Computational immunology meets bioinformatics: the use of prediction tools for molecular binding in the simulation of the immune system

Design and evaluation of a multi-epitope DNA vaccine against HPV16

Cervical cancer, among the deadliest cancers affecting women globally, primarily arises from persistent infection with high-risk human papillomavirus (HPV). To effectively combat persistent infection and prevent the progression of precancerous lesions into malignancy, a therapeutic HPV vaccine is under development. This study utilized an immunoinformatics approach to predict epitopes of cytotoxic T lymphocytes (CTLs) and helper T lymphocytes (HTLs) using the E6 and E7 oncoproteins of the HPV16 strain as target antigens. Subsequently, through meticulous selection of T-cell epitopes and other necessary elements, a multi-epitope vaccine was constructed, exhibiting good immunogenic, physicochemical, and structural characteristics. Furthermore, in silico simulations showed that the vaccine not only interacted well with toll-like receptors (TLR2/TLR3/TLR4), but also induced a strong innate and adaptive immune response characterized by elevated Th1-type cytokines, such as interferon-gamma (IFN-γ) and interleukin-2 (IL2). Additionally, our study investigated the effects of different immunization intervals on immune responses, aiming to optimize a time-efficient immunization program. In animal model experiments, the vaccine exhibited robust immunogenic, therapeutic, and prophylactic effects. Administered thrice, it consistently induced the expansion of specific CD4 and CD8 T cells, resulting in substantial cytokines release and increased proliferation of memory T cell subsets in splenic cells. Overall, our findings support the potential of this multi-epitope vaccine in combating HPV16 infection and signify its candidacy for future HPV vaccine development.

In silico design of a novel hybrid epitope-based antigen harboring highly exposed immunogenic peptides of BamA, OmpA, and Omp34 against Acinetobacter baumannii

Acinetobacter baumannii, is among the highest priority bacteria according to the WHO categorization which necessitate the exploration of alternative strategies such as vaccination. OmpA, BamA, and Omp34 are assigned as appropriate antigens to serve in vaccine development against this pathogen. Experimentally validated exposed epitopes of OmpA and Omp34 along with selected exposed epitopes predicted by an integrative in silico approach were represented by the barrel domain of BamA as a scaffold. Among the 8 external loops of BamA, 5 loops were replaced with selected loops of OmpA and Omp34. The designed antigen was analyzed regarding the physicochemical properties, antigenicity, epitope retrieval, topology, structure, and safety. BamA is a two-domain OMP with a 16-stranded barrel in which L4, L6, and L7 were the longest loops of BamA in order. The designed antigen consisted of 478 amino acids with antigen probability of 0.7793. The novel antigen was a 16-stranded barrel. No identical 8-meric peptides were found in the human proteome against the designed antigen sequence. The designed construct was safe regarding the allergenicity, toxicity, and human proteome reactivity. The designed antigen could develop higher protection against A. baumannii in comparison to either OmpA, BamA, or Omp34 alone.

Designing a multi-epitope subunit vaccine against Orf virus using molecular docking and molecular dynamics

Orf virus (ORFV) is an acute contact, epitheliotropic, zoonotic, and double-stranded DNA virus that causes significant economic losses in the livestock industry. The objective of this study is to design an immunoinformatics-based multi-epitope subunit vaccine against ORFV. Various immunodominant cytotoxic T lymphocytes (CTL), helper T lymphocytes (HTL), and B-cell epitopes from the B2L, F1L, and 080 protein of ORFV were selected and linked by short connectors to construct a multi-epitope subunit vaccine. Immunogenicity was enhanced by adding an adjuvant β-defensin to the N-terminal of the vaccine using the EAAAK linker. The vaccine exhibited a significant degree of antigenicity and solubility, without allergenicity or toxicity. The 3D formation of the vaccine was subsequently anticipated, improved, and verified. The optimized model exhibited a lower Z-score of -4.33, indicating higher quality. Molecular docking results demonstrated that the vaccine strongly binds to TLR2 and TLR4. Molecular dynamics results indicated that the docked vaccine-TLR complexes were stable. Immune simulation analyses further confirmed that the vaccine can induce a marked increase in IgG and IgM antibody titers, and elevated levels of IFN-γ and IL-2. Finally, the optimized DNA sequence of the vaccine was cloned into the vector pET28a (+) for high expression in the E.coli expression system. Overall, the designed multi-epitope subunit vaccine is highly stable and can induce robust humoral and cellular immunity, making it a promising vaccine candidate against ORFV.

Computational strategies in Klebsiella pneumoniae vaccine design: navigating the landscape of in silico insights

The emergence of multidrug-resistant Klebsiella pneumoniae poses a grave threat to global public health, necessitating urgent strategies for vaccine development. In this context, computational tools have emerged as indispensable assets, offering unprecedented insights into klebsiellal biology and facilitating the design of effective vaccines. Here, a review of the application of computational methods in the development of K. pneumoniae vaccines is presented, elucidating the transformative impact of in silico approaches. Through a systematic exploration of bioinformatics, structural biology, and immunoinformatics techniques, the complex landscape of K. pneumoniae pathogenesis and antigenicity was unravelled. Key insights into virulence factors, antigen discovery, and immune response mechanisms are discussed, highlighting the pivotal role of computational tools in accelerating vaccine development efforts. Advancements in epitope prediction, antigen selection, and vaccine design optimisation are examined, highlighting the potential of in silico approaches to update vaccine development pipelines. Furthermore, challenges and future directions in leveraging computational tools to combat K. pneumoniae are discussed, emphasizing the importance of multidisciplinary collaboration and data integration. This review provides a comprehensive overview of the current state of computational contributions to K. pneumoniae vaccine development, offering insights into innovative strategies for addressing this urgent global health challenge.

Rational design of a multi-epitope vaccine against heartland virus (HRTV) using immune-informatics, molecular docking and dynamics approaches

Heartland virus (HRTV) is a single-stranded negative-sense RNA virus that infects human beings. Because there are no antiviral medications available to treat HRTV infection, supportive care management is used in cases of severe disease. Therefore, it has spurred research into developing a multi-epitope vaccine capable of providing effective protection against HRTV infection. A multi-epitope vaccine was created using a combination of immuno-informatics, molecular docking and molecular dynamics simulation in this investigation. The HRTV proteome was utilized to predict B-cell, T-cell (HTL and CTL), and IFN-epitopes. Following prediction, highly antigenic, non-allergenic and immunogenic epitopes were chosen, including 6 CTL, 8 HTL, and 5 LBL epitopes that were connected to the final peptide by AAY, GPGPG, and KK linkers, respectively. An adjuvant was introduced to the vaccine's N-terminal through the EAAAK linker to increase its immunogenicity. Following the inclusion of linkers and adjuvant, the final construct has 359 amino acids. The presence of B-cell and IFN-γ-epitopes validates the construct's acquired humoral and cell-mediated immune responses. To ensure the vaccine's safety and immunogenicity profile, its allergenicity, antigenicity, and various physicochemical characteristics were assessed. Docking was used to assess the binding affinity and molecular interaction between the vaccination and TLR-3. In silico cloning was used to confirm the construct's validity and expression efficiency. The results of these computer assays demonstrated that the designed vaccine is highly promising in terms of developing protective immunity against HRTV; nevertheless, additional in vivo and in vitro investigations are required to validate its true immune-protective efficiency.

A review on the development of bacterial multi-epitope recombinant protein vaccines via reverse vaccinology

Bacterial vaccines play a crucial role in combating bacterial infectious diseases. Apart from the prevention of disease, bacterial vaccines also help to reduce the mortality rates in infected populations. Advancements in vaccine development technologies have addressed the constraints of traditional vaccine design, providing novel approaches for the development of next-generation vaccines. Advancements in reverse vaccinology, bioinformatics, and comparative proteomics have opened horizons in vaccine development. Specifically, the use of protein structural data in crafting multi-epitope vaccines (MEVs) to target pathogens has become an important research focus in vaccinology. In this review, we focused on describing the methodologies and tools for epitope vaccine development, along with recent progress in this field. Moreover, this article also discusses the challenges in epitope vaccine development, providing insights for the future development of bacterial multi-epitope genetically engineered vaccines.

Pangenome analysis of five representative Tropheryma whipplei strains following multiepitope-based vaccine design via immunoinformatic approaches

Whipple disease caused by Tropheryma whipplei a gram-positive bacterium is a systemic disorder that impacts not only the gastrointestinal tract but also the vascular system, joints, central nervous system, and cardiovascular system. Due to the lack of an approved vaccine, this study aimed to utilize immunoinformatic approaches to design multiepitope -based vaccine by utilizing the proteomes of five representative T. whipplei strains. The genomes initially comprised a total of 4,844 proteins ranging from 956 to 1012 proteins per strain. We collected 829 nonredundant lists of core proteins, that were shared among all the strains. Following subtractive proteomics, one extracellular protein, WP_033800108.1, a WhiB family transcriptional regulator, was selected for the chimeric-based multiepitope vaccine. Five immunodominant epitopes were retrieved from the WhiB family transcriptional regulator protein, indicating MHC-I and MHC-II with a global population coverage of 70.61%. The strong binding affinity, high solubility, nontoxicity, nonallergenic properties and high antigenicity scores make the selected epitopes more appropriate. Integration of the epitopes into a chimeric vaccine was carried out by applying appropriate adjuvant molecules and linkers, leading to the vaccine construct having enhanced immunogenicity and successfully eliciting both innate and adaptive immune responses. Moreover, the abilityof the vaccine to bind TLR4, a core innate immune receptor, was confirmed. Molecular dynamics simulations have also revealed the promising potential stability of the designed vaccine at 400 ns. In summary, we have designed a potential vaccine construct that has the ability not only to induce targeted immunogenicity for one strain but also for global T. whipplei strains. This study proposes a potential universal vaccine, reducing Whipple's disease risk and laying the groundwork for future research on multi-strain pathogens.

In-silico evaluation of the T-cell based immune response against SARS-CoV-2 omicron variants

During of COVID-19 pandemic, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has continuously evolved, resulting in the emergence of several new variants of concerns (VOCs) with numerous mutations. These VOCs dominate in various regions due to increased transmissibility and antibody evasion, potentially reducing vaccine effectiveness. Nonetheless, it remains uncertain whether the recent SARS-CoV-2 VOCs have the ability to circumvent the T cell immunity elicited by either COVID-19 vaccination or natural infection. To address this, we conducted in-silico analysis to examine the impact of VOC-specific mutations at the epitope level and T cell cross-reactivity with the ancestral SARS-CoV-2. According to the in-silico investigation, T cell responses triggered by immunization or prior infections still recognize the variants in spite of mutations. These variants are expected to either maintain their dominant epitope HLA patterns or bind with new HLAs, unlike the epitopes of the ancestral strain. Our findings indicate that a significant proportion of immuno-dominant CD8 + and CD4 + epitopes are conserved across all the variants, implying that existing vaccines might maintain efficacy against new variations. However, further in-vitro and in-vivo studies are needed to validate the in-silico results and fully elucidate immune sensitivities to VOCs.

Application of immunoinformatics to develop a novel and effective multiepitope chimeric vaccine against Variovorax durovernensis

Bloodstream infections pose a significant public health challenge caused by resistant bacteria such as Variovorax durovernensis, a recently reported Gram-negative bacterium, worsening the burden on healthcare systems. The design of a vaccine using chimeric peptides derived from a representative V. durovernensis strain holds significant promise for preventing disease onset. The current study aimed to employ reverse vaccinology (RV) approaches such as the retrieval of V. durovernensis proteomics data, removal of redundant proteins by CD-HIT, filtering of non-homologous proteins to humans and essential proteins, identification of outer membrane (OM) proteins by CELLO and PSORTb. Following these steps immunoinformatic approaches were applied, such as epitope prediction by IEDB, vaccine design using linkers and adjuvant and analysis of antigenicity, allergenicity, safety and stability. Among the 4208 nonredundant proteins, an OmpA family protein (A0A940EKP4) was designated a potential candidate for the development of a multiepitope vaccine construct. Upon analysis of OM protein, six immunodominant (B cell) epitopes were found on the basis of the chimeric construct following the prediction of CTL stands cytotoxic T lymphocyte and HTL stands helper T lymphocyte epitopes. To ensure comprehensive population coverage globally, the CTL and HTL coverage rates were 58.18 % and 46.56 %, respectively, and 77.23 % overall. By utilizing EAAAK, GPGPG, and AAY linkers, Cholera toxin B subunit adjuvants, and appropriate epitopes were smoothly incorporated into a chimeric vaccine effectively triggering both adaptive and innate immune responses. For example, the administered antigen showed a peak in counts on the fifthday post injection and then gradually declined until the fifteenth day. Elevated levels of several antibodies (IgG + IgM > 700,000; IgM > 600,000; IgG1 + IgG2; IgG1 > 500,000) were observed as decreased in the antigen concentration. Molecular dynamics simulations carried out via iMODS revealed strong correlations between residue pairs, highlighting the stability of the docked complex. The designed vaccine has promising potential in eliciting specific immunogenic responses, thereby facilitating future research for vaccine development against V. durovernensis.

Rational design of novel peptide-based vaccine against the emerging OZ virus

Oz virus (OZV) belongs to the Orthomyxoviridae family which includes viruses with a negative-sense, single-stranded, and segmented RNA genome. OZV is a zoonotic pathogen, particularly since the virus can cause deadly illness when injected intracerebrally into nursing mice. OZV is an emerging pathogen with the potential to spark a pandemic as there is no preventive and licensed treatment against this virus. The goal of this study was to develop a novel multi-epitope vaccination against OZV proteins utilizing immunoinformatics and immunological simulation analysis. This work evaluated immunological epitopes (B cells, MHC-I, and MHC-II) to identify highly antigenic OZV target proteins. Shortlisted epitopes were joined together by using appropriate linkers and adjuvants to design multi-epitope vaccine constructs (MEVC). The vaccine models were designed, improved, validated, and the globular regions and post-translational modifications (PTMs) were also evaluated in the vaccine's structure. Molecular docking analysis with the Toll-like receptor (TLR4) showed strong interactions and appropriate binding energies. Molecular dynamics (MD) simulation confirmed stable interactions between the vaccines and TLR4. Bioinformatics tools helped optimize codons, resulting in successful cloning into appropriate host vectors. This study showed that the developed vaccines are stable and non-allergenic in the human body and successfully stimulated immunological responses against OZV. Finally, a mechanism of action for the designed vaccine construct was also proposed. Further experimental validations of the designed vaccine construct will pave the way to create a potentially effective vaccine against this emerging pathogen.

Designing novel multiepitope mRNA vaccine targeting Hendra virus (HeV): An integrative approach utilizing immunoinformatics, reverse vaccinology, and molecular dynamics simulation

Human and animal health is threatened by Hendra virus (HeV), which has few treatments. This in-silico vaccine design study focuses on HeV G (glycoprotein), F (fusion protein), and M (matrix protein). These proteins were computationally assessed for B and T-cell epitopes after considering HeV strain conservation, immunogenicity, and antigenicity. To improve vaccination immunogenicity, these epitopes were selectively ligated into a multiepitope construct. To improve vaccination longevity and immunological response, adjuvants and linkers were ligated. G, F, and M epitopes were used to create an mRNA HeV vaccine. Cytotoxic, helper, and linear B-lymphocytes' epitopes are targeted by this vaccine. The population coverage analysis demonstrates that multi-epitope vaccination covers 91.81 percent of CTL and 98.55 percent of HTL epitopes worldwide. GRAVY evaluated the vaccine's well-characterized physicochemical properties -0.503, indicating solubility and functional stability. Structure analysis showed well-stabilized 2° and 3° structures in the vaccine, with alpha helix, beta sheet, and coil structures (Ramachandran score of 88.5% and Z score of -3.44). There was a strong affinity as shown by docking tests with TLR-4 (central score of -1139.4 KJ/mol) and TLR-2 (center score of -1277.9 KJ/mol). The coupled V-apo, V-TLR2, and V-TLR4 complexes were tested for binding using molecular dynamics simulation where extremely stable complexes were found. The predicted mRNA structures provided significant stability. Codon optimization for Escherichia. coli synthesis allowed the vaccine to attain a GC content of 46.83% and a CAI score of 1.0, which supports its significant expression. Immunological simulations indicated vaccine-induced innate and adaptive immune reactions. Finally, this potential HeV vaccine needs more studies to prove its efficacy and safety.

Immunoinformatics Design of a Multiepitope Vaccine (MEV) Targeting Streptococcus mutans: A Novel Computational Approach

Dental caries, a persistent oral health challenge primarily linked to Streptococcus mutans, extends its implications beyond dental decay, affecting over 4 billion individuals globally. Despite its historical association with childhood, dental caries often persists into adulthood with prevalence rates ranging from 60 to 90% in children and 26 to 85% in adults. Currently, there is a dearth of multiepitope vaccines (MEVs) specifically designed to combat S. mutans. To address this gap, we employed an immunoinformatics approach for MEV design, identifying five promising vaccine candidates (PBP2X, PBP2b, MurG, ATP-F, and AGPAT) based on antigenicity and conservation using several tools including CELLO v.2.5, Vaxign, v2.0, ANTIGENpro, and AllerTop v2.0 tools. Subsequent identification of linear B-cell and T-cell epitopes by SVMTrip and NetCTL/NetMHC II tools, respectively, guided the construction of a MEV comprising 10 Cytotoxic T Lymphocyte (CTL) epitopes, 5 Helper T Lymphocyte (HTL) epitopes, and 5 linear B-cell epitopes, interconnected by suitable linkers. The resultant MEV demonstrated high antigenicity, solubility, and structural stability. In silico immune simulations showcased the MEV's potential to elicit robust humoral and cell-mediated immune responses. Molecular docking studies revealed strong interactions between the MEV construct and Toll-Like Receptors (TLRs) and Major Histocompatibility Complex (MHC) molecules. Remarkably, the MEV-TLR-4 complexes exhibited a low energy score, high binding affinity, and a low dissociation constant. The Molecular Dynamic (MD) simulation analysis suggested that MEV-TLR-4 complexes had the highest stability and minimal conformational changes indicating equilibrium within 40 nanosecond time frames. Comprehensive computational analyses strongly support the potential of the proposed MEV to combat dental caries and associated infections. The study's computational assays yielded promising results, but further validation through in vitro and in vivo experiments is needed to assess its efficacy and safety.

Predictive immunoinformatics reveal promising safety and anti-onchocerciasis protective immune response profiles to vaccine candidates (Ov-RAL-2 and Ov-103) in anticipation of phase I clinical trials

Onchocerciasis (river blindness) is a debilitating tropical disease that causes significant eye and skin damage, afflicting millions worldwide. As global efforts shift from disease management to elimination, vaccines have become crucial supplementary tools. The Onchocerciasis Vaccine for Africa (TOVA) Initiative was established in 2015, to advance at least one vaccine candidate initially targeting onchocerciasis in infants and children below 5 years of age, through Phase I human trials by 2025. Notably, Ov-RAL-2 and Ov-103 antigens have shown great promise during pre-clinical development, however, the overall success rate of vaccine candidates during clinical development remains relatively low due to certain adverse effects and immunogenic limitations. This study, thus, aimed at predicting the safety and immunogenicity of Ov-RAL-2 and Ov-103 potential onchocerciasis vaccine candidates prior to clinical trials. Advanced molecular simulation models and analytical immunoinformatics algorithms were applied to predict potential adverse side effects and efficacy of these antigens in humans. The analyses revealed that both Ov-RAL-2 and Ov-103 demonstrate favourable safety profiles as toxicogenic and allergenic epitopes were found to be absent within each antigen. Also, both antigens were predicted to harbour substantial numbers of a wide range of distinct epitopes (antibodies, cytokines, and T- Cell epitopes) associated with protective immunity against onchocerciasis. In agreement, virtual vaccination simulation forecasted heightened, but sustained levels of primary and secondary protective immune responses to both vaccine candidates over time. Ov-103 was predicted to be non-camouflageable, as it lacked epitopes identical to protein sequences in the human proteome. Indeed, both antigens were able to bind with high affinity and activate the innate immune TLR4 receptor, implying efficient immune recognition. These findings suggest that Ov-RAL-2 and Ov-103 can induce sufficient protective responses through diverse humoral and cellular mechanisms. Overall, our study provides additional layer of evidence for advancing the clinical development of both vaccine candidates against onchocerciasis.

In silico analysis and structural vaccinology prediction of Toxoplasma gondii ROP41 gene via immunoinformatics methods as a vaccine candidate

INTRODUCTION

Toxoplasma gondii (T. gondii) infects all warm-blooded animals, including humans. Currently, no effective treatments exist to prevent the generation of chronic tissue cysts in infected hosts. Therefore, developing a vaccine to protect to deal with toxoplasmosis is a promising strategy, as a single immunization could provide lifelong protective immunity. Rhoptry proteins (ROPs) play a vital role for the parasite's survival within host cells and perform critical functions during different phases of parasite invasion. Little is known about ROP41 gene. Nevertheless, Understanding the characteristics of ROP41 will enhance diagnostic and vaccine research.

MATERIALS AND METHODS

The current article provides a comprehensive analysis of the essential components of the ROP41 protein, including its transmembrane domain, physico-chemical properties, subcellular location, tertiary and secondary structures, and potential T- and B-cell epitopes. These features were determined by many bioinformatics approaches to identify possible epitopes for developing a highly effective vaccine.

RESULTS

ROP41 protein showed 36 possible post-translational modification regions. The ROP41 protein secondary structure contains 17.35 % extended strand, 33.47 % alpha-helix, and 49.18 % random coil. Also, ROP41 showed many possible B- and T-cell epitopes. According to the Ramachandran plot, 90.78 % of amino acid residues had been placed in favored, 3.28 % in outlier, and 5.94 % in allowed areas. Also, the allergenicity and antigenicity evaluation indicated that ROP41 is non-allergenic and immunogenic.

CONCLUSION

The current study offered critical basic and conceptual information on ROP41 to increase a successful vaccine in opposition to continual and acute toxoplasmosis for in addition in vivo assessments. Further research is necessary for the development of vaccines utilizing ROP41 alone or combined with various antigens.

Unlocking Hope: Paving the Way for a Cutting-Edge Multi-Epitope Dengue Virus Vaccine

Dengue fever is a significant health issue in Pakistan, demanding a vaccine effective against all the viral strains. This study employs reverse vaccinology to develop potential dengue vaccine candidates (DVAX I-III). The study thoroughly examined conserved areas of dengue virus serotypes 1-4's structural and non-structural proteins. Key viral proteins were analyzed to find antigenic peptides, which were incorporated into vaccine candidates and potentiated with adjuvants. Computational methods predicted peptide structures and evaluated their binding to immune receptors TLR 2, TLR 4, HLA *A1101, and DRB*401. A molecular dynamics simulation lasting 100 ns of the DVAX II-TLR4 complex at different time intervals clearly indicated that the ligand is attached to the receptor. Normal mode analysis assessed the stability and flexibility of these interactions. Encouragingly, all three vaccine candidates demonstrated favorable interactions with these immune receptors and the potential to induce a robust immune response. These findings suggest their safety and warrant further in vivo studies to evaluate their efficacy for clinical development.

Machine learning tools used for mapping some immunogenic epitopes within the major structural proteins of the bovine coronavirus (BCoV) and for the in silico design of the multiepitope-based vaccines

Introduction

BCoV is one of the significant causes of enteritis in young calves; it may also be responsible for many respiratory outbreaks in young calves. BCoV participates in the development of bovine respiratory disease complex in association with other bacterial pathogens. Our study aimed (1) to map the immunogenic epitopes (B and T cells) within the major BCoV structural proteins. These epitopes are believed to induce a robust immune response through the interaction with major histocompatibility complex (MHC class II) molecules (2) to design some novel BCoV multiepitope-based vaccines.

Materials and Methods

The goal is achieved through several integrated in silico prediction computational tools to map these epitopes within the major BCoV structural proteins. The final vaccine was constructed in conjugation with the Choleratoxin B toxin as an adjuvant. The tertiary structure of each vaccine construct was modeled through the AlphaFold2 tools. The constructed vaccine was linked to some immunostimulants such as Toll-like receptors (TLR2 and TLR4). We also predicted the affinity binding of these vaccines with this targeted protein using molecular docking. The stability and purity of each vaccine construct were assessed using the Ramachandran plot and the Z-score values. We created the in silico cloning vaccine constructs using various expression vectors through vector builder and Snap gene.

Results and discussion

The average range of major BCoV structural proteins was detected within the range of 0.4 to 0.5, which confirmed their antigen and allergic properties. The binding energy values were detected between -7.9 and -9.4 eV and also confirmed their best interaction between our vaccine construct and Toll-like receptors. Our in silico cloning method expedited the creation of vaccine constructs and established a strong basis for upcoming clinical trials and experimental validations.

Conclusion

Our designed multiepitope vaccine candidates per each BCoV structural protein showed high antigenicity, immunogenicity, non-allergic, non-toxic, and high-water solubility. Further studies are highly encouraged to validate the efficacy of these novel BCoV vaccines in the natural host.

Delineating multi-epitopes vaccine designing from membrane protein CL5 against all monkeypox strains: a pangenome reverse vaccinology approach

The recently identified monkeypox virus (MPXV or mpox) is a zoonotic orthopox virus that infects humans and causes diseases with traits like smallpox. The world health organization (WHO) estimates that 3-6% of MPXV cases result in death. As it might impact everyone globally, like COVID, and become the next pandemic, the cure for this disease is important for global public health. The high incidence and disease ratio of MPXV necessitates immediate efforts to design a unique vaccine candidate capable of addressing MPXV diseases. Here, we used a computational pan-genome-based vaccine design strategy for all currently reported 19 MPXV strains acquired from different regions of the world. Thus, this study's objective was to develop a new and safe vaccine candidate against MPXV by targeting the membrane CL5 protein; identified after the pangenome analysis. Proteomics and reverse vaccinology have covered up all of the MPXV epitopes that would usually stimulate robust host immune responses. Following this, only two mapped (MHC-I, MHC-II, and B-cell) epitopes were observed to be extremely effective that can be used in the construction of CL5 protein vaccine candidates. The suggested vaccine (V5) candidate from eight vaccine models was shown to be antigenic, non-allergenic, and stable (with 213 amino acids). The vaccine's candidate efficacy was evaluated by using many in silico methods to predict, improve, and validate its 3D structure. Molecular docking and molecular dynamics simulations further reveal that the proposed vaccine candidate ensemble has a high interaction energy with the HLAs and TRL2/4 immunological receptors under study. Later, the vaccine sequence was used to generate an expression vector for the E. coli K12 strain. Further study uncovers that V5 was highly immunogenic because it produced robust primary, secondary, and tertiary immune responses. Eventually, the use of computer-aided vaccine designing may significantly reduce costs and speed up the process of developing vaccines. Although, the results of this research are promising, however, more research (experimental; in vivo, and in vitro studies) is needed to verify the biological efficacy of the proposed vaccine against MPXV.Communicated by Ramaswamy H. Sarma.

Designing of neoepitopes based vaccine against breast cancer using integrated immuno and bioinformatics approach

Cancer is characterized by genetic instability due to accumulation of somatic mutations in the genes which generate neoepitopes (mutated epitopes) for targeting by Cytotoxic T lymphocytes (CTL). Breast cancer has a high transformation rate with unique composition of mutational burden and neoepitopes load that open a platform to designing a neoepitopes-based vaccine. Neoepitopes-based therapeutic cancer vaccines designed by neoantigens have shown to be feasible, nontoxic, and immunogenic in cancer patients. Stimulation of CTL by neoepitope-based vaccine of self-antigenic proteins plays a key role in distinguishing cancer cells from normal cells and selectively targets only malignant cells. A neoepitopes-based vaccine to combat breast cancer was designed by combining immunology and bioinformatics approaches. The vaccine construct was assembled by the fusion of CTL neoepitopes, helper sequences (used for better separation of the epitopes), and adjuvant together with linkers. The neoepitopes were identified from somatic mutations in the MUC16, TP53, RYR2, F5, DNAH17, ASPM, and ABCA13 self-antigenic proteins. The vaccine construct was undertaken to study the immune simulations (IS), physiochemical characteristics (PP), molecular docking (MD) and simulations, and cloning in appropriate vector. Together, these parameters establish safety, stability, and a strong binding affinity against class I MHC molecules capable of inducing a complete immune response against breast cancer cells.Communicated by Ramaswamy H. Sarma.

A therapeutic epitopes-based vaccine engineering against Salmonella enterica XDR strains for typhoid fever: a Pan-vaccinomics approach

A prevalent food-borne pathogen, Salmonella enterica serotypes Typhi, is responsible for gastrointestinal and systemic infections globally. Salmonella vaccines are the most effective, however, producing a broad-spectrum vaccine remains challenging due to Salmonella's many serotypes. Efforts are urgently required to develop a novel vaccine candidate that can tackle all S. Typhi strains because of their high resistance to multiple kinds of antibiotics (particularly the XDR H58 strain). In this work, we used a computational pangenome-based vaccine design technique on all available (n = 119) S. Typhi reference genomes and identified one TonB-dependent siderophore receptor (WP_001034967.1) as highly conserved and prospective vaccine candidates from the predicted core genome (n = 3,351). The applied pan-proteomics and Immunoinformatic approaches help in the identification of four epitopes that may trigger adequate host body immune responses. Furthermore, the proposed vaccine ensemble demonstrates a stable binding conformation with the examined immunological receptor (HLAs and TRL2/4) and has large interaction energy determined via molecular docking and molecular dynamics simulation techniques. Eventually, an expression vector for the Escherichia. coli K12 strain was constructed from the vaccine sequence. Additional analysis revealed that the vaccine may help to elicit strong immune responses for typhoid infections, however, experimental analysis is required to verify the vaccine's effectiveness based on these results. Moreover, the applied computer-assisted vaccine design may considerably decrease vaccine development costs and speed up the process. The study's findings are intriguing, but they must be evaluated in the experimental labs to confirm the developed vaccine's biological efficiency against XDR S. Typhi.Communicated by Ramaswamy H. Sarma.

In silico design of Mycobacterium tuberculosis multi-epitope adhesin protein vaccines

Mycobacterium tuberculosis (Mtb) adhesin proteins are promising candidates for subunit vaccine design. Multi-epitope Mtb vaccine and diagnostic candidates were designed using immunoinformatic tools. The antigenic potential of 26 adhesin proteins were determined using VaxiJen 2.0. The truncated heat shock protein 70 (tnHSP70), 19 kDa antigen lipoprotein (lpqH), Mtb curli pili (MTP), and Phosphate transport protein S1 (PstS1) were selected based on the number of known epitopes on the Immune Epitope Database (IEDB). B- and T-cell epitopes were identified using BepiPred2.0, ABCpred, SVMTriP, and IEDB, respectively. Population coverage was analysed using prominent South African specific alleles on the IEDB. The allergenicity, physicochemical characteristics and tertiary structure of the tri-fusion proteins were determined. The in silico immune simulation was performed using C-ImmSim. Three truncated sequences, with predicted B and T cell epitopes, and without allergenicity or signal peptides were linked by three glycine-serine residues, resulting in the stable, hydrophilic molecules, tnlpqH-tnPstS1-tnHSP70 (64,86 kDa) and tnMTP-tnPstS1-tnHSP70 (63,96 kDa). Restriction endonuclease recognition sequences incorporated at the N- and C-terminal ends of each construct, facilitated virtual cloning using Snapgene, into pGEX6P-1, resulting in novel, highly immunogenic vaccine candidates (0,912-0,985). Future studies will involve the cloning, recombinant protein expression and purification of these constructs for downstream applications.

Advancing one health vaccination: In silico design and evaluation of a multi-epitope subunit vaccine against Nipah virus for cross-species immunization using immunoinformatics and molecular modeling

The resurgence of the Nipah virus (NiV) in 2023 has raised concerns for another potentially severe pandemic, given its history of high mortality from previous outbreaks. Unfortunately, no therapeutics and vaccines have been available for the virus. This study used immunoinformatics and molecular modeling to design and evaluate a multi-epitope subunit vaccine targeting NiV. The designed vaccine construct aims to stimulate immune responses in humans and two other intermediate animal hosts of the virus-swine and equine. Using several epitope prediction tools, ten peptides that induced B-lymphocyte responses, 17 peptides that induced cytotoxic T-lymphocyte (CTL) responses, and 12 peptides that induced helper T-lymphocyte (HTL) responses were mapped from nine NiV protein sequences. However, the CTL and HTL-inducing peptides were reduced to ten and eight, respectively, following molecular docking and dynamics. These screened peptides exhibited stability with 30 common major histocompatibility complex (MHC) receptors found in humans, swine, and equine. All peptides were linked using peptide linkers to form the multi-epitope construct and various adjuvants were tested to enhance its immunogenicity. The vaccine construct with resuscitation-promoting factor E (RpfE) adjuvant was selected as the final design based on its favorable physicochemical properties and superior immune response profile. Molecular docking was used to visualize the interaction of the vaccine to toll-like receptor 4 (TLR4), while molecular dynamics confirmed the structural stability of this interaction. Physicochemical property evaluation and computational simulations showed that the designed vaccine construct exhibited favorable properties and elicited higher antibody titers than the six multi-epitope NiV vaccine designs available in the literature. Further in vivo and in vitro experiments are necessary to validate the immunogenicity conferred by the designed vaccine construct and its epitope components. This study demonstrates the capability of computational methodologies in rational vaccine design and highlights the potential of cross-species vaccination strategies for mitigating potential NiV threats.

Targeting Polyprotein to Design Potential Multiepitope Vaccine against Omsk Hemorrhagic Fever Virus (OHFV) by Evaluating Allergenicity, Antigenicity, and Toxicity Using Immunoinformatic Approaches

Omsk Hemorrhagic Fever Virus (OHFV) is an RNA virus with a single-stranded, positive-sense genome. It is classified under the Flaviviridae family. The genome of this virus is 98% similar to the Alkhurma hemorrhagic fever virus (AHFV), which belongs to the same family. Cases of the virus have been reported in various regions of Saudi Arabia. Both OHFV and AHFV have similarities in pathogenic polyprotein targets. No effective and licensed vaccines are available to manage OHFV infections. Therefore, an effective and safe vaccine is required that can activate protective immunity against OHFV. The current study aimed to design a multiepitope subunit vaccine against the OHFV utilizing several immunoinformatic tools. The polyprotein of OHFV was selected and potent antigenic, non-allergenic, and nontoxic cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and linear B-lymphocyte (LBL) epitopes were chosen. After screening, eight (8) CTL, five (5) HTL, and six (6) B cell epitopes were joined with each other using different linkers. Adjuvant human beta defensin-2 was also linked to the epitopes to increase vaccine antigenic and immunogenic efficiency. The designed vaccine was docked with Toll-like receptor 4 (TLR4) as it activates and induces primary and secondary immune responses against OHFV. Codon optimization was carried out, which resulted in a CAI value of 0.99 and 53.4% GC contents. In addition, the construct was blindly docked to the TLR4 immune receptor and subjected to conformational dynamics simulation analysis to interpret the intricate affinity and comprehend the time-dependent behavior. Moreover, it was predicted that immune responses to the developed vaccine construct reported formation of strong humoral and cellular immune cells. Therefore, the proposed vaccine may be considered in experimental assays to combat OHFV infections. Laboratory experiments for the above predictions are essential in order to evaluate the effectiveness, safety, and protective properties of the subject in question.

Designing of a chimeric multiepitope vaccine against bancroftian lymphatic filariasis through immunoinformatics approaches

The filarial worms of Wuchereria bancrofti are the primary cause of lymphatic filariasis (LF), a mosquito-borne disease among the neglected tropical parasitic diseases. Considering the global endemic consequences of the disease, there is a need to develop a successful vaccine candidate against LF. Using advanced immunoinformatics approaches, we designed two multiepitope vaccines targeting W. bancrofti's glutathione S-transferase and thioredoxin. Therefore, we predicted several MHC-1, MHC-2, and B-cell epitopes from these proteins and mapped two vaccine candidates (V1 and V2). The vaccines were subsequently employed for physicochemical analysis, structural prediction and validation, docking and normal mode analysis, codon optimization, and immune simulation. The selected MHC-1, MHC-2, and B-cell epitopes were antigenic without allergenicity or toxicity. The designed vaccines were expected to be soluble, stable proteins under physiological conditions. Compared to V2, V1's secondary and tertiary structures were simultaneously favorable, with Ramachandran plot analysis revealing 95.6% residues in favored areas. Subsequently, the molecular docking analysis indicated that the V1 had a high binding affinity for the TLR-2, TLR-4 and TLR-5, as suggested by the docking scores of -1248.7, -1038.5 and -1562.8, respectively. The NMA of these complexes further indicated their structural flexibility. Molecular dynamics simulations of V1-TLR complexes revealed V1-TLR-4 as the most stable, with the lowest free energy and minimal fluctuations, indicating the strongest binding affinity. The results of the codon optimization showed high levels of expression, with a favorable CAI score (<1.0). A three-dose vaccination analysis showed significant and persistent immunological responses, including adaptive and innate immune responses. The findings emphasize the potential of the V1 against W. bancrofti, but further validation is required through in vitro, in vivo, and clinical trials.

Anticipatory in silico vaccine designing based on specific antigenic epitopes from Streptococcus mutans against diabetic pathogenesis

The metabolic disorder Type 2 Diabetes Mellitus (T2DM) is characterized by hyperglycaemia, causing increased mortality and healthcare burden globally. Recent studies emphasize the impact of metabolites in the gut microbiome on T2DM pathogenesis. One such microbial metabolite, imidazole propionate (Imp) derived from histidine metabolism, is shown to interfere with insulin signalling and other key metabolic processes. The key enzyme urocanate reductase (UrdA) is involved in ImP production. Hence, we propose to develop a novel therapeutic vaccine against the gut microbe producing Imp based on UrdA as a target for treating T2DM using immunoinformatics approach. Antigenic, non-allergic, non-toxic, and immunogenic B cell and T cell potential epitopes were predicted using immunoinformatics servers and tools. These epitopes were adjoined using linker sequences, and to increase immunogenicity, adjuvants were added at the N-terminal end of the final vaccine construct. Further, to confirm the vaccine's safety, antigenic and non-allergic characteristics of the developed vaccine construct were assessed. The tertiary structure of the UrdA vaccine sequence was predicted using molecular modelling tools. A molecular docking study was utilized to understand the vaccine construct interaction with immune receptors, followed by molecular dynamics simulation and binding free energy calculations to assess stability of the complex. In silico cloning techniques were employed to evaluate the expression and translation effectiveness of the developed vaccine in pET vector. In conclusion, this study developed an in silico epitope-based vaccine construct as a novel adjunct therapeutic for T2DM.

Graphical Abstract

Identification of highly conserved surface-exposed peptides of spike protein for multiepitope vaccine design against emerging omicron variants: An immunoinformatic approach

The COVID-19 pandemic, originating in Wuhan in 2019, was caused by SARS-CoV-2, leading to significant global fatalities. Despite the development of vaccines, the virus mutates, creating variants that evade vaccine-induced immunity. To address SARS-CoV-2's evolving nature, a multiepitope vaccine was developed using immunoinformatics approach, specifically targeting the Omicron variant's spike protein. This vaccine includes six CD8 + and eleven CD4 + epitopes selected for their immunogenicity, non-toxicity, and significant conservation among former Variants of Concern (VOCs) and Variants of Interest (VOIs), such as Alpha, Beta, Gamma, Delta, Lambda, Mu, R1, and Zeta, as well as current Variants Under Monitoring (VUMs) like XBB.1.5, XBB.1.16, EG.5, BA.2.86, and JN.1. Notably, certain epitopes like ELLHAPATV and PYRVVVLSFELLHAP were fully conserved across all tested variants in the spike protein's receptor binding domain (RBD). Others, such as NATRFASVYAWNRKR, were fully conserved in all former VOCs and VOIs and 93.33 % in current VUMs, while ERDISTEIYQAGNKP was entirely conserved in current VUMs within the RBD region. The study went on to model, refine, and validate the vaccine prototype's tertiary structure. Docking experiments and molecular dynamic simulations revealed robust and stable interactions with Toll-like receptor 4. Cloning and codon optimization confirmed successful expression in E. coli. Subsequently, the immunological reaction of the multiepitope vaccine demonstrated that the three-time administration of the prototype significantly enhanced the antibody response while decreasing the number of antigens. The designed vaccine's epitopes showed significant combined global population coverage of 100 % with 89.75 % for CD8 + and 99.98 % for CD4 + epitopes and conservation across SARS-CoV-2 variants especially in current monitoring omicron subvariants, supporting its broader applicability and potential efficacy. Although, this promising vaccine candidate needs to undergo clinical trials to determine its effectiveness in neutralising SARS-CoV-2.

Development of innovative multi-epitope mRNA vaccine against central nervous system tuberculosis using in silico approaches

Tuberculosis(TB) of the Central nervous system (CNS) is a rare and highly destructive disease. The emergence of drug resistance has increased treatment difficulty, leaving the Bacillus Calmette-Guérin (BCG) vaccine as the only licensed preventative immunization available. This study focused on identifying the epitopes of PknD (Rv0931c) and Rv0986 from Mycobacterium tuberculosis(Mtb) strain H37Rv using an in silico method. The goal was to develop a therapeutic mRNA vaccine for preventing CNS TB. The vaccine was designed to be non-allergenic, non-toxic, and highly antigenic. Codon optimization was performed to ensure effective translation in the human host. Additionally, the secondary and tertiary structures of the vaccine were predicted, and molecular docking with TLR-4 was carried out. A molecular dynamics simulation confirmed the stability of the complex. The results indicate that the vaccine structure shows effectiveness. Overall, the constructed vaccine exhibits ideal physicochemical properties, immune response, and stability, laying a theoretical foundation for future laboratory experiments.

Unveiling a Comprehensive Multi-epitope Subunit Vaccine Strategy Against Salmonella subsp. enterica: Bridging Core, Subtractive Proteomics, and Immunoinformatics

Salmonella subsp. enterica (SE) presents a significant global health challenge in both developed and developing countries. Current SE vaccines have limitations, targeting specific strains and demonstrating moderate efficacy in adults, while also being unsuitable for young children and often unaffordable in regions with lower income levels where the disease is prevalent. To address these challenges, this study employed a computational approach integrating core proteomics, subtractive proteomics, and immunoinformatics to develop a universal SE vaccine and identify potential drug targets. Analysis of the core proteome of 185 SE strains revealed 1964 conserved proteins. Subtractive proteomics identified 9 proteins as potential vaccine candidates and 41 as novel drug targets. Using reverse vaccinology-based immunoinformatics, four multi-epitope-based subunit vaccine constructs (MESVCs) were designed, aiming to stimulate cytotoxic T lymphocyte, helper T lymphocyte, and linear B lymphocyte responses. These constructs underwent comprehensive evaluations for antigenicity, immunogenicity, toxicity, hydropathicity, and physicochemical properties. Predictive modeling, refinement, and validation were conducted to determine the secondary and tertiary structures of the SE-MESVCs, followed by docking studies with MHC-I, MHC-II, and TLR4 receptors. Molecular docking assessments showed favorable binding with all three receptors, with SE-MESVC-4 exhibiting the most promising binding energy. Molecular dynamics simulations confirmed the binding affinity and stability of SE-MESVC-4 with the TLR4/MD2 complex. Additionally, codon optimization and in silico cloning verified the efficient translation and successful expression of SE-MESVC-4 in Escherichia coli (E. coli) str. K12. Subsequent in silico immune simulation evaluated the efficacy of SE-MESVC-4 in triggering an effective immune response. These results suggest that SE-MESVC-4 may induce both humoral and cellular immune responses, making it a potential candidate for an effective SE vaccine. However, further experimental investigations are necessary to validate the immunogenicity and efficacy of SE-MESVC-4, bringing us closer to effectively combating SE infections.

Development of an ancestral DC and TLR4-inducing multi-epitope peptide vaccine against the spike protein of SARS-CoV and SARS-CoV-2 using the advanced immunoinformatics approaches

The oldest human coronavirus that started pandemics is severe acute respiratory syndrome virus (SARS-CoV). While SARS-CoV was eradicated, its new version, SARS-CoV2, caused the global pandemic of COVID-19. Evidence highlights the harmful events orchestrated by these viruses are mediated by Spike (S)P protein. Experimental epitopes of the S protein which were overlapping and ancestral between SARS-CoV and SARS-CoV-2 were obtained from the immune epitopes database (IEDB). The epitopes were then assembled in combination with a 50 S ribosomal protein L7/L12 adjuvant, a Mycobacterium tuberculosis-derived element and mediator of dendritic cells (DCs) and toll-like receptor 4 (TLR4). The immunogenic sequence was modeled by the GalaxyWeb server. After the improvement and validation of the protein structure, the physico-chemical properties and immune simulation were performed. To investigate the interaction with TLR3/4, Molecular Dynamics Simulation (MDS) was used. By merging the 17 B- and T-lymphocyte (HTL/CTL) epitopes, the vaccine sequence was created. Also, the Ramachandran plot presented that most of the residues were located in the most favorable and allowed areas. Moreover, SnapGene was successful in cloning the DNA sequence linked to our vaccine in the intended plasmid. A sequence was inserted between the XhoI and SacI position of the pET-28a (+) vector, and simulating the agarose gel revealed the existence of the inserted gene in the cloned plasmid with SARS vaccine (SARSV) construct, which has a 6565 bp in length overall. In terms of cytokines/IgG response, immunological simulation revealed a strong immune response. The stabilized vaccine showed strong interactions with TLR3/4, according to Molecular Dynamics Simulation (MDS) analysis. The present ancestral vaccine targets common sequences which seem to be valuable targets even for the new variant SARS-CoV-2.

Genome-level therapeutic targets identification and chimeric Vaccine designing against the Blastomyces dermatitidis

Blastomyces dermatitidis is a thermally dimorphic fungus that can cause serious and sometimes fatal infections, including blastomycosis. After spore inhalation, a pulmonary infection develops, which can be asymptomatic and have lethal effects, such as acute respiratory distress syndrome. Its most common extra-pulmonary sites are the central nervous system, bones, skin, and genito-urinary systems. Currently, no vaccine has been approved by the FDA to prevent this infection. In the study, a peptide-based vaccine was developed against blastomycosis by using subtractive proteomics and reverse vaccinology approaches. It focuses on mining the whole genome of B. dermatitidis, identifying potential therapeutic targets, and pinpointing potential epitopes for both B- and T-cells that are immunogenic, non-allergenic, non-toxic, and highly antigenic. Multi-epitope constructs were generated by incorporating appropriate linker sequences. A linker (EAAAK) was also added to incorporate an adjuvant sequence to increase immunological potential. The addition of adjuvants and linkers ultimately resulted in the formation of a vaccine construct in which the number of amino acids was 243 and the molecular weight was 26.18 kDa. The designed antigenic and non-allergenic vaccine constructs showed suitable physicochemical properties. The vaccine's structures were predicted, and further analysis verified their interactions with the human TLR-4 receptor through protein-protein docking. Additionally, MD simulation showed a potent interaction between prioritized vaccine-receptor complexes. Immune simulation predicted that the final vaccine injections resulted in significant immune responses for the T- and B-cell immune responses. Moreover, in silico cloning ensured a high expression possibility of the lead vaccine in the E. coli (K12) vector. This study offers an initiative for the development of effective vaccines against B. dermatitidis; however, it is necessary to validate the designed vaccine's immunogenicity experimentally.

Rational design and computational evaluation of a multi-epitope vaccine for monkeypox virus: Insights into binding stability and immunological memory

Multi-epitope vaccines strategically tackle rapidly mutating viruses by targeting diverse epitopes from different proteins, providing a comprehensive and adaptable immune protection approach for enhanced coverage against various viral variants. This research employs a comprehensive approach that includes the mapping of immune cells activating epitopes derived from the six structural glycoproteins (A29L, A30L, A35R, L1R, M1R, and E8L) of Monkeypox virus (Mpox). A total of 7 T-cells-specific epitopes, 13 B-cells-specific epitopes, and 5 IFN-γ activating epitopes were forecasted within these glycoproteins. The selection process focused on epitopes indicating high immunogenicity and favorable binding affinity with multiple MHC alleles. Following this, a vaccine has been formulated by incorporating the chosen epitopes, alongside adjuvants (PADRE peptide) and various linkers (EAAAK, GPGPG, and AAY). The physicochemical properties and 3D structure of the multi-epitope hybrid vaccine were analysed for characterization. MD simulations were employed to predict the binding stability between the vaccine and various pathogen recognition receptors such as TLRs (TLR1, TLR2, TLR4, and TLR6), as well as both class I and II MHC, achieved through hydrogen bonding and hydrophobic interactions. Through in silico cloning and immune simulation, it was observed that the multi-epitopes vaccine induced a robust memory immune response upon booster doses, forecasting protective immunity upon viral challenge. This protective immunity was characterized by the production of IgM + IgG antibodies, along with release of inflammatory cytokines like IFN-γ, and IL12, and the activation of various immune cells. This study offers valuable insights into the potential of a multi-epitope vaccine targeting the Mpox virus.

An In Silico Design of a Vaccine against All Serotypes of the Dengue Virus Based on Virtual Screening of B-Cell and T-Cell Epitopes

Dengue virus poses a significant global health challenge, particularly in tropical and subtropical regions. Despite the urgent demand for vaccines in the control of the disease, the two approved vaccines, Dengvaxia and TV003/TV005, there are current questions regarding their effectiveness due to an increased risk of antibody-dependent enhancement (ADE) and reduced protection. These challenges have underscored the need for further development of improved vaccines for Dengue Virus. This study presents a new design using an in silico approach to generate a more effective dengue vaccine. Initially, our design process began with the collection of Dengue polyprotein sequences from 10 representative countries worldwide. And then conserved fragments of viral proteins were retrieved as the bases for epitope screening. The selection of epitopes was then carried out with criteria such as antigenicity, immunogenicity, and binding affinity with MHC molecules, while the exclusion criteria were according to their allergenicity, toxicity, and potential for antibody-dependent enhancement. We then constructed a core antigen with the selected epitopes and linked the outcomes with distinct adjuvant proteins, resulting in three candidate vaccines: PSDV-1, PSDV-2, and PSDV-3. Among these, PSDV-2 was selected for further validation due to its superior physicochemical and structural properties. Extensive simulations demonstrated that PSDV-2 exhibited strong binding to pattern recognition receptors, high stability, and robust immune induction, confirming its potential as a high-quality vaccine candidate. For its recombinant expression, a plasmid was subsequently designed. Our new vaccine design offers a promising additional option for Dengue virus protection. Further experimental validations will be conducted to confirm its protective efficacy and safety.

Reverse vaccinology approaches to design a potent multiepitope vaccine against the HIV whole genome: immunoinformatic, bioinformatics, and molecular dynamics approaches

Substantial advances have been made in the development of promising HIV vaccines to eliminate HIV-1 infection. For the first time, one hundred of the most submitted HIV subtypes and CRFs were retrieved from the LANL database, and the consensus sequences of the eleven HIV proteins were obtained to design vaccines for human and mouse hosts. By using various servers and filters, highly qualified B-cell epitopes, as well as HTL and CD8 + epitopes that were common between mouse and human alleles and were also located in the conserved domains of HIV proteins, were considered in the vaccine constructs. With 90% coverage worldwide, the human vaccine model covers a diverse allelic population, making it widely available. Codon optimization and in silico cloning in prokaryotic and eukaryotic vectors guarantee high expression of the vaccine models in human and E. coli hosts. Molecular dynamics confirmed the stable interaction of the vaccine constructs with TLR3, TLR4, and TLR9, leading to a substantial immunogenic response to the designed vaccine. Vaccine models effectively target the humoral and cellular immune systems in humans and mice; however, experimental validation is needed to confirm these findings in silico.

Rational Design of a Multi-epitope Vaccine Using Neoantigen Against Colorectal Cancer Through Structural Immunoinformatics and ML-Enabled Simulation Approach

Colorectal cancer poses a substantial global health burden. Regarding WHO, the global burden of colorectal cancer will be about 3.2 million new cases by the year 2040. Simultaneously, it indicated that this cancer will cause 6 million deaths per year. Despite advancements in chemotherapy and monoclonal antibody therapy, the disease remains a significant challenge due to the resistance of cancer stem cells. This study endeavors to design a multi-epitopic peptide (9-mer epitopes) neoantigen-based vaccine targeting the TLR4/MD2 complex as a potential vaccine candidate. These tumor-specific neoantigens (TSA) are considered novel antigens that can be used for vaccine development against cancer. To develop the neoantigen vaccine candidate, we used the SPENCER database, and 140 lncRNA-derived epitopes were retrieved. From 140 epitopes, we selected seven neoantigens with high antigenic properties for the vaccine construct. A novel vaccine containing epitopes, linkers (EAAAK and CPCPG), and adjuvants (ribosomal [50S] protein L7L12) was formulated utilizing immunoinformatics tools. The vaccine's biophysical properties were evaluated, revealing its antigenicity (0.6469), stability (instability index: 37.05), and potential for immune system interaction. In-depth structural analyses, molecular docking studies, and ML-enabled immune simulation profiling underscored the vaccine's structural integrity, binding affinity with TLR4, and ability to elicit robust immune responses against colorectal cancer antigens. These findings suggest that the multi-epitopic vaccine holds promise as a next-generation approach to combat colorectal cancer. Our in silico studies exhibit potentiality of the vaccine candidate; however, further in vivo and in vitro investigations are crucial to validate immunogenicity, safety, and efficacy before clinical implementation. Our study developed a first-time lncRNA-derived neoantigen-based cancer vaccine.

Design of a Helicobacter pylori multi-epitope vaccine based on immunoinformatics

Helicobacter pylori (H. pylori) is an infectious bacterium that colonizes the stomach of approximately half of the global population. It has been classified as a Group I carcinogen by the World Health Organization due to its strong association with an increased incidence of gastric cancer and exacerbation of stomach diseases. The primary treatment for H. pylori infection currently involves triple or quadruple therapy, primarily consisting of antibiotics and proton pump inhibitors. However, the increasing prevalence of antibiotic resistance poses significant challenges to this approach, underscoring the urgent need for an effective vaccine. In this study, a novel multi-epitope H. pylori vaccine was designed using immunoinformatics. The vaccine contains epitopes derived from nine essential proteins. Software tools and online servers were utilized to predict, evaluate, and analyze the physiochemical properties, secondary and tertiary structures, and immunogenicity of the candidate vaccine. These comprehensive assessments ultimately led to the formulation of an optimal design scheme for the vaccine. Through constructing a novel multi-epitope vaccine based on immunoinformatics, this study offers promising prospects and great potential for the prevention of H. pylori infection. This study also provides a reference strategy to develop multi-epitope vaccines for other pathogens.

Epitopes screening and vaccine molecular design of PEDV S protein based on immunoinformatics

Porcine epidemic diarrhea virus (PEDV) is a serious disease that poses a significant threat to the pig industry. This study focused on analyzing the Spike protein of PEDV, which harbors crucial antigenic determinants, in identifying dominant epitopes. Immunoinformatics tools were used to screen for B-cell, CD4+ and CD8+ predominance epitopes. These epitopes were then connected to the N-terminal of ferritin to form a self-assembled nanoparticle vaccine. Various physical and chemical properties of the candidate vaccine were analyzed, including secondary structure prediction, tertiary structure modeling, molecular docking, immune response simulation and computer cloning. The results demonstrated that the candidate vaccine was antigenic, soluble, stable, non-allergic, and formed a stable complex with the target receptor TLR-3. Immune simulation analysis showed that the candidate vaccine effectively stimulated both cellular and humoral reactions, leading to increased related cytokines production. Furthermore, efficient and stable expression of the candidate vaccine was achieved through reverse translation in the Escherichia coli K12 expression system following codon optimization and in silico cloning. The developed nanoparticle candidate vaccine in this study holds promise as an effective PEDV vaccine candidate, offering a new approach for the research, development and improvement of vaccines targeting porcine enteric diarrhea coronavirus.

DNA Vaccines Encoding HTNV GP-Derived Th Epitopes Benefited from a LAMP-Targeting Strategy and Established Cellular Immunoprotection

Vaccines has long been the focus of antiviral immunotherapy research. Viral epitopes are thought to be useful biomarkers for immunotherapy (both antibody-based and cellular). In this study, we designed a novel vaccine molecule, the Hantaan virus (HTNV) glycoprotein (GP) tandem Th epitope molecule (named the Gnc molecule), in silico. Subsequently, computer analysis was used to conduct a comprehensive and in-depth study of the various properties of the molecule and its effects as a vaccine molecule in the body. The Gnc molecule was designed for DNA vaccines and optimized with a lysosomal-targeting membrane protein (LAMP) strategy. The effects of GP-derived Th epitopes and multiepitope vaccines were initially verified in animals. Our research has resulted in the design of two vaccines based on effective antiviral immune targets. The effectiveness of molecular therapies has also been preliminarily demonstrated in silico and in laboratory animals, which lays a foundation for the application of a vaccines strategy in the field of antivirals.

Advanced vaccinomic, immunoinformatic, and molecular modeling strategies for designing Multi- epitope vaccines against the Enterobacter cloacae complex

The increasing and ongoing issue of antibiotic resistance in bacteria is of huge concern globally, mainly to healthcare facilities. It is now crucial to develop a vaccine for therapeutic and preventive purposes against the bacterial species causing hospital-based infections. Among the many antibiotic- resistant bacterial pathogens, the Enterobacter cloacae complex (ECC) including six species, E. Colcae, E. absuriae, E. kobie, E. hormaechei, E. ludwigii, and E. nimipressuralis, are dangerous to public health and may worsen the situation. Vaccination plays a vital role in the prevention of infections and infectious diseases. This research highlighted the construction and design of a multi-epitope vaccine for the E. cloacae complex by retrieving their complete sequenced proteome. The retrieved proteome was assessed to opt for potential vaccine candidates using immunoinformatic tools. Both B and T-cell epitopes were predicted in order to create both humoral and cellular immunity and further scrutinized for antigenicity, allergenicity, water solubility, and toxicity analysis. The final potential epitopes were subjected to population coverage analysis. Major histocompatibility complex (MHC) class combined, and MHC Class I and II world population coverage was obtained as 99.74%, and 98.55% respectively while a combined 81.81% was covered. A multi-epitope peptide-based vaccine construct consisting of the adjuvant, epitopes, and linkers was subjected to the ProtParam tool to calculate its physiochemical properties. The total amino acids were 236, the molecular weight was 27.64kd, and the vaccine construct was stable with an instability index of 27.01. The Grand Average of Hydropathy (GRAVY) (hydrophilicity) value obtained was -0.659, being more negative and depicting the hydrophilic character. It was non-allergen antigenic with an antigenicity of 0.8913. The vaccine construct was further validated for binding efficacy with immune cell receptors MHC-I, MHC-II, and Toll-like receptor (TLR)-4. The molecular docking results depict that the designed vaccine has good binding potency with immune receptors crucial for antigen presentation and processing. Among the Vaccine-MHC-I, Vaccine-MHC-II, and Vaccine-TLR-4 complexes, the best-docked poses were identified based on their lowest binding energy scores of -886.8, -995.6, and -883.6, respectively. Overall, we observed that the designed vaccine construct can evoke a proper immune response and the construct could help experimental researchers in the formulation of a vaccine against the targeted pathogens.

Bioinformatic elucidation of conserved epitopes to design a potential vaccine candidate against existing and emerging SARS-CoV-2 variants of concern

The COVID-19 pandemic caused by SARS-CoV-2 poses a significant adverse effects on health and economy globally. Due to mutations in genome, COVID-19 vaccine efficacy decreases. We used immuno-informatics to design a Multi epitope vaccine (MEV) candidate for SARS-CoV-2 variants of concern (VOCs). Hence, we predicted binders/epitopes MHC-I, CD8+, MHC-II, CD4+, and CTLs from spike, membrane and envelope proteins of VOCs. In addition, we assessed the conservation of these binders and epitopes across different VOCs. Subsequently, we designed MEV by combining the predicted CTL and CD4+ epitopes from spike protein, peptide linkers, and an adjuvant. Further, we evaluated the binding of MEV candidate against immune receptors namely HLA class I histocompatibility antigen, HLA class II histocompatibility antigen, and TLR4, achieving binding scores of -1265.3, -1330.7, and -1337.9. Molecular dynamics and normal mode analysis revealed stable docking complexes. Moreover, immune simulation suggested MEV candidate elicits both innate and adaptive immune response. We anticipate that this conserved MEV candidate will provide protection from VOCs and emerging strains.

Development of a multi-epitope vaccine candidate against Pseudomonas aeruginosa causing urinary tract infection and evaluation of its immunoreactivity in a rabbit model

Pseudomonas aeruginosa is associated with different infections such as urinary tract infections (UTIs). The increased antibiotic resistance reaches the need to develop vaccine against the infections. In the present study, bioinformatics approaches were applied to design a novel multi-epitope of PcrV and OmpE from P. aeruginosa. The raised antibody against the multi-epitope was evaluated and challenge experiment was done to evaluate the efficacy of the multi-epitope. The results of epitope mapping of B-cells indicated 8 regions for PcrV and OmpE. The predicted 3D structure showed C-score = -1 and Z-score = -8.12. Molecular docking indicated high interaction between residues of Toll-like receptor 2 (TLR2) and TLR4 with the multi-epitope. The results of in silico simulation of the immune responses showed elevated levels of B-cell, T-cell, and memory cells. PcrV, OmpE, and the multi-epitope were expressed in pET28a-E. coli BL21 (DE3) and purified by Nickel columns. Our findings indicated that the sera collected from immunized rabbits with the multi-epitope reacted with the multi-epitope, PcrV, and OmpE in western blot. According to the ELISA results, the antibody developed against the multi-epitope showed cross-reactivity with individual proteins PcrV and OmpE. The level of antibody raised against the multi-epitope was significantly higher than the antibody reacted with PcrV or OmpE alone in ELISA. The challenge results confirmed that the load of bacteria was decreased in immunized rabbits as compared to the control. The results present the multi-epitope composed of PcrV and OmpE as a promising candidate against P. aeruginosa. Further evaluations are under investigation in animal model.Communicated by Ramaswamy H. Sarma.

Development of a novel multi-epitope vaccine based on capsid and envelope protein against Chikungunya virus

Chikungunya virus (CHIKV), a type A virus borne by mosquitoes that can cause major clinical manifestations including rash, fever and debilitating arthritis, grown into a reemerging serious public health issue. Currently, there is no licensed therapy or vaccine available for CHIKV, although the most promising form of treatment appears to be immunotherapy. Neutralizing antibodies for CHIKV can provide high protection for all CHIKV strains, as well as other alphaviruses. Development of a protective vaccine may be an effective strategy to prevent the outbreak of CHIKV and provide protection for travelers. In this study, we designed a multi-epitope vaccine with a 543-amino-acid structure based on the E1, E2 and capsid proteins of CHIKV, including 6 CTL epitopes, 6 HTL epitopes, 12 linear B epitopes, along with the adjuvant β-defensin III. All T-cell epitopes were docked with their corresponding MHC alleles to validate their effect on inducing immune responses, and the vaccine's sequence was proven to have acceptable physicochemical properties. Further, the developed vaccine was docked with TLR3 and TLR8, both of which play an important role in recognizing RNA viruses. Basic analyses of the docked complexes and molecular dynamic simulations revealed that the vaccine interacted strongly with TLRs. Immunological simulations indicated that the vaccine could induce both cellular and humoral immunity. Hopefully, this proposed vaccine structure can serve as a viable candidate against CHIKV infection.Communicated by Ramaswamy H. Sarma.

Exploring computational approaches to design mRNA Vaccine against vaccinia and Mpox viruses

BACKGROUND

Messenger RNA (mRNA) vaccines emerged as a powerful tool in the fight against infections. Unlike traditional vaccines, this unique type of vaccine elicits robust and persistent innate and humoral immune response with a unique host cell-mediated pathogen gene expression and antigen presentation.

METHODS

This offers a novel approach to combat poxviridae infections. From the genome of vaccinia and Mpox viruses, three key genes (E8L, E7R, and H3L) responsible for virus attachment and virulence were selected and employed for designing the candidate mRNA vaccine against vaccinia and Mpox viral infection. Various bioinformatics tools were employed to generate (B cell, CTL, and HTL) epitopes, of which 28 antigenic and immunogenic epitopes were selected and are linked to form the mRNA vaccine construct. Additional components, including a 5' cap, 5' UTR, adjuvant, 3' UTR, and poly(A) tail, were incorporated to enhance stability and effectiveness. Safety measures such as testing for human homology and in silico immune simulations were implemented to avoid autoimmunity and to mimics the immune response of human host to the designed mRNA vaccine, respectively. The mRNA vaccine's binding affinity was evaluated by docking it with TLR-2, TLR-3, TLR-4, and TLR-9 receptors which are subsequently followed by molecular dynamics simulations for the highest binding one to predict the stability of the binding complex.

RESULTS

With a 73% population coverage, the mRNA vaccine looks promising, boasting a molecular weight of 198 kDa and a molecular formula of C8901H13609N2431O2611S48 and it is said to be antigenic, nontoxic and nonallergic, making it safe and effective in preventing infections with Mpox and vaccinia viruses, in comparison with other insilico-designed vaccine for vaccinia and Mpox viruses.

CONCLUSIONS

However, further validation through in vivo and in vitro techniques is underway to fully assess its potential.

Immunoinformatics approach for design novel multi-epitope prophylactic and therapeutic vaccine based on capsid proteins L1 and L2 and oncoproteins E6 and E7 of human papillomavirus 16 and human papillomavirus 18 against cervical cancer

BACKGROUND

This study aimed to identify the optimal protein construction for designing a multi-epitope vaccine with both prophylactic and therapeutic effects against cervical cancer, utilizing an immunoinformatics approach. The construction process involved using capsid epitopes L1 and L2, as well as oncoproteins E5, E6, and E7 from human papillomavirus (HPV) types 16 and 18.

METHODS

An experimental in silico analysis with an immunoinformatics approach was used to develop 2 multi-epitope vaccine constructs (A and B). Further analysis was then conducted to compare the constructs and select the one with the highest potential against cervical cancer.

RESULTS

This study produced 2 antigenic, non-allergenic, and nontoxic multi-epitope vaccine constructs (A and B), which exhibited the ideal physicochemical properties for a vaccine. Further analysis revealed that construct B effectively induced both cellular and humoral immune responses.

CONCLUSION

The multi-epitope vaccine construct B for HPV 16 and 18, designed for both prophylactic and therapeutic purposes, met the development criteria for a cervical cancer vaccine. However, these findings need to be validated through in vitro and in vivo experiments.

Immunoinformatic-guided novel mRNA vaccine designing to elicit immunogenic responses against the endemic Monkeypox virus

Monkeypox virus (MPXV) is an orthopoxvirus, causing zoonotic infections in humans with smallpox-like symptoms. The WHO reported MPXV cases in May 2022 and the outbreak caused significant morbidity threats to immunocompromised individuals and children. Currently, no clinically validated therapies are available against MPXV infections. The present study is based on immunoinformatics approaches to design mRNA-based novel vaccine models against MPXV. Three proteins were prioritized based on high antigenicity, low allergenicity, and toxicity values to predict T- and B-cell epitopes. Lead T- and B-cell epitopes were used to design vaccine constructs, linked with epitope-specific linkers and adjuvant to enhance immune responses. Additional sequences, including Kozak sequence, MITD sequence, tPA sequence, Goblin 5', 3' UTRs, and a poly(A) tail were added to design stable and highly immunogenic mRNA vaccine construct. High-quality structures were predicted by molecular modeling and 3D-structural validation of the vaccine construct. Population coverage and epitope-conservancy speculated broader protection of designed vaccine model against multiple MPXV infectious strains. MPXV-V4 was eventually prioritized based on its physicochemical and immunological parameters and docking scores. Molecular dynamics and immune simulations analyses predicted significant structural stability and binding affinity of the top-ranked vaccine model with immune receptors to elicit cellular and humoral immunogenic responses against the MPXV. The pursuance of experimental and clinical follow-up of these prioritized constructs may lay the groundwork to develop safe and effective vaccine against MPXV.Communicated by Ramaswamy H. Sarma.

An integrated in silico approach for the identification of novel potential drug target and chimeric vaccine against Neisseria meningitides strain 331401 serogroup X by subtractive genomics and reverse vaccinology

Neisseria meningitidis, commonly known as the meningococcus, leads to substantial illness and death among children and young adults globally, revealing as either epidemic or sporadic meningitis and/or septicemia. In this study, we have designed a novel peptide-based chimeric vaccine candidate against the N. meningitidis strain 331,401 serogroup X. Through rigorous analysis of subtractive genomics, two essential cytoplasmic proteins, namely UPI000012E8E0(UDP-3-O-acyl-GlcNAc deacetylase) and UPI0000ECF4A9(UDP-N-acetylglucosamine acyltransferase) emerged as potential drug targets. Additionally, using reverse vaccinology, the outer membrane protein UPI0001F4D537 (Membrane fusion protein MtrC) identified by subcellular localization and recognized for its known indispensable role in bacterial survival was identified as a novel chimeric vaccine target. Following a careful comparison of MHC-I, MHC-II, T-cell, and B-cell epitopes, three epitopes derived from UPI0001F4D537 were linked with three types of linkers-GGGS, EAAAK, and the essential PADRE-for vaccine construction. This resulted in eight distinct vaccine models (V1-V8). Among them V1 model was selected as the final vaccine construct. It exhibits exceptional immunogenicity, safety, and enhanced antigenicity, with 97.7 % of its residues in the Ramachandran plot's most favored region. Subsequently, the vaccine structure was docked with the TLR4/MD2 complex and six different HLA allele receptors using the HADDOCK server. The docking resulted in the lowest HADDOCK score of 39.3 ± 9.0 for TLR/MD2. Immune stimulation showed a strong immune response, including antibodies creation and the activation of B-cells, T Cytotoxic cells, T Helper cells, Natural Killer cells, and interleukins. Furthermore, the vaccine construct was successfully expressed in the Escherichia coli system by reverse transcription, optimization, and ligation in the pET-28a (+) vector for the expression study. The current study proposes V1 construct has the potential to elicit both cellular and humoral responses, crucial for the developing an epitope-based vaccine against N. meningitidis strain 331,401 serogroup X.

Designing multi-epitope vaccine against human cytomegalovirus integrating pan-genome and reverse vaccinology pipelines

Human cytomegalovirus (HCMV) is accountable for high morbidity in neonates and immunosuppressed individuals. Due to the high genetic variability of HCMV, current prophylactic measures are insufficient. In this study, we employed a pan-genome and reverse vaccinology approach to screen the target for efficient vaccine candidates. Four proteins, envelope glycoprotein M, UL41A, US23, and US28, were shortlisted based on cellular localization, high solubility, antigenicity, and immunogenicity. A total of 29 B-cell and 44 T-cell highly immunogenic and antigenic epitopes with high global population coverage were finalized using immunoinformatics tools and algorithms. Further, the epitopes that were overlapping among the finalized B-cell and T-cell epitopes were linked with suitable linkers to form various combinations of multi-epitopic vaccine constructs. Among 16 vaccine constructs, Vc12 was selected based on physicochemical and structural properties. The docking and molecular simulations of VC12 were performed, which showed its high binding affinity (-23.35 kcal/mol) towards TLR4 due to intermolecular hydrogen bonds, salt bridges, and hydrophobic interactions, and there were only minimal fluctuations. Furthermore, Vc12 eliciting a good response was checked for its expression in Escherichia coli through in silico cloning and codon optimization, suggesting it to be a potent vaccine candidate.

Reverse vaccinology-based multi-epitope vaccine design against Indian group A rotavirus targeting VP7, VP4, and VP6 proteins

Rotavirus, a primary contributor to severe cases of infantile gastroenteritis on a global scale, results in significant morbidity and mortality in the under-five population, particularly in middle to low-income countries, including India. WHO-approved live-attenuated vaccines are linked to a heightened susceptibility to intussusception and exhibit low efficacy, primarily attributed to the high genetic diversity of rotavirus, varying over time and across different geographic regions. Herein, molecular data on Indian rotavirus A (RVA) has been reviewed through phylogenetic analysis, revealing G1P[8] to be the prevalent strain of RVA in India. The conserved capsid protein sequences of VP7, VP4 and VP6 were used to examine helper T lymphocyte, cytotoxic T lymphocyte and linear B-cell epitopes. Twenty epitopes were identified after evaluation of factors such as antigenicity, non-allergenicity, non-toxicity, and stability. These epitopes were then interconnected using suitable linkers and an N-terminal beta defensin adjuvant. The in silico designed vaccine exhibited structural stability and interactions with integrins (αvβ3 and αIIbβ3) and toll-like receptors (TLR2 and TLR4) indicated by docking and normal mode analyses. The immune simulation profile of the designed RVA multiepitope vaccine exhibited its potential to trigger humoral as well as cell-mediated immunity, indicating that it is a promising immunogen. These computational findings indicate potential efficacy of the designed vaccine against rotavirus infection.

Contriving a novel of CHB therapeutic vaccine based on IgV_CTLA-4 and L protein via immunoinformatics approach

Chronic infection induced by immune tolerance to hepatitis B virus (HBV) is one of the most common causes of hepatic cirrhosis and hepatoma. Fortunately, the application of therapeutic vaccine can not only reverse HBV-tolerance, but also serve a potentially effective therapeutic strategy for treating chronic hepatitis B (CHB). However, the clinical effect of the currently developed CHB therapeutic vaccine is not optimistic due to the weak immunogenicity. Given that the human leukocyte antigen CTLA-4 owns strong binding ability to the surface B7 molecules (CD80 and CD86) of antigen presenting cell (APCs), the immunoglobulin variable region of CTLA-4 (IgV_CTLA-4) was fused with the L protein of HBV to contrive a novel therapeutic vaccine (V_C4HBL) for CHB in this study. We found that the addition of IgV_CTLA-4 did not interfere with the formation of L protein T cell and B cell epitopes after analysis by means of immunoinformatics approaches. Meanwhile, we also found that the IgV_CTLA-4 had strong binding force to B7 molecules through molecular docking and molecular dynamics (MD) simulation. Notably, our vaccine V_C4HBL showed good immunogenicity and antigenicity by in vitro and in vivo experiments. Therefore, the V_C4HBL is promising to again effectively activate the cellular and humoral immunity of CHB patients, and provides a potentially effective therapeutic strategy for the treatment of CHB in the future.Communicated by Ramaswamy H. Sarma.

Multi-epitope peptide vaccines targeting dengue virus serotype 2 created via immunoinformatic analysis

The Middle East has witnessed a greater spread of infectious Dengue viruses, with serotype 2 (DENV-2) being the most prevalent form. Through this work, multi-epitope peptide vaccines against DENV-2 that target E and nonstructural (NS1) proteins were generated through an immunoinformatic approach. MHC class I and II and LBL epitopes among NS1 and envelope E proteins sequences were predicted and their antigenicity, toxicity, and allergenicity were investigated. Studies of the population coverage denoted the high prevalence of NS1 and envelope-E epitopes among different countries where DENV-2 endemic. Further, both the CTL and HTL epitopes retrieved from NS1 epitopes exhibited high conservancies' percentages with other DENV serotypes (1, 3, and 4). Three vaccine constructs were created and the expected immune responses for the constructs were estimated using C-IMMSIM and HADDOCK (against TLR 2,3,4,5, and 7). Molecular dynamics simulation for vaccine construct 2 with TLR4 denoted high binding affinity and stability of the construct with the receptor which might foretell favorable in vivo interaction and immune responses.

Design of multi-epitope vaccine candidate based on OmpA, CarO and ZnuD proteins against multi-drug resistant Acinetobacter baumannii

Acinetobacter baumannii has been identified as a major cause of nosocomial infections. Acinetobacter infections are often difficult to treat with multidrug resistant phenotypes. One of the most effective ways to combat infectious diseases is through vaccination. In this study, an attempt was made to select the most protective and potent immunostimulatory epitopes based on the epitope-rich domains of the ZnuD, OmpA and CarO proteins of Acinetobacter baumannii to design a vaccine that can protect against this infection. After predicting the epitope of B- and T-cells, seven antigenic regions of three proteins CarO, ZnuD and OmpA, were selected. These regions were bound by a GGGS linker. The binding affinity and molecular interactions of the vaccine with the immune receptors TLR2 and TLR4 were studied using molecular docking analysis. This vaccine design was subjected to in silico immune simulations using C-ImmSim. The designed vaccine was highly antigenic, non-allergenic and stable. TLR2 and TLR4 were selected to analyze the ability of the modeled chimeric protein to interact with immune system receptors. The results showed strong interaction between the designed protein vaccine with TLR2 (-18.8 kcal mol-1) and TLR4 (-15.1 kcal mol-1). To verify the stability of the interactions and the structure of the designed protein, molecular dynamics (MD) simulations were performed for 200 ns. Various analyses using MD showed that the protein structure is stable alone and in interaction with TLR2 and TLR4. The ability of the vaccine candidate protein to stimulate the immune system to produce the necessary cytokines and antibodies against Acinetobacter baumannii was also demonstrated by the ability of the protein designed using the C-ImmSim web server to induce an immune response. Therefore, the designed protein vaccine may be a suitable candidate for in vivo as well as in vitro studies against Acinetobacter baumannii infections.

Revolutionizing Nipah virus vaccinology: insights into subunit vaccine development strategies and immunological advances

The Nipah virus (NiV), a zoonotic virus in the Henipavirus genus of the Paramyxoviridae family, emerged in Malaysia in 1998 and later spread globally. Diseased patients may have a 40- 70% chance of fatality depending on the severity and early medication. The recent outbreak of NiV was reported in Kerala (India) by a new strain of MCL-19-H-1134 isolate. Currently, no vaccines are available, highlighting the critical need for a conclusive remedy. Our study aims to develop a subunit vaccine against the NiV by analyzing its proteome. NiV genome and proteome sequences were obtained from the NCBI database. A phylogenetic tree was constructed based on genome alignment. T-cell, helper T-cell, and B-cell epitopes were predicted from the protein sequences using NetCTL-1.2, NetMHCIIPan-4.1, and IEDB servers, respectively. High-affinity epitopes for human receptors were selected to construct a multi-epitope vaccine (MEV). These epitopes' antigenicity, toxicity, and allergenicity were evaluated using VaxiJen, AllergenFP-v.1.0, and AllergenFP algorithms. Molecular interactions with specific receptors were analyzed using PyRx and ClusPro. Amino acid interactions were visualized and analyzed using PyMOL and LigPlot. Immuno-simulation was conducted using C-ImmSim to assess the immune response elicited by the MEV. Finally, the vaccine cDNA was inserted into the pET28a(+) expression vector using SnapGene tool for in silico cloning in an E. coli host. The potential for an imminent outbreak cannot be overlooked. A subunit vaccine is more cost-effective and time-efficient. With additional in vitro and in vivo validation, this vaccine could become a superior preventive measure against NiV disease.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-024-00246-9.