.

Decreasing the immunogenicity of Erwinia chrysanthemi asparaginase via protein engineering: computational approach

Immunogenicity of therapeutic proteins is one of the main challenges in disease treatment. L-Asparaginase is an important enzyme in cancer treatment which sometimes leads to undesirable side effects such as immunogenic or allergic responses. Here, to decrease Erwinase (Erwinia chrysanthemiL-Asparaginase) immunogenicity, which is the main drawback of the enzyme, firstly conformational B cell epitopes of Erwinase were predicted from three-dimensional structure by three different computational methods. A few residues were defined as candidates for reducing immunogenicity of the protein by point mutation. In addition to immunogenicity and hydrophobicity, stability and binding energy of mutants were also analyzed computationally. In order to evaluate the stability of the best mutant, molecular dynamics simulation was performed. Among mutants, H240A and Q239A presented significant reduction in immunogenicity. In contrast, the immunogenicity scores of D235A slightly decreased according to two servers. Binding affinity of substrate to the active site reduced significantly in K265A and E268A. The final results of molecular dynamics simulation indicated that H240A mutation has not changed the stability, flexibility, and the total structure of desired protein. Overall, point mutation can be used for reducing immunogenicity of therapeutic proteins, in this context, in silico approaches can be used to screen suitable mutants.

In silico rational design of a novel tetra-epitope tetanus vaccine with complete population coverage using developed immunoinformatics and surface epitope mapping approaches

Presentation of many unwanted epitopes within tetanus toxoid vaccine to lymphocyte clones may lead to production of many unwanted antibodies. Moreover an ideal vaccine must cover all individuals in a population that is dependent to the kinds of human leukocyte antigen alleles. Concerning these issues, our study was aimed to in silico design of a multi-epitope tetanus vaccine (METV) in order to improve population coverage and protectivity of tetanus vaccine as well as reduction of complications. Concerning these issues, a novel rational filtration was implemented to design a novel METV using immunoinformatics and surface epitope mapping approaches. Prediction of epitopes for tetanus toxin was performed in the candidate country in which the frequency had been gathered from almost all geographical distributions. The most strong binder epitopes for major histocompatibility complex class II were selected and among them the surface epitopes of native toxin were selected. The population coverage of the selected epitopes was estimated. The final candidate epitopes had highly population coverage. Molecular docking was performed to prediction of binding affinity of our candidate epitopes to the HLA-DRB1 alleles. At first, 680 strong binder epitopes were predicted. Among them 11 epitopes were selected. Finally, 4 epitopes had the most population coverage and suggested as a tetra-epitope tetanus vaccine. 99.41% of inessential strong binders were deleted using our tree steps filtration. HLA-DP had the most roles in epitope presentation. Molecular docking analysis proved the strong binding affinity of candidate epitopes to the HLA-DRB1 alleles. In conclusion, we theoretically reduced 99.41% of unwanted antibodies using our novel filtration strategies. Our tetra-epitope tetanus vaccine showed 100% population coverage in the candidate country. Furthermore, it was demonstrated that HLA-DP and HLA-DQ had more potential in epitope presentation in comparison to HLA-DRB1.

Towards the first multi-epitope recombinant vaccine against Crimean-Congo hemorrhagic fever virus: A computer-aided vaccine design approach

Crimean-Congo hemorrhagic fever (CCHF) is considered one of the major public health concerns with case fatality rates of up to 80%. Currently, there is no effective approved vaccine for CCHF. In this study, we used a computer-aided vaccine design approach to develop the first multi-epitope recombinant vaccine for CCHF. For this purpose, linear B-cell and T-cell binding epitopes from two structural glycoproteins of CCHF virus including Gc and Gn were predicted. The epitopes were further studied regarding their antigenicity, allergenicity, hydrophobicity, stability, toxicity and population coverage. A total number of seven epitopes including five T-cell and two B-cell epitopes were screened for the final vaccine construct. Final vaccine construct composed of 382 amino acid residues which were organized in four domains including linear B-cell, T-cell epitopes and cholera toxin B-subunit (CTxB) along with heat labile enterotoxin IIc B subunit (LT-IIc) as adjuvants. All the segments were joined using appropriate linkers. The physicochemical properties as well as the presence of IFN-γ inducing epitopes in the proposed vaccine, was also checked to determining the vaccine stability, solubility and its ability to induce cell-mediated immune responses. The 3D structure of proposed vaccine was subjected to the prediction of computational B-cell epitopes and molecular docking studies with MHC-I and II molecules. Furthermore, molecular dynamics stimulations were performed to study the vaccine-MHCs complexes stability during stimulation time. The results suggest that our proposed vaccine was stable, well soluble in water and potentially antigenic. Results also demonstrated that the vaccine can induce both humoral and cell-mediated immune responses and could serve as a promising anti-CCHF vaccine candidate.

Design of novel multi-epitope vaccines against severe acute respiratory syndrome validated through multistage molecular interaction and dynamics

Severe acute respiratory syndrome (SARS) is endemic in South China and is continuing to spread worldwide since the 2003 outbreak, affecting human population of 37 countries till present. SARS is caused by the severe acute respiratory syndrome Coronavirus (SARS-CoV). In the present study, we have designed two multi-epitope vaccines (MEVs) composed of cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL) and B cell epitopes overlap, bearing the potential to elicit cellular as well as humoral immune response. We have used truncated (residues 10-153) Onchocerca volvulus activation-associated secreted protein-1 as molecular adjuvants at N-terminal of both the MEVs. Selected overlapping epitopes of both the MEVs were further validated for stable molecular interactions with their respective human leukocyte antigen class I and II allele binders. Moreover, CTL epitopes were further studied for their molecular interaction with transporter associated with antigen processing. Furthermore, after tertiary structure modelling, both the MEVs were validated for their stable molecular interaction with Toll-like receptors 2 and 4. Codon-optimized cDNA of both the MEVs was analysed for their potential high level of expression in the mammalian cell line (Human) needed for their further in vivo testing. Overall, the present study proposes in silico validated design of two MEVs against SARS composed of specific epitopes with the potential to cause a high level of SARS-CoV specific cellular as well as humoral immune response. Communicated by Ramaswamy H. Sarma.

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.

Evaluating the effect of BDNF Val66Met polymorphism on complex formation with HAP1 and Sortilin1 via structural modeling

Brain derived neurotrophic factor (BDNF) has a critical role in the neurogenesis, differentiation, survival of the neurons, regulation of the appetite, and energy homeostasis. Two key proteins, Huntingtin associated protein-1 (HAP1) and sortilin1, regulate the intracellular trafficking and stabilization of the precursor proBDNF through interaction with its prodomain region and mark it for secretion. Evidence suggests that the most frequent single nucleotide polymorphism (SNP) of BDNF gene (rs6265) has been associated with different psychiatric, neurodegenerative and eating disorders. In this study, structural bioinformatics and molecular dynamics (MD) simulations were applied, in order to get precise insights into the impact of Val66Met polymorphism on the proBDNF structure and its interaction with HAP1 and Sortilin1. Homology modeling, structure validation, refinement and also protein-protein docking were performed using appropriate servers. The stability, the fluctuations and the compactness of protein complexes were measured by MD simulation parameters including root mean square deviation (RMSD), root mean square fluctuation (RMSF) and Radius of gyration (Rg), respectively. The mutant proBDNF complexes with HAP1 and Sortilin1 revealed higher RMSD and RMSF values and also variable R_g over time compared with wild-type proBDNF. These computational results indicated that, wild-type proBDNF possessed more stable structure in binding with HAP1 and Sortilin1 compared with its mutant form. Therefore, Val66Met SNP could be deleterious due to making structural changes. It may cause a decrease in proBDNF secretion, which could possibly lead to different psychiatric, neurodegenerative and eating disorders. Further experimental lab studies are required for a more accurate conclusion.

Structural basis of development of multi-epitope vaccine against Middle East respiratory syndrome using in silico approach

Background

Middle East respiratory syndrome (MERS) is caused by MERS coronavirus (MERS-CoV). Thus far, MERS outbreaks have been reported from Saudi Arabia (2013 and 2014) and South Korea (2015). No specific vaccine has yet been reported against MERS.

Purpose

To address the urgent need for an MERS vaccine, in the present study, we have designed two multi-epitope vaccines (MEVs) against MERS utilizing several in silico methods and tools.

Methods

The design of both the multi-epitope vaccines (MEVs) are composed of cytotoxic T lymphocyte (CTL) and helper T lymphocyte (HTL) epitopes, screened form thirteen different proteins of MERS-CoV. Both the MEVs also carry potential B-cell linear epitope regions, B-cell discontinuous epitopes as well as interferon-γ-inducing epitopes. Human β-defensin-2 and β-defensin-3 were used as adjuvants to enhance the immune response of MEVs. To design the MEVs, short peptide molecular linkers were utilized to link screened most potential CTL epitopes, HTL epitopes and the adjuvants. Tertiary models for both the MEVs were generated, refined, and further studied for their molecular interaction with toll-like receptor 3. The cDNAs of both MEVs were generated and analyzed in silico for their expression in a mammalian host cell line (human).

Results

Screened CTL and HTL epitopes were found to have high propensity for stable molecular interaction with HLA alleles molecules. CTL epitopes were also found to have favorable molecular interaction within the cavity of transporter associated with antigen processing. The selected CTL and HTL epitopes jointly cover upto 94.0% of worldwide human population. Both the CTL and HTL MEVs molecular models have shown to have stable binding and complex formation propensity with toll-like receptor 3. The cDNA analysis of both the MEVs have shown high expression tendency in mammalian host cell line (human).

Conclusion

After multistage in silico analysis, both the MEVs are predicted to elicit humoral as well as cell mediated immune response. Epitopes of the designed MEVs are predicted to cover large human population worldwide. Hence both the designed MEVs could be tried in vivo as potential vaccine candidates against MERS.

Exploring dengue proteome to design an effective epitope-based vaccine against dengue virus

Dengue, a mosquito-borne disease, is caused by four known dengue serotypes. This infection causes a range of symptoms from a mild fever to a sever homorganic fever and death. It is a serious public health problem in subtropical and tropical countries. There is no specific vaccine currently available for clinical use and study on this issue is ongoing. In this study, bioinformatics approaches were used to predict antigenic, immunogenic, non-allergenic, and conserved B and T-cell epitopes as promising targets to design an effective peptide-based vaccine against dengue virus. Molecular docking analysis indicated the deep binding of the identified epitopes in the binding groove of the most popular human MHC I allele (human leukocyte antigens [HLA] A*0201). The final vaccine construct was created by conjugating the B and T-cell identified epitopes using proper linkers and adding an appropriate adjuvant at the N-terminal. The characteristics of the new subunit vaccine demonstrated that the epitope-based vaccine was antigenic, non-toxic, stable, and soluble. Other physicochemical properties of the new designed construct including isoelectric point value, aliphatic index, and grand average of hydropathicity were biologically considerable. Molecular docking of the engineered vaccine with Toll-like receptor 2 (TLR2) model revealed the hydrophobic interaction between the adjuvant and the ligand binding regions in the hydrophobic channel of TLR2. The study results indicated the high potential capability of the new multi-epitope vaccine to induce cellular and humoral immune responses against the dengue virus. Further experimental tests are required to investigate the immune protection capacity of the new vaccine construct in animal models. Communicated by Ramaswamy H. Sarma.

Exploring NS3/4A, NS5A and NS5B proteins to design conserved subunit multi-epitope vaccine against HCV utilizing immunoinformatics approaches

Hepatitis C virus (HCV) vaccines, designed to augment specific T-cell responses, have been designated as an important aspect of effective antiviral treatment. However, despite the current satisfactory progress of these vaccines, extensive past efforts largely remained unsuccessful in mediating clinically relevant anti-HCV activity in humans. In this study, we used a series of immunoinformatics approaches to propose a multiepitope vaccine against HCV by prioritizing 16 conserved epitopes from three viral proteins (i.e., NS34A, NS5A, and NS5B). The prioritised epitopes were tested for their possible antigenic combinations with each other along with linker AAY using structural modelling and epitope-epitope interactions analysis. An adjuvant (β-defensin) at the N-terminal of the construct was added to enhance the immunogenicity of the vaccine construct. Molecular dynamics (MD) simulation revealed the most stable structure of the proposed vaccine. The designed vaccine is potentially antigenic in nature and can form stable and significant interactions with Toll-like receptor 3 and Toll-like receptor 8. The proposed vaccine was also subjected to an in silico cloning approach, which confirmed its expression efficiency. These analyses suggest that the proposed vaccine can elicit specific immune responses against HCV; however, experimental validation is required to confirm the safety and immunogenicity profile of the proposed vaccine construct.

Immunoinformatics-aided design of a potential multi-epitope peptide vaccine against Leishmania infantum

Visceral leishmaniasis (VL) or kala-azar, the most severe form of the disease, is endemic in more than eighty countries across the world. To date, there is no approved vaccine against VL in the market. Recent advances in reverse vaccinology could be promising approach in designing the efficient vaccine for VL treatment. In this study, an efficient multi-epitope vaccine against Leishmania infantum, the causative agent of VL, was designed using various computational vaccinology methods. Potential immunodominant epitopes were selected from four antigenic proteins, including histone H1, sterol 24-c-methyltransferase (SMT), Leishmania-specific hypothetical protein (LiHy), and Leishmania-specific antigenic protein (LSAP). To enhance vaccine immunogenicity, two resuscitation-promoting factor of Mycobacterium tuberculosis, RpfE and RpfB, were employed as adjuvants. All the aforesaid segments were joined using proper linkers. Homology modeling, followed by refinement and validation was performed to obtain a high-quality 3D structure of designed vaccine. Docking analyses and molecular dynamics (MD) studies indicated vaccine/TLR4 complex was in the stable form during simulation time. In sum, we expect our designed vaccine is able to induce humoral and cellular immune responses against L. infantum, and may be promising medication for VL, after in vitro and in vivo immunological assays.

H1N1 influenza virus epitopes classified by monoclonal antibodies

Epitopes serve an important role in influenza infection. It may be useful to screen universal influenza virus vaccines, analyzing the epitopes of multiple subtypes of the hemagglutinin (HA) protein. A total of 40 monoclonal antibodies (mAbs) previously obtained from flu virus HA antigens (development and characterization of 40 mAbs generated using H1N1 influenza virus split vaccines were previously published) were used to detect and classify mAbs into distinct flu virus sub-categories using the ELISA method. Following this, the common continuous amino acid sequences were identified by multiple sequence alignment analysis with the GenBank database and DNAMAN software, for use in predicting the epitopes of the HA protein. Synthesized peptides of these common sequences were prepared, and used to verify and determine the predicted linear epitopes through localization and distribution analyses. With these methods, nine HA linear epitopes distributed among different strains of influenza virus were identified, which included three from influenza A, four from 2009 H1N1 and seasonal influenza, and two from H1. The present study showed that considering a combination of the antigen-antibody reaction specificity, variation in the influenza virus HA protein and linear epitopes may present a useful approach for designing effective multi-epitope vaccines. Furthermore, the study aimed to clarify the cause and pathogenic mechanism of influenza virus HA-induced flu, and presents a novel idea for identifying the epitopes of other pathogenic microorganisms.

A survey on chimeric UreB229-561-HpaA protein targeting Helicobacter pylori: Computational and in vitro urease activity valuation

Helicobacter pylori (H. pylori) as microaerophilic, Gram-negative bacterium colonize the human gastric milieu, where it impetuses chronic disorders. Vaccination is a complementary plan, along with antibiotic therapy, for clearance of H. pylori. Today, Computer based tools are essential for the evaluation, design, and experiment for novel chimeric targets for immunological administration. The purpose of this experiment was immunoinformatic analysis of UreB and HpaA molecules in a fusion arrangement and also, construction and expression of recombinant protein containing chimeric sequences. The targets sequences were screened by using of standard in silico tools and immunoinformatic web servers. The high-resolution 3D models of the protein were created and were validated; indeed, the B-and T-cell restricted epitopes were mapped on the chimeric protein. The recombinant protein in frame of the expression vector pET28a were expressed and purified successfully. The urease activity and immunoblotting were performed in vitro condition. This study confirmed that the engineered protein as a highly conserved, hydrophilic, non-allergenic contained remarkable B-cell and T-cell epitopes. It was magnificently attained; chimeric UreB_229-561-HpaA could provoke both humoral and cellular immunity. The immunoblotting was shown that the chimeric protein could be detected by serum of immunized animal and H.pylori positive patients. In this study, several antigenic patches from UreB and HpaA were identified that could be an efficient immune system activator. The in vitro analysis of our chimeric molecule confirmed its urease activity. It also confirmed that the chimeric protein could be detected by serum of immunized animal and H.pylori positive patients.

Deep analysis of N-cadherin/ADH-1 interaction: a computational survey

Due to the considerable role of N-cadherin in cancer metastasis, tumor growth, and progression, inhibition of this protein has been highly regarded in recent years. Although ADH-1 has been known as an appropriate inhibitor of N-cadherin in clinical trials, its chemical nature and binding mode with N-cadherin have not been precisely specified yet. Accordingly, in this study, quantum mechanics calculations were used to investigate the chemical nature of ADH-1. These calculations clarify the molecular properties of ADH-1 and determine its reactive sites. Based on the results, the oxygen atoms are suitable for electrophilic reactivity, while the hydrogen atoms that are connected to nitrogen atoms are the favorite sites for nucleophilic reactivity. The higher electronegativity of the oxygen atoms makes them the most reactive portions in this molecule. Molecular docking and molecular dynamics (MD) simulation have also been applied to specify the binding mode of ADH-1 with N-cadherin and determine the important residues of N-cadherin involving in the interaction with ADH-1. Moreover, the verified model by MD simulation has been studied to extract the free energy value and find driving forces. These calculations and molecular electrostatic potential map of ADH-1 indicated that hydrophobic and electrostatic interactions are almost equally involved in the implantation of ADH-1 in the N-cadherin binding site. The presented results not only enable a closer examination of N-cadherin in complex with ADH-1 molecule, but also are very beneficial in designing new inhibitors for N-cadherin and can help to save time and cost in this field.

Proteome-scale identification of Leishmania infantum for novel vaccine candidates: A hierarchical subtractive approach

Vaccines are one of the most significant achievements in medical science. However, vaccine design is still challenging at all stages. The selection of antigenic peptides as vaccine candidates is the first and most important step for vaccine design. Experimental selection of antigenic peptides for the design of vaccines is a time-consuming, labor-intensive and expensive procedure. More recently, in the light of computer-aided biotechnology and reverse vaccinology, the precise selection of antigenic peptides and rational vaccine design against many pathogens have developed. In this study, the whole proteome of Leishmania infantum was analyzed using a pipeline of algorithms. From the set of 8045 proteins of L. infantum, sixteen novel antigenic proteins were derived using a hierarchical proteome subtractive analysis. These novel vaccine targets can be utilized as top candidates for designing the new prophylactic or therapeutic vaccines against visceral leishmaniasis. Significantly, all the sixteen novel vaccine candidates are non-allergen antigenic proteins that have not been used for the design of vaccines against visceral leishmaniasis until now.

Helicobacter: Inflammation, immunology and vaccines

Helicobacter pylori is usually acquired in early childhood and the infection persists lifelong without causing symptoms. In a small of cases, the infection leads to gastric or duodenal ulcer disease, or gastric cancer. Why disease occurs in these individuals remains unclear, however the host response is known to play a very important part. Understanding the mechanisms involved in maintaining control over the immune and inflammatory response is therefore extremely important. Vaccines against H. pylori have remained elusive but are desperately needed for the prevention of gastric carcinogenesis. This review focuses on research findings which may prove useful in the development of prognostic tests for gastric cancer development, therapeutic agents to control immunopathology, and effective vaccines.

Harnessing self-assembled peptide nanoparticles in epitope vaccine design

Vaccination has been one of the most successful breakthroughs in medical history. In recent years, epitope-based subunit vaccines have been introduced as a safer alternative to traditional vaccines. However, they suffer from limited immunogenicity. Nanotechnology has shown value in solving this issue. Different kinds of nanovaccines have been employed, among which virus-like nanoparticles (VLPs) and self-assembled peptide nanoparticles (SAPNs) seem very promising. Recently, SAPNs have attracted special interest due to their unique properties, including molecular specificity, biodegradability, and biocompatibility. They also resemble pathogens in terms of their size. Their multivalency allows an orderly repetitive display of antigens on their surface, which induces a stronger immune response than single immunogens. In vaccine design, SAPN self-adjuvanticity is regarded an outstanding advantage, since the use of toxic adjuvants is no longer required. SAPNs are usually composed of helical or β-sheet secondary structures and are tailored from natural peptides or de novo structures. Flexibility in subunit selection opens the door to a wide variety of molecules with different characteristics. SAPN engineering is an emerging area, and more novel structures are expected to be generated in the future, particularly with the rapid progress in related computational tools. The aim of this review is to provide a state-of-the-art overview of self-assembled peptide nanoparticles and their use in vaccine design in recent studies. Additionally, principles for their design and the application of computational approaches to vaccine design are summarized.

Exploring dengue genome to construct a multi-epitope based subunit vaccine by utilizing immunoinformatics approach to battle against dengue infection

Dengue is considered as a major health issue which causes a number of deaths worldwide each year; tropical countries are majorly affected by dengue outbreaks. It is considered as life threatening issue because, since many decades not a single effective approach for treatment and prevention of dengue has been developed. Therefore, to find new preventive measure, we used immunoinformatics approaches to develop a multi-epitope based subunit vaccine for dengue which can generate various immune responses inside the host. Different B-cell, TC cell, and TH cell binding epitopes were predicted for structural and non-structural proteins of dengue virus. Final vaccine constructs consisting of TC and TH cell epitopes and an adjuvant (β-defensin) at N-terminal of the construct. Presence of B-cell and IFN-γ inducing epitopes confirms the humoral and cell mediated immune response developed by designed vaccine. Designed vaccine was not found allergic and was potentially antigenic in nature. Modeling of tertiary structure and the refined model was used for molecular docking with TLR-3 (immune receptor). Molecular docking and dynamics simulation confirms the microscopic interactions between ligand and receptor. In silico cloning approach was used to ensure the expression and translation efficiency of vaccine within an expression vector.