In silico construction of a multiepitope Zika virus vaccine using immunoinformatics tools

From defense to offense: Modulating toll-like receptors to combat arbovirus infections

Arboviruses are a significant threat to global public health, with outbreaks occurring worldwide. Toll-like receptors (TLRs) play a crucial role in the innate immune response against these viruses by recognizing pathogen-associated molecular patterns and initiating an inflammatory response. Significantly, TLRs commonly implicated in the immune response against viral infections include TLR2, TLR4, TLR6, TLR3, TLR7, and TLR8; limiting or allowing them to replicate and spread within the host. Modulating TLRs has emerged as a promising approach to combat arbovirus infections. This review summarizes recent advances in TLR modulation as a therapeutic target in arbovirus infections. Studies have shown that the activation of TLRs can enhance the immune response against arbovirus infections, leading to increased viral clearance and protection against disease. Conversely, inhibition of TLRs can reduce the excessive inflammation and tissue damage associated with arbovirus infection. Modulating TLRs represents a potential therapeutic strategy to combat arbovirus infections.

Dominant B cell-T cell epitopes instigated robust immune response in-silico against Scrub Typhus

Scrub typhus, a potentially life-threatening infectious disease, is attributed to bacteria Orientia tsutsugamushi (O. tsutsugamushi). The transmission of this illness to humans occurs through the bite of infected chiggers, which are the larval forms of mites belonging to the genus Leptotrombidium. In this research, we developed a subunit vaccine specifically designed to target outer membrane proteins. Immunodominant cytotoxic T-lymphocytes (CTLs), B- lymphocytes (BCLs), and major histocompatibility complex (MHC)- II epitopes were identified using machine learning and bioinformatics approaches. These epitopes were arranged in different combinations with the help of suitable linkers like AAY, KK, GPGPG and adjuvant (cholera toxin B) that resulted in a vaccine construct. Physiochemical properties were assessed, where the predicted solubility (0.571) was higher than threshold value. Tertiary structure was predicted using I-TASSER web server and evaluated using Ramachandran plot (94 % residues in most favourable region) and z-score (-6.04), which had shown the structure to have good stability and residue arrangement. Molecular docking with immune receptors, Toll-like receptor (TLR)-2 and -4 showed good residue interaction with 13 and 5 hydrogen bonds respectively. Molecular dynamics simulations of receptor-ligand complex provided the idea about the strong interaction having 1.524751 × 10-5 eigenvalue. Amino acid sequence of vaccine was converted to nucleotide sequence and underwent codon optimization. The optimized codon sequence was used for in-silico cloning, which provided idea about the possibility of synthesis of vaccine using E. coli as host. Overall, this study provided a promising blueprint for a scrub typhus vaccine, although experimental validation is needed for confirmation. Furthermore, it is crucial to acknowledge that while bioinformatics provides valuable insights, in-vitro and in-vivo studies are imperative for a comprehensive evaluation of vaccine candidate. Thus, the integration of computational predictions with empirical research is essential to validate the efficacy, safety, and real-world applicability of the designed vaccine against Scrub Typhus. Nevertheless, the findings are good to carry forward for in-vitro and in-vivo investigations.

Integrating pan-genome and reverse vaccinology to design multi-epitope vaccine against Herpes simplex virus type-1

Herpes simplex virus type-1 (HSV-1), the etiological agent of sporadic encephalitis and recurring oral (sometimes genital) infections in humans, affects millions each year. The evolving viral genome reduces susceptibility to existing antivirals and, thus, necessitates new therapeutic strategies. Immunoinformatics strategies have shown promise in designing novel vaccine candidates in the absence of a clinically licensed vaccine to prevent HSV-1. However, to encourage clinical translation, the HSV-1 pan-genome was integrated with the reverse-vaccinology pipeline for rigorous screening of universal vaccine candidates. Viral targets were screened from 104 available complete genomes. Among 364 proteins, envelope glycoprotein D being an outer membrane protein with a high antigenicity score (> 0.4) and solubility (> 0.6) was selected for epitope screening. A total of 17 T-cell and 4 B-cell epitopes with highly antigenic, immunogenic, non-toxic properties and high global population coverage were identified. Furthermore, 8 vaccine constructs were designed using different combinations of epitopes and suitable linkers. VC-8 was identified as the most potential vaccine candidate regarding chemical and structural stability. Molecular docking revealed high interactive affinity (low binding energy: - 56.25 kcal/mol) of VC-8 with the target elicited by firm intermolecular H-bonds, salt-bridges, and hydrophobic interactions, which was validated with simulations. Compatibility of the vaccine candidate to be expressed in pET-29(a) + plasmid was established by in silico cloning studies. Immune simulations confirmed the potential of VC-8 to trigger robust B-cell, T-cell, cytokine, and antibody-mediated responses, thereby suggesting a promising candidate for the future of HSV-1 prevention.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-024-04022-6.

Rational design and production of a chimeric antigen targeting Zika virus that induces neutralizing antibodies in mice

The Zika virus (ZIKV) is considered a public health problem worldwide due to its association with the development of microcephaly and the Guillain-Barré syndrome. Currently, there is no specific treatment or vaccine approved to combat this disease, and thus, developing safe and effective vaccines is a relevant goal. In this study, a multi-epitope protein called rpZDIII was designed based on a series of ZIKV antigenic sequences, a bacterial carrier, and linkers. The analysis of the predicted 3D structure of the rpZDIII chimeric antigen was performed on the AlphaFold 2 server, and it was produced in E. coli and purified from inclusion bodies, followed by solubilization and refolding processes. The yield achieved for rpZDIII was 11 mg/L in terms of pure soluble recombinant protein per liter of fermentation. rpZDIII was deemed immunogenic since it induced serum IgG and IgM responses in mice upon subcutaneous immunization in a three-dose scheme. Moreover, sera from mice immunized with rpZDIII showed neutralizing activity against ZIKV. Therefore, this study reveals rpZDIII as a promising immunogen for the development of a rationally designed multi-epitope vaccine against ZIKV, and completion of its preclinical evaluation is guaranteed.

Decrypting the multi-genome data for chimeric vaccine designing against the antibiotic resistant Yersinia pestis

Yersinia pestis, the causative agent of plague, is a gram-negative bacterium that can be fatal if not treated properly. Three types of plague are currently known: bubonic, septicemic, and pneumonic plague, among which the fatality rate of septicemic and pneumonic plague is very high. Bubonic plague can be treated, but only if antibiotics are used at the initial stage of the infection. But unfortunately, Y. pestis has also shown resistance to certain antibiotics such as kanamycin, minocycline, tetracycline, streptomycin, sulfonamides, spectinomycin, and chloramphenicol. Despite tremendous progress in vaccine development against Y. pestis, there is no proper FDA-approved vaccine available to protect people from its infections. Therefore, effective broad-spectrum vaccine development against Y. pestis is indispensable. In this study, vaccinomics-assisted immunoinformatics techniques were used to find possible vaccine candidates by utilizing the core proteome prepared from 58 complete genomes of Y. pestis. Human non-homologous, pathogen-essential, virulent, and extracellular and membrane proteins are potential vaccine targets. Two antigenic proteins were prioritized for the prediction of lead epitopes by utilizing reverse vaccinology approaches. Four vaccine designs were formulated using the selected B- and T-cell epitopes coupled with appropriate linkers and adjuvant sequences capable of inducing potent immune responses. The HLA allele population coverage of the T-cell epitopes selected for vaccine construction was also analyzed. The V2 constructs were top-ranked and selected for further analysis on the basis of immunological, physicochemical, and immune-receptor docking interactions and scores. Docking and molecular dynamic simulations confirmed the stability of construct V2 interactions with the host immune receptors. Immune simulation analysis anticipated the strong immune profile of the prioritized construct. In silico restriction cloning ensured the feasible cloning ability of the V2 construct in the expression system of E. coli strain K12. It is anticipated that the designed vaccine construct may be safe, effective, and able to elicit strong immune responses against Y. pestis infections and may, therefore, merit investigation using in vitro and in vivo assays.

Immunoinformatics design of a structural proteins driven multi-epitope candidate vaccine against different SARS-CoV-2 variants based on fynomer

The ideal vaccines for combating diseases that may emerge in the future require more than simply inactivating a few pathogenic strains. This study aims to provide a peptide-based multi-epitope vaccine effective against various severe acute respiratory syndrome coronavirus 2 strains. To design the vaccine, a library of peptides from the spike, nucleocapsid, membrane, and envelope structural proteins of various strains was prepared. Then, the final vaccine structure was optimized using the fully protected epitopes and the fynomer scaffold. Using bioinformatics tools, the antigenicity, allergenicity, toxicity, physicochemical properties, population coverage, and secondary and three-dimensional structures of the vaccine candidate were evaluated. The bioinformatic analyses confirmed the high quality of the vaccine. According to further investigations, this structure is similar to native protein and there is a stable and strong interaction between vaccine and receptors. Based on molecular dynamics simulation, structural compactness and stability in binding were also observed. In addition, the immune simulation showed that the vaccine can stimulate immune responses similar to real conditions. Finally, codon optimization and in silico cloning confirmed efficient expression in Escherichia coli. In conclusion, the fynomer-based vaccine can be considered as a new style in designing and updating vaccines to protect against coronavirus disease.

Reverse engineering protection: A comprehensive survey of reverse vaccinology-based vaccines targeting viral pathogens

Vaccines have significantly reduced the impact of numerous deadly viral infections. However, there is an increasing need to expedite vaccine development in light of the recurrent pandemics and epidemics. Also, identifying vaccines against certain viruses is challenging due to various factors, notably the inability to culture certain viruses in cell cultures and the wide-ranging diversity of MHC profiles in humans. Fortunately, reverse vaccinology (RV) efficiently overcomes these limitations and has simplified the identification of epitopes from antigenic proteins across the entire proteome, streamlining the vaccine development process. Furthermore, it enables the creation of multiepitope vaccines that can effectively account for the variations in MHC profiles within the human population. The RV approach offers numerous advantages in developing precise and effective vaccines against viral pathogens, including extensive proteome coverage, accurate epitope identification, cross-protection capabilities, and MHC compatibility. With the introduction of RV, there is a growing emphasis among researchers on creating multiepitope-based vaccines aiming to stimulate the host's immune responses against multiple serotypes, as opposed to single-component monovalent alternatives. Regardless of how promising the RV-based vaccine candidates may appear, they must undergo experimental validation to probe their protection efficacy for real-world applications. The time, effort, and resources allocated to the laborious epitope identification process can now be redirected toward validating vaccine candidates identified through the RV approach. However, to overcome failures in the RV-based approach, efforts must be made to incorporate immunological principles and consider targeting the epitope regions involved in disease pathogenesis, immune responses, and neutralizing antibody maturation. Integrating multi-omics and incorporating artificial intelligence and machine learning-based tools and techniques in RV would increase the chances of developing an effective vaccine. This review thoroughly explains the RV approach, ideal RV-based vaccine construct components, RV-based vaccines designed to combat viral pathogens, its challenges, and future perspectives.

Rational design of B-cell and T-cell multi epitope-based vaccine against Zika virus, an in silico study

The Zika virus (ZKV) is a single-stranded positive-sense, enveloped RNA virus. Zika infection during pregnancy can cause congenital microcephaly, Guillain-Barré syndrome, miscarriage, and other CNS abnormalities. The world needs safe and effective vaccinations to fight against ZIKV infection since vaccination is generally regarded as one of the most effective ways to prevent infectious diseases. In the present work, we used immunoinformatics and docking studies to construct a vaccine containing multi-epitopes using the structural and non-structural proteins of ZKV. The structural models of ZKV proteins (PrE, PrM, NS1, and NS2A) were constructed using Pyre2 and RaptorX servers. The epitopes of B-cell, T-cell (HTL and CTL), and IFN-γ were predicted, and each epitope's immunogenic nature and physiochemical properties were confirmed. As an adjuvant, the CPG-Oligodeoxynucleotide, an agonist of Toll-like receptor 9 (TLR9), is associated to cytotoxic T-lymphocytes (CTL) epitopes via PAPAP linker. To assess the binding affinity and the tendency of the designed vaccine to induce an immune response through TLR9, molecular docking was done. In the next step, molecular dynamics (MD) simulation to 100 nanoseconds (ns) was used to evaluate the stability of the interaction of the designed vaccine with TLR9. The designed vaccine is predicted to be highly antigenic, non-toxic, soluble, and stable with low flexibility in MD simulation. MD studies indicated that the finalized vaccine-TLR9 docked complex was stable during simulation time. The vaccine construct is able to stimulate both humoral and cellular immune responses. We suppose that our constructed model of the vaccine may have the ability to induce the host immune response against ZKV. Further studies, including in vitro and in vivo experimental analyses, are needed to prove the constructed vaccine's efficacy with multi-epitopes.Communicated by Ramaswamy H. Sarma.

Zika virus precursor membrane peptides induce immune response in peripheral blood mononuclear cells

Zika virus is a re-merging flavivirus allied to serious mental health conditions in the fetuses. There is currently no preventives or treatment available for Zika infection. In this work, we have extended the in silico analysis by performing the molecular docking of previous reported three conserved Zika virus precursor membrane (prM) peptides (MP1, MP2 and MP3) with HLA complex (pHLA) and T cell receptors (TCR) and also evaluated the peptide specific immune response in human peripheral blood mononuclear cells (PBMC). Most of the CD8+ and CD4+ T cell peptides-HLA complexes demonstrated good binding energies (ΔG) and HADDOCK scores in molecular docking analysis. Immunogenic response of peptides is measured as human peripheral blood mononuclear cell (PBMC) proliferation and interferon-gamma (IFN-γ) production using a 3-(4,5- dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) assay and a sandwich enzyme-linked immunosorbent assay (ELISA) respectively on ten different healthy blood samples. Peptide MP3 exhibited significant results in eight (cell proliferation) and seven (IFN-γ secretion) healthy volunteers' blood samples out of ten. Additionally, peptides MP1 and MP2 presented significant cell proliferation and IFN-γ release in six healthy blood samples. Thus, the outcomes from in silico and in vitro studies showed the immunogenic potential of peptides which need to validated in different experimental system before considering as candidate vaccine against Zika virus infection.

An immunoinformatics and structural vaccinology approach to design a novel and potent multi-epitope base vaccine targeting Zika virus

Zika virus is an infectious virus, that belongs to Flaviviridae family, which is transferred to humans through mosquito vectors and severely threatens human health; but, apart from available resources, no effective and secure vaccine is present against Zika virus, to prevent such infections. In current study, we employed structural vaccinology approach to design an epitope-based vaccine against Zika virus, which is biocompatible, and secure and might trigger an adaptive and innate immune response by using computational approaches. We first retrieved the protein sequence from National Center for Biotechnology Information (NCBI) database and carried out for BLAST P. After BLAST P, predicted protein sequences were shortlisted and checked for allergic features and antigenic properties. Final sequence of Zika virus, with accession number (APO40588.1) was selected based on high antigenic score and non-allergenicity. Final protein sequence used various computational approaches including antigenicity testing, toxicity evaluation, allergenicity, and conservancy assessment to identify superior B-cell and T-cell epitopes. Two B-cell epitopes, five MHC-six MHC-II epitopes and I were used to construct an immunogenic multi-epitope-based vaccine by using suitable linkers. A 50S ribosomal protein was added at N terminal to improve the immunogenicity of vaccine. In molecular docking, strong interactions were presented between constructed vaccine and Toll-like receptor 9 (- 1100.6 kcal/mol), suggesting their possible relevance in the immunological response to vaccine. The molecular dynamics simulations ensure the dynamic and structural stability of constructed vaccine. The results of C-immune simulation revealed that constructed vaccine activate B and T lymphocytes which induce high level of antibodies and cytokines to combat Zika infection. The constructed vaccine is an effective biomarker with non-sensitization, nontoxicity; nonallergic, good immunogenicity, and antigenicity, however, experimental assays are required to verify the results of present study.

Computational identification of a multi-peptide vaccine candidate in E2 glycoprotein against diverse Hepatitis C virus genotypes

Hepatitis C Virus (HCV) is estimated to affect nearly 180 million people worldwide, culminating in ∼0.7 million yearly casualties. However, a safe vaccine against HCV is not yet available. This study endeavored to identify a multi-genotypic, multi-epitopic, safe, and globally competent HCV vaccine candidate. We employed a consensus epitope prediction strategy to identify multi-epitopic peptides in all known envelope glycoprotein (E2) sequences, belonging to diverse HCV genotypes. The obtained peptides were screened for toxicity, allergenicity, autoimmunity and antigenicity, resulting in two favorable peptides viz., P2 (VYCFTPSPVVVG) and P3 (YRLWHYPCTV). Evolutionary conservation analysis indicated that P2 and P3 are highly conserved, supporting their use as part of a designed multi-genotypic vaccine. Population coverage analysis revealed that P2 and P3 are likely to be presented by >89% Human Leukocyte Antigen (HLA) molecules from six geographical regions. Indeed, molecular docking predicted the physical binding of P2 and P3 to various representative HLAs. We designed a vaccine construct using these peptides and assessed its binding to toll-like receptor 4 (TLR-4) by molecular docking and simulation. Subsequent analysis by energy-based and machine learning tools predicted high binding affinity and pinpointed the key binding residues (i.e. hotspots) in P2 and P3. Also, a favorable immunogenic profile of the construct was predicted by immune simulations. We encourage the scientific community to validate our vaccine construct in vitro and in vivo.Communicated by Ramaswamy H. Sarma.

Immunoinformatics-Based Identification of the Conserved Immunogenic Peptides Targeting of Zika Virus Precursor Membrane Protein

Zika virus infections lead to neurological complications such as congenital Zika syndrome and Guillain-Barré syndrome. Rising Zika infections in newborns and adults have triggered the need for vaccine development. In the current study, the precursor membrane (prM) protein of the Zika virus is explored for its functional importance and design of epitopes enriched conserved peptides with the usage of different immunoinformatics approach. Phylogenetic and mutational analyses inferred that the prM protein is highly conserved. Three conserved peptides containing multiple T and B cell epitopes were designed by employing different epitope prediction algorithms. IEDB population coverage analysis of selected peptides in six different continents has shown the population coverage of 60-99.8% (class I HLA) and 80-100% (class II HLA). Molecular docking of selected peptides/epitopes was carried out with each of class I and II HLA alleles using HADDOCK. A majority of peptide-HLA complex (pHLA) have HADDOCK scores found to be comparable and more than native-HLA complex representing the good binding interaction of peptides to HLA. Molecular dynamics simulation with best docked pHLA complexes revealed that pHLA complexes are stable with RMSD <5.5Å. Current work highlights the importance of prM as a strong antigenic protein and selected peptides have the potential to elicit humoral and cell-mediated immune responses.

Immunoinformatic and reverse vaccinology-based designing of potent multi-epitope vaccine against Marburgvirus targeting the glycoprotein

Marburg virus (MARV) has been a major concern since its first outbreak in 1967. Although the deadly BSL-4 pathogen has been reported in few individuals with sporadic outbreaks following 1967, its rarity commensurate the degree of disease severity. The virus has been known to cause extreme hemorrhagic fever presenting flu-like symptoms (as implicated in COVID-19) with a 90% case fatality rate (CFR). After a number of plausible evidences, it has been observed that the virus usually originates from African fruit bat, Rousettus aegyptiacus, who themselves do not indicate any signs of illness. Thus, efforts have been made in the recent years for a universal treatment of the infection, but till date, no such vaccine or therapeutics could circumvent the viral pathogenicity. In an attempt to formulate a vaccine design computationally, we have explored the entire proteome of the virus and found a strong correlation of its glycoprotein (GP) in receptor binding and subsequent role in infection progression. The present study, explores the MARV glycoprotein GP1 and GP2 domains for quality epitopes to elicit an extended immune response design potential vaccine construct using appropriate linkers and adjuvants. Finally, the chimeric vaccine wass evaluated for its binding affinity towards the receptors via molecular docking and molecular dynamics simulation studies. The rare, yet deadly zoonotic infection with mild outbreaks in recent years has flustered an alarming future with various challenges in terms of viral diseases. Thus, our study has aimed to provide novel insights to design potential vaccines by using the predictive framework.

Whole Yeast Vaccine Displaying ZIKV B and T Cell Epitopes Induces Cellular Immune Responses in the Murine Model

Improving antigen presentation is crucial for the success of immunization strategies. Yeasts are classically used as biofactories to produce recombinant proteins and are efficient vehicles for antigen delivery, in addition to their adjuvant properties. Despite the absence of epidemic outbreaks, several vaccine approaches continue to be developed for Zika virus infection. The development of these prophylactic strategies is fundamental given the severity of clinical manifestations, mainly due to viral neurotropism. The present study aimed to evaluate in vivo the immune response induced by P. pastoris recombinant strains displaying epitopes of the envelope (ENV) and NS1 ZIKV proteins. Intramuscular immunization with heat-attenuated yeast enhanced the secretion of IL-6, TNF-α, and IFN-γ, in addition to the activation of CD4⁺ and CD8⁺ T cells, in BALB/c mice. P. pastoris displaying ENV epitopes induced a more robust immune response, increasing immunoglobulin production, especially IgG isotypes. Both proposed vaccines showed the potential to induce immune responses without adverse effects, confirming the safety of administering P. pastoris as a vaccine vehicle. Here, we demonstrated, for the first time, the evaluation of a vaccine against ZIKV based on a multiepitope construct using yeast as a delivery system and reinforcing the applicability of P. pastoris as a whole-cell vaccine.

Immunoinformatic prediction of the pathogenicity of bovine viral diarrhea virus genotypes: implications for viral virulence determinants, designing novel diagnostic assays and vaccines development

Introduction

Bovine viral diarrhea virus (BVDV) significantly impacts the bovine industries, both dairy and beef sectors. BVDV can infect various domestic and wild animals, most notably cattle. The dynamic variations among BVDV serotypes due to the continuous genetic diversity, especially in BVDV1 (BVDV1), reduce the effectiveness of the currently available vaccines and reduce the specificity/sensitivity of the diagnostic assays. The development of novel, safe, and effective vaccines against BVDV requires deep knowledge of the antigenicity and virulence of the virus. Previous studies on the antigenicity and the virulence of BVDV serotypes have been mainly focused on one or a few BVDV proteins. While however, little is known about the orchestration of all BVDV in the context of viral virulence and immunogenicity. The main aim of the current study was to do a comparative computational evaluation of the immunogenicity, and virulence for all the encoded proteins of both BVDV1 and BVDV2 and their sub-genotypes.

Methods

To achieve this goal, 11,737 protein sequences were retrieved from Virus Pathogen Resource. The analysis involved a total of 4,583 sequences after the removal of short sequences and those with unknown collection time. We used the MP3 tool to map the pathogenic proteins across different BVDV strains. The potential protective and the epitope motifs were predicted using the VaxiJen and EMBOSS antigen tools, respectively.

Results and discussion

The virulence prediction revealed that the NS4B proteins of both BVDV1 and BVDV2 likely have essential roles in BVDV virulence. Similarly, both the capsid (C) and the NS4-A proteins of BVDV1 and the N^pro and P7 proteins of BVDV2 are likely important virulent factors. There was a clear trend of increasing predicted virulence with the progression of time in the case of BVDV1 proteins, but that was not the case for the BVDV2 proteins. Most of the proteins of the two BVDV serotypes possess antigens predicted immunogens except N^pro, P7, and NS4B. However, the predicted antigenicity of the BVDV1 was significantly higher than that of BVDV2. Meanwhile, the predicted immunogenicity of the immunodominant-E2 protein has been decreasing over time. Based on our predicted antigenicity and pathogenicity studies of the two BVDV serotypes, the sub-genotypes (1a, 1f, 1k, 2a, and 2b) may represent ideal candidates for the development of future vaccines against BVDV infection in cattle. In summary, we identified some common differences between the two BVDV genotypes (BVDV1 and BVDV2) and their sub-genotypes regarding their protein antigenicity and pathogenicity. The data presented here will increase our understanding of the molecular pathogenesis of BVDV infection in cattle. It will also pave the way for developing some novel diagnostic assays and novel vaccines against BVDV in the near future.

Immunoinformatics Vaccine Design for Zika Virus

Zika virus (ZIKV) is an emerging virus from the Flaviviridae family and Flavivirus genus that has caused important outbreaks around the world. ZIKV infection is associated with severe neuropathology in newborns and adults. Until now, there is no licensed vaccine available for ZIKV infection. Therefore, the development of a safe and effective vaccine against ZIKV is an urgent need. Recently, we designed an in silico multi-epitope vaccine for ZIKV based on immunoinformatics tools. To construct this in silico ZIKV vaccine, we used a consensus sequence generated from ZIKV sequences available in databank. Then, we selected CD4+ and CD8+ T cell epitopes from all ZIKV proteins based on the binding prediction to class II and class I human leukocyte antigen (HLA) molecules, promiscuity, and immunogenicity. ZIKV Envelope protein domain III (EDIII) was added to the construct and B cell epitopes were identified. Adjuvants were associated to increase immunogenicity. Distinct linkers were used for connecting the CD4+ and CD8+ T cell epitopes, EDIII, and adjuvants. Several analyses, such as antigenicity, population coverage, allergenicity, autoimmunity, and secondary and tertiary structures of the vaccine, were evaluated using various immunoinformatics tools and online web servers. In this chapter, we present the protocols with the rationale and detailed steps needed for this in silico multi-epitope ZIKV vaccine design.

Multi-Epitope Vaccine for Monkeypox Using Pan-Genome and Reverse Vaccinology Approaches

Outbreaks of monkeypox virus infections have imposed major health concerns worldwide, with high morbidity threats to children and immunocompromised adults. Although repurposed drugs and vaccines are being used to curb the disease, the evolving traits of the virus, exhibiting considerable genetic dynamicity, challenge the limits of a targeted treatment. A pan-genome-based reverse vaccinology approach can provide fast and efficient solutions to resolve persistent inconveniences in experimental vaccine design during an outbreak-exigency. The approach encompassed screening of available monkeypox whole genomes (n = 910) to identify viral targets. From 102 screened viral targets, viral proteins L5L, A28, and L5 were finalized based on their location, solubility, and antigenicity. The potential T-cell and B-cell epitopes were extracted from the proteins using immunoinformatics tools and algorithms. Multiple vaccine constructs were designed by combining the epitopes. Based on immunological properties, chemical stability, and structural quality, a novel multi-epitopic vaccine construct, V4, was finalized. Flexible-docking and coarse-dynamics simulation portrayed that the V4 had high binding affinity towards human HLA-proteins (binding energy < -15.0 kcal/mol) with low conformational fluctuations (<1 Å). Thus, the vaccine construct (V4) may act as an efficient vaccine to induce immunity against monkeypox, which encourages experimental validation and similar approaches against emerging viral infections.

Vaccines against Emerging and Neglected Infectious Diseases: An Overview

Neglected Tropical Diseases (NTDs) are a group of diseases that are highly prevalent in tropical and subtropical regions, and closely associated with poverty and marginalized populations. Infectious diseases affect over 1.6 billion people annually, and vaccines are the best prophylactic tool against them. Along with NTDs, emerging and reemerging infectious diseases also threaten global public health, as they can unpredictably result in pandemics. The recent advances in vaccinology allowed the development and licensing of new vaccine platforms that can target and prevent these diseases. In this work, we discuss the advances in vaccinology and some of the difficulties found in the vaccine development pipeline for selected NTDs and emerging and reemerging infectious diseases, including HIV, Dengue, Ebola, Chagas disease, malaria, leishmaniasis, zika, and chikungunya.

In Silico Comparative Analysis of Predicted B Cell Epitopes against Dengue Virus (Serotypes 1–4) Isolated from the Philippines

Dengue is a viral mosquito-borne disease that rapidly spreads in tropical and subtropical countries, including the Philippines. One of its most distinguishing characteristics is the ability of the Dengue Virus (DENV) to easily surpass the innate responses of the body, thus activating B cells of the adaptive immunity to produce virus-specific antibodies. Moreover, Dengvaxia^® is the only licensed vaccine for DENV, but recent studies showed that seronegative individuals become prone to increased disease severity and hospitalization. Owing to this limitation of the dengue vaccine, this study determined and compared consensus and unique B cell epitopes among each DENV (1–4) Philippine isolate to identify potential areas of interest for future vaccine studies and therapeutic developments. An in silico-based epitope prediction of forty (40) DENV 1–4 strains, each serotype represented by ten (10) sequences from The National Center for Biotechnology Information (NCBI), was conducted using Kolaskar and Tongaonkar antigenicity, Emini surface accessibility, and Parker hydrophilicity prediction in Immune Epitope Database (IEDB). Results showed that five (5) epitopes were consensus for DENV-1 with no detected unique epitope, one (1) consensus epitope for DENV-2 with two (2) unique epitopes, one (1) consensus epitope for DENV-3 plus two (2) unique epitopes, and two (2) consensus epitopes and one (1) unique epitope for DENV-4. The findings of this study would contribute to determining potential vaccine and diagnostic marker candidates for further research studies and immunological applications against DENV (1–4) Philippine isolates.