Design of a multi-epitope-based vaccine targeting M-protein of SARS-CoV2: an immunoinformatics approach

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.

Development of T cell antigen-based human coronavirus vaccines against nAb-escaping SARS-CoV-2 variants

Currently approved vaccines have been successful in preventing the severity of COVID-19 and hospitalization. These vaccines primarily induce humoral immune responses; however, highly transmissible and mutated variants, such as the Omicron variant, weaken the neutralization potential of the vaccines, thus, raising serious concerns about their efficacy. Additionally, while neutralizing antibodies (nAbs) tend to wane more rapidly than cell-mediated immunity, long-lasting T cells typically prevent severe viral illness by directly killing infected cells or aiding other immune cells. Importantly, T cells are more cross-reactive than antibodies, thus, highly mutated variants are less likely to escape lasting broadly cross-reactive T cell immunity. Therefore, T cell antigen-based human coronavirus (HCoV) vaccines with the potential to serve as a supplementary weapon to combat emerging SARS-CoV-2 variants with resistance to nAbs are urgently needed. Alternatively, T cell antigens could also be included in B cell antigen-based vaccines to strengthen vaccine efficacy. This review summarizes recent advancements in research and development of vaccines containing T cell antigens or both T and B cell antigens derived from proteins of SARS-CoV-2 variants and/or other HCoVs based on different vaccine platforms.

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.

Computational method for designing vaccines applied to virus-like particles (VLPs) as epitope carriers

Nonenveloped virus-like particles (VLPs) are self-assembled oligomeric structures composed of one or more proteins that originate from diverse viruses. Because these VLPs have similar antigenicity to the parental virus, they are successfully used as vaccines against cognate virus infection. Furthermore, after foreign antigenic sequences are inserted in their protein components (chimVLPs), some VLPs are also amenable to producing vaccines against pathogens other than the virus it originates from (these VLPs are named platform or epitope carrier). Designing chimVLP vaccines is challenging because the immunogenic response must be oriented against a given antigen without altering stimulant properties inherent to the VLP. An important step in this process is choosing the location of the sequence modifications because this must be performed without compromising the assembly and stability of the original VLP. Currently, many immunogenic data and computational tools can help guide the design of chimVLPs, thus reducing experimental costs and work. In this study, we analyze the structure of a novel VLP that originate from an insect virus and describe the putative regions of its three structural proteins amenable to insertion. For this purpose, we employed molecular dynamics (MD) simulations to assess chimVLP stability by comparing mutated and wild-type (WT) VLP protein trajectories. We applied this procedure to design a chimVLP that can serve as a prophylactic vaccine against the SARS-CoV-2 virus. The methodology described in this work is generally applicable for VLP-based vaccine development.

Evaluation of humoral and cellular immune responses against Vibrio cholerae using oral immunization by multi-epitope-phage-based vaccine

INTRODUCTION

Cholera is a severe gastrointestinal disease that manifests with rapid onset of diarrhea, vomiting, and high mortality rates. Due to its widespread occurrence in impoverished communities with poor water sanitation, there is an urgent demand for a cost-effective and highly efficient vaccine. Multi-epitope vaccines containing dominant immunological epitopes and adjuvant compounds have demonstrated potential in boosting the immune response.

MATERIAL AND METHODS

B and T epitopes of OMPU, OMPW, TCPA, CTXA, and CTXB proteins were predicted using bioinformatics methods. Subsequently, highly antigenic multi-epitopes that are non-allergenic and non-toxic were synthesized. These multi-epitopes were then cloned into the pCOMB phagemid. A plasmid M13KO7ΔpIII containing all helper phage proteins except pIII was created to produce the recombinant phage. Female Balb/c mice were divided into three groups and immunized accordingly. The mice received the helper phage, recombinant phage or PBS via gavage feeding thrice within two weeks. Serum samples were collected before and after immunization for the ELISA test as well as evaluating immune system induction through ELISpot testing of spleen lymphocytes.

RESULTS

The titer of the recombinant phage was determined to be 1011 PFU/ml. The presence of the recombinant phage was confirmed through differences in optical density between sample and control groups in the ELISA phage technique, as well as by observing transduction activity, which demonstrated successful production of a recombinant phage displaying the Vibrio multi-epitope on M13 phage pIII. ELISA results revealed significant differences in phage antibodies before and after inoculation, particularly notable in the negative control mice. Mice treated with multi-epitope phages exhibited antibodies against Vibrio cholerae lysate. Additionally, ELISpot results indicated activation of cellular immunity in mice receiving both Vibrio and helper phage.

CONCLUSION

This study emphasizes the potential of multi-epitope on phage to enhance both cellular and humoral immunity in mice, demonstrating how phages can be used as adjuvants to stimulate mucosal immunity and act as promising candidates for oral vaccination.

A novel chimeric vaccine containing multiple epitopes for simulating robust immune activation against Klebsiella pneumoniae

BACKGROUND

Due to antibiotic resistance, the Klebsiella genus is linked to morbidity and death, necessitating the development of a universally protective vaccine against Klebsiella pathogens.

METHODS

Core sequence analysis prioritized non-redundant host molecules and expected lipid bilayer peptides from fully sequenced Klebsiella genomes. These proteins were refined to identify epitopes, examining their immunogenicity, toxicity, solubility, and interaction with MHC alleles. Epitopes were linked to CPG ODN C274 via EAAAK, HEYGAEALERAG, and GGGS linkers to enhance immunological responses. The vaccine's tertiary structure was modelled and docked with MHC-I and MHC-II.

RESULTS

Fifty-five proteins were recognized in the Vaxign collection as having remarkable features. Twenty-three proteins with potential pathogenicity were then identified. Eight options for vaccines emerged after the immunogenicity of proteins was examined. The best antigens were three proteins: MrkD, Iron-regulated lipid membrane polypeptides, and RmpA. These compounds were selected for their sensitivity. The structural protein sequences of K. pneumoniae were utilized to identify seven CTL epitopes, seven HTL epitopes, and seven LBL epitopes, respectively. The produced immunization displayed a stable contact with the receptors, based on molecular dynamic simulations lasting 250 nanoseconds. Intermolecular binding free energies also indicated the dominance of the van der Waals and electrostatic energies.

CONCLUSION

In summary, the results of this study might help scientists develop a novel vaccine to prevent K. pneumoniae infections.

Designing of a multi-epitopes based vaccine against Haemophilius parainfluenzae and its validation through integrated computational approaches

Haemophilus parainfluenzae is a Gram-negative opportunist pathogen within the mucus of the nose and mouth without significant symptoms and has an ability to cause various infections ranging from ear, eye, and sinus to pneumonia. A concerning development is the increasing resistance of H. parainfluenzae to beta-lactam antibiotics, with the potential to cause dental infections or abscesses. The principal objective of this investigation is to utilize bioinformatics and immuno-informatic methodologies in the development of a candidate multi-epitope Vaccine. The investigation focuses on identifying potential epitopes for both B cells (B lymphocytes) and T cells (helper T lymphocytes and cytotoxic T lymphocytes) based on high non-toxic and non-allergenic characteristics. The selection process involves identifying human leukocyte antigen alleles demonstrating strong associations with recognized antigenic and overlapping epitopes. Notably, the chosen alleles aim to provide coverage for 90% of the global population. Multi-epitope constructs were designed by using suitable linker sequences. To enhance the immunological potential, an adjuvant sequence was incorporated using the EAAAK linker. The final vaccine construct, comprising 344 amino acids, was achieved after the addition of adjuvants and linkers. This multi-epitope Vaccine demonstrates notable antigenicity and possesses favorable physiochemical characteristics. The three-dimensional conformation underwent modeling and refinement, validated through in-silico methods. Additionally, a protein-protein molecular docking analysis was conducted to predict effective binding poses between the multi-epitope Vaccine and the Toll-like receptor 4 protein. The Molecular Dynamics (MD) investigation of the docked TLR4-vaccine complex demonstrated consistent stability over the simulation period, primarily attributed to electrostatic energy. The docked complex displayed minimal deformation and enhanced rigidity in the motion of residues during the dynamic simulation. Furthermore, codon translational optimization and computational cloning was performed to ensure the reliability and proper expression of the multi-Epitope Vaccine. It is crucial to emphasize that despite these computational validations, experimental research in the laboratory is imperative to demonstrate the immunogenicity and protective efficacy of the developed vaccine. This would involve practical assessments to ascertain the real-world effectiveness of the multi-epitope Vaccine.

Designing a Novel Multiepitope Vaccine from the Human Papilloma Virus E1 and E2 Proteins for Indonesia with Immunoinformatics and Molecular Dynamics Approaches

One of the deadliest malignant cancer in women globally is cervical cancer. Specifically, cervical cancer is the second most common type of cancer in Indonesia. The main infectious agent of cervical cancer is the human papilloma virus (HPV). Although licensed prophylactic vaccines are available, cervical cancer cases are on the rise. Therapy using multiepitope-based vaccines is a very promising therapy for cervical cancer. This study aimed to develop a multiepitope vaccine based on the E1 and E2 proteins of HPV 16, 18, 45, and 52 using in silico. In this study, we develop a novel multiepitope vaccine candidate using an immunoinformatic approach. We predicted the epitopes of the cytotoxic T lymphocyte (CTL) and helper T lymphocyte (HTL) and evaluated their immunogenic properties. Population coverage analysis of qualified epitopes was conducted to determine the successful use of the vaccine worldwide. The epitopes were constructed into a multiepitope vaccine by using AAY linkers between the CTL epitopes and GPGPG linkers between the HTL epitopes. The tertiary structure of the multiepitope vaccine was modeled with AlphaFold and was evaluated by Prosa-web. The results of vaccine construction were analyzed for B-cell epitope prediction, molecular docking with Toll like receptor-4 (TLR4), and molecular dynamics simulation. The results of epitope prediction obtained 4 CTL epitopes and 7 HTL epitopes that are eligible for construction of multiepitope vaccines. Prediction of the physicochemical properties of multiepitope vaccines obtained good results for recombinant protein production. The interaction showed that the interaction of the multiepitope vaccine-TLR4 complex is stable based on the binding free energy value -106.5 kcal/mol. The results of the immune response simulation show that multiepitope vaccine candidates could activate the adaptive and humoral immune systems and generate long-term B-cell memory. According to these results, the development of a multiepitope vaccine with a reverse vaccinology approach is a breakthrough to develop potential cervical cancer therapeutic vaccines.

Construction by artificial intelligence and immunovalidation of hypoallergenic mite allergen Der f 36 vaccine

Background

The house dust mite (HDM) is widely recognized as the most prevalent allergen in allergic diseases. Allergen-specific immunotherapy (AIT) has been successfully implemented in clinical treatment for HDM. Hypoallergenic B-cell epitope-based vaccine designed by artificial intelligence (AI) represents a significant progression of recombinant hypoallergenic allergen derivatives.

Method

The three-dimensional protein structure of Der f 36 was constructed using Alphafold2. AI-based tools were employed to predict B-cell epitopes, which were subsequently verified through IgE-reaction testing. Hypoallergenic Der f 36 was then synthesized, expressed, and purified. The reduced allergenicity was assessed by enzyme-linked immunosorbent assay (ELISA), immunoblotting, and basophil activation test. T-cell response to hypoallergenic Der f 36 and Der f 36 was evaluated based on cytokine expression in the peripheral blood mononuclear cells (PBMCs) of patients. The immunogenicity was evaluated and compared through rabbit immunization with hypoallergenic Der f 36 and Der f 36, respectively. The inhibitory effect of the blocking IgG antibody on the specific IgE-binding activity and basophil activation of Der f 36 allergen was also examined.

Results

The final selected non-allergic B-cell epitopes were 25-48, 57-67, 107-112, 142-151, and 176-184. Hypoallergenic Der f 36 showed significant reduction in IgE-binding activity. The competitive inhibition of IgE-binding to Der f 36 was investigated using the hypoallergenic Der f 36, and only 20% inhibition could be achieved, which is greatly reduced when compared with inhibition by Der f 36 (98%). The hypoallergenic Der f 36 exhibited a low basophil-stimulating ratio similar to that of the negative control, and it could induce an increasing level of IFN-γ but not Th2 cytokines IL-5 and IL-13 in PBMCs. The vaccine-specific rabbit blocking IgG antibodies could inhibit the patients' IgE binding and basophil stimulation activity of Derf 36.

Conclusion

This study represents the first application of an AI strategy to facilitate the development of a B-cell epitope-based hypoallergenic Der f 36 vaccine, which may become a promising immunotherapy for HDM-allergic patients due to its reduced allergenicity and its high immunogenicity in inducing blocking of IgG.

Design of a multi-epitope vaccine against goatpox virus using an immunoinformatics approach

Introduction

Goatpox, a severe infectious disease caused by goatpox virus (GTPV), leads to enormous economic losses in the livestock industry. Traditional live attenuated vaccines cause serious side effects and exist a risk of dispersal. Therefore, it is urgent to develop efficient and safer vaccines to prevent and control of GTPV.

Methods

In the present study, we are aimed to design a multi-epitope subunit vaccine against GTPV using an immunoinformatics approach. Various immunodominant cytotoxic T lymphocytes (CTL) epitopes, helper T lymphocytes (HTL) epitopes, and B-cell epitopes from P32, L1R, and 095 proteins of GTPV were screened and liked by the AAY, GPGPG, and KK connectors, respectively. Furthermore, an adjuvant β-defensin was attached to the vaccine's N-terminal using the EAAAK linker to enhance immunogenicity.

Results

The constructed vaccine was soluble, non-allergenic and non-toxic and exhibited high levels of antigenicity and immunogenicity. The vaccine's 3D structure was subsequently predicted, refined and validated, resulting in an optimized model with a Z-value of -3.4. Molecular docking results demonstrated that the vaccine had strong binding affinity with TLR2(-27.25 kcal/mol), TLR3(-39.84 kcal/mol), and TLR4(-59.42 kcal/mol). Molecular dynamics simulation results indicated that docked vaccine-TLR complexes were stable. Immune simulation analysis suggested that the vaccine can induce remarkable increase in antibody titers of IgG and IgM, higher levels of IFN-γ and IL-2.

Conclusion

The designed GTPV multi-epitope vaccine is structurally stable and can induce robust humoral and cellular immune responses, which may be a promising vaccine candidate against GTPV.

Structure-based evaluation of the envelope domain III-nonstructural protein 1 (EDIII-NS1) fusion as a dengue virus vaccine candidate

The lack of effective medicines or vaccines, combined with climate change and other environmental factors, annually subjects a significant proportion of the world's inhabitants to the risk of dengue virus (DENV) infection. These conditions increase the likelihood of exposure to mosquito-borne diseases such as dengue fever. Hence, many research approaches tend to develop efficient vaccine candidates against the dengue virus. Therefore, we used immunoinformatics and bioinformatics to design a construction for developing a candidate vaccine against dengue virus serotypes. In this study, the in silico structure, containing the non-structural protein 1 region (NS1) (consensus and epitope), the envelope domain III protein (EDIII) as the structural part of the virus construction, and the bc-loop of envelope domain II (EDII) as the neutralizing and protected epitope, were employed. We utilized in silico tools to enhance the immunogenicity and effectiveness of dengue virus vaccine candidates. Evaluations included refining and validating physicochemical characteristics, B and T-cell epitopes, homology modeling, and the three-dimensional structure to assess the designed vaccine's quality. In silico results for tertiary structure prediction and validation revealed high-quality modeling for all vaccine constructs. Additionally, the instructed model demonstrated stability throughout molecular dynamics simulation. The results of the immune simulation suggested that the titers of IgG and IgM could be raised to desirable values following injection into in vivo models. It can be concluded that the designed construct effectively induce humoral and cellular immunity and can be proposed as effective vaccine candidate against four dengue serotypes.Communicated by Ramaswamy H. Sarma.

Immunoinformatics-driven approach for development of potential multi-epitope vaccine against the secreted protein FlaC of Campylobacter jejuni

Campylobacter jejuni causes a leading human gastrointestinal infection which is associated with foodborne diarrhea, stomach cramping, and fever. In the recent years, numerous multidrug-resistant strains of C. jejuni has evolved and is considered in the priority pathogens category. Therefore, an increasing demand exists to develop an effective vaccine against Campylobacteriosis. The T cell and B cell epitopes from the FlaC protein were predicted using comprehensive immunoinformatics tools. The predicted epitopes were chosen based on their antigenicity, allergenicity, and toxicity profiles. Using the bioinformatics approach various physicochemical properties of the constructed vaccine were determined. The molecular docking analysis of the vaccine with the TLRs demonstrated that TLR5 has a higher binding affinity of -1159.0 kcal/mol. Molecular dynamics simulation has confirmed the stable association of the vaccine with TLR5. The immune response of the constructed vaccine was validated using immunostimulation. Based on this study, we recommend the formulation of a multi-epitope vaccine as a promising agent to effectively combat the dreadful campylobacteriosis infection.Communicated by Ramaswamy H. Sarma.

Development and immunological evaluation of an mRNA-based vaccine targeting Naegleria fowleri for the treatment of primary amoebic meningoencephalitis

More than 95% of patients fall victim to primary amoebic meningoencephalitis (PAM), a fatal disease attacking the central nervous system. Naegleria fowleri, a brain-eating microorganism, is PAM's most well-known pathogenic ameboflagellate. Despite the use of antibiotics, the fatality rate continues to rise as no clinical trials have been conducted against this disease. To address this, we mined the UniProt database for pathogenic proteins and selected assumed epitopes to create an mRNA-based vaccine. We identified thirty B-cell and T-cell epitopes for the vaccine candidate. These epitopes, secretion boosters, subcellular trafficking structures, and linkers were used to construct the vaccine candidate. Through predictive modeling and confirmation via the Ramachandran plot (with a quality factor of 92.22), we assessed secondary and 3D structures. The adjuvant RpfE was incorporated to enhance the vaccine construct's immunogenicity (GRAVY index: 0.394, instability index: 38.99, antigenicity: 0.8). The theoretical model of immunological simulations indicated favorable responses from both innate and adaptive immune cells, with memory cells expected to remain active for up to 350 days post-vaccination, while the antigen was eliminated from the body within 24 h. Notably, strong interactions were observed between the vaccine construct and TLR-4 (- 11.9 kcal/mol) and TLR-3 (- 18.2 kcal/mol).

Systematic review of reverse vaccinology and immunoinformatics data for non-viral sexually transmitted infections

Sexually Transmitted Infections (STIs) are a public health burden rising in developed and developing nations. The World Health Organization estimates nearly 374 million new cases of curable STIs yearly. Global efforts to control their spread have been insufficient in fulfilling their objective. As there is no vaccine for many of these infections, these efforts are focused on education and condom distribution. The development of vaccines for STIs is vital for successfully halting their spread. The field of immunoinformatics is a powerful new tool for vaccine development, allowing for the identification of vaccine candidates within a bacterium's genome and allowing for the design of new genome-based vaccine peptides. The goal of this review was to evaluate the usage of immunoinformatics in research focused on non-viral STIs, identifying fields where research efforts are concentrated. Here we describe gaps in applying these techniques, as in the case of Treponema pallidum and Trichomonas vaginalis.

Development of a multi-epitope vaccine candidate for leishmanial parasites applying immunoinformatics and in vitro approaches

Leishmaniasis is a neglected tropical disease, and its severity necessitates the development of a potent and efficient vaccine for the disease; however, no human vaccine has yet been approved for clinical use. This study aims to design and evaluate a multi-epitope vaccine against the leishmanial parasite by utilizing helper T-lymphocyte (HTL), cytotoxic T-lymphocyte (CTL), and linear B-lymphocyte (LBL) epitopes from membrane-bound acid phosphatase of Leishmania donovani (LdMAcP). The designed multi-epitope vaccine (LdMAPV) was highly antigenic, non-allergenic, and non-toxic, with suitable physicochemical properties. The three-dimensional structure of LdMAPV was modeled and validated, succeeded by molecular docking and molecular dynamics simulation (MDS) studies that confirmed the high binding affinity and stable interactions between human toll-like receptors and LdMAPV. In silico disulfide engineering provided improved stability to LdMAPV, whereas immune simulation displayed the induction of both immune responses, i.e., antibody and cell-mediated immune responses, with a rise in cytokines. Furthermore, LdMAPV sequence was codon optimized and cloned into the pET-28a vector, followed by its expression in a bacterial host. The recombinant protein was purified using affinity chromatography and subjected to determine its effect on cytotoxicity, cytokines, and nitric oxide generation by mammalian macrophages. Altogether, this report provides a multi-epitope vaccine candidate from a leishmanial protein participating in parasitic virulence that has shown its potency to be a promising vaccine candidate against leishmanial parasites.

Development of multi-epitope based subunit vaccine against Mycobacterium Tuberculosis using immunoinformatics approach

The etiological agent of tuberculosis (TB), Mycobacterium tuberculosis, is a deadly pathogen that adapts to thrive within the host. Since 2020, the COVID-19 pandemic has had colossal health, societal, and economic consequences, which have affected the reporting of new incidences and mortality cases of TB. As per the WHO 2022 report, 10.6 million people were diagnosed with TB, and 1.6 million died worldwide. The increase in resistant strains of tuberculosis is making it more burdensome to reach the End TB strategy. A reliable and efficient TB vaccine that may avert both primary infection and recurrence of latent TB in adults and adolescents is of the utmost importance. In this study, we used computational techniques to predict the ability of HLA molecules to display epitopes for six TB proteins (PPE68, PE_PGRS17, EspC, LDT4, RpfD, and RpfC) to design the multi-epitope subunit vaccine. From the aimed proteins, the potential B-cell, helper T lymphocyte (HTL), and cytotoxic T lymphocyte (CTL) epitopes were predicted and linked together with LPA adjuvant, and the vaccine was designed. The vaccine's physicochemical analysis demonstrates that it is non-allergic, non-toxic, and antigenic. Then, the vaccine structure was predicted, improved, and verified to yield the optimal structure. The developed vaccine's binding mechanism with distinct immunogenic receptors (Tlr2 and MHC-II) was assessed utilizing molecular docking. The molecular dynamic simulation and MMPBSA analysis were performed to comprehend the complexes' dynamics and stability. The immune simulation was utilized to anticipate the vaccine's immunogenic attributes. In silico cloning was employed to demonstrate the efficient expression of the designed vaccine in E. coli as a host. Moreover, in vitro and in vivo animal testing is required to determine the efficacy of the in silico developed vaccine.Communicated by Ramaswamy H. Sarma.

Designing of Multi-Epitope Peptide Vaccine Based on Outer Membrane Proteins OmpF, OmpC, and PgtE of Salmonella entericaTyphi

Consumption of contaminated water and foods by Salmonella Typhi cause the most common enteric disease known as Typhoid fever in both humans and animals. Despite the existence of various vaccines but infectious diseases remain a major cause of mortality worldwide. Nowadays, in-silico tools design a reliable and stable vaccine to combat such infections. The study aimed to design and evaluate a multi-epitope vaccine based on the outer-membrane proteins of Salmonella Typhi. B-cells and T-cells epitopes were predicted. Predicted epitopes were connected by AAY, KK, and GPGPG linkers. Heparin-Binding Hemagglutinin Adhesin (HBHA) has been attached to the N-terminal of the final vaccine as a potent immune adjuvant. Epitope's antigenicity, allergenicity, immunogenicity, and physicochemical characteristics were defined using in-silico tools. Molecular docking of vaccine-TLR4 was done. ∆G of vaccine-TLR4 is -3.91×104 Kcal mol-1 with 1.93 RMSD. The results indicated protein was stable and non-allergen. In conclusion, the multi-epitope vaccine base on outer membrane proteins of the Salmonella Typhi bacterium might be considered to combat typhoid fever.

Designing a novel multi-epitopes pan-vaccine against SARS-CoV-2 and seasonal influenza: in silico and immunoinformatics approach

The merger of COVID-19 and seasonal influenza infections is considered a potentially serious threat to public health. These two viral agents can cause extensive and severe lower and upper respiratory tract infections with lung damage with host factors. Today, the development of vaccination has been shown to reduce the risk of hospitalization and mortality from the COVID-19 virus and influenza epidemics. Therefore, this study contributes to an immunoinformatics approach to producing a vaccine that can elicit strong and specific immune responses against COVID-19 and influenza A and B viruses. The NCBI, GISAID, and Uniprot databases were used to retrieve sequences. Linear B cell, Cytotoxic T lymphocyte, and Helper T lymphocyte epitopes were predicted using the online servers. Population coverage of MHC I epitopes worldwide for SARS-CoV-2, Influenza virus H3N2, H3N2, and Yamagata/Victoria were 99.93%, 68.67%, 68.38%, and 85.45%, respectively. Candidate epitopes were linked by GGGGS, GPGPG, and KK linkers. Different epitopes were permutated several times to form different peptides and then screened for antigenicity, allergenicity, and toxicity. The vaccine construct was analyzed for physicochemical properties, conformational B-cell epitopes, interaction with Toll-like receptors, and IFN-gamma-induced. Immune stimulation response of final construct was evaluated using C-IMMSIM. Eventually, the final construct sequence was codon-optimized for Escherichia coli K12 and Homo sapiens to design a multi-epitope vaccine and mRNA vaccine. In conclusion, due to the variable nature of SARS-CoV-2 and influenza proteins, the design of a multi-epitope vaccine can protect against all their standard variants, but laboratory validation is required.Communicated by Ramaswamy H. Sarma.

Designing a multi-epitope vaccine to control porcine epidemic diarrhea virus infection using immunoinformatics approaches

Porcine epidemic diarrhea virus (PEDV), a continuously evolving pathogen, causes severe diarrhea in piglets with high mortality rates. However, current vaccines cannot provide complete protection against PEDV, so vaccine development is still necessary and urgent. Here, with the help of immunoinformatics approaches, we attempted to design a multi-epitope vaccine named rPMEV to prevent and control PEDV infection. The epitopes of rPMEV were constructed by 9 cytotoxic T lymphocyte epitopes (CTLs), 11 helper T lymphocyte epitopes (HTLs), 6 linear B cell epitopes (LBEs), and 4 conformational B cell epitopes (CBEs) based on the S proteins from the four representative PEDV G2 strains. To enhance immunogenicity, porcine β-defensin-2 (PBD-2) was adjoined to the N-terminal of the vaccine as an adjuvant. All of the epitopes and PBD-2 were joined by corresponding linkers and recombined into the multivalent vaccine, which is stable, antigenic, and non-allergenic. Furthermore, we adopted molecular docking and molecular dynamics simulation methods to analyze the interaction of rPMEV with the Toll-like receptor 4 (TLR4): a stable interaction between them created by 13 hydrogen bonds. In addition, the results of the immune simulation showed that rPMEV could stimulate both cellular and humoral immune responses. Finally, to raise the expression efficiency, the sequence of the vaccine protein was cloned into the pET28a (+) vector after the codon optimization. These studies indicate that the designed multi-epitope vaccine has a potential protective effect, providing a theoretical basis for further confirmation of its protective effect against PEDV infection in vitro and in vivo studies.

Reverse vaccinology and immunoinformatics approaches to design multi-epitope based vaccine against oncogenic KRAS

Mutant KRAS-induced tumorigenesis is highly involved in the progression of pancreatic, lung, and breast cancer. Comparatively, KRAS G12D and KRAS G12C are the most frequent mutations that promote cancer progression and aggressiveness. Although KRAS mutant inhibitors exhibit significant therapeutic potential, day by day, they are becoming resistant among patients. Multi-epitope based cancer vaccines are a promising alternative strategy that induces an immune response against tumor antigens. In the present study, we have designed, constructed, and validated a novel multi-epitope vaccine construct against KRAS G12D and G12C mutants using reverse vaccinology and immunoinformatics approaches. In addition, the vaccine construct was structurally refined and showed significant physiochemical properties, and could induce an immune response. Furthermore, the optimized vaccine construct was cloned into a pET‑28a (+) expression vector through in silico cloning. Conclusively, the multi-epitope vaccine construct is structurally stable, soluble, antigenic, non‑allergic, and non‑toxic. Further, it has to be studied in in vitro and in vivo to evaluate its therapeutic efficacy against KRAS-mutated cancers in the near future.

Designing a novel SOX9 based multi-epitope vaccine to combat metastatic triple-negative breast cancer using immunoinformatics approach

Immunotherapies are a promising treatment option especially for the management of TNBC owing to its higher levels of tumour-associated antigens together with higher mutational load. Of note, the administration of preventive vaccines in the early stage of the cancer holds promise for effective disease management. Therefore, the present study aimed to develop a novel multi-epitope peptide-based vaccination against TNBC employing SOX9, which has recently been recognized as a key regulator of TNBC metastasis. The immunodominant regions from the SOX9 protein were computed and assessed based on their ability to elicit both T and B lymphocyte mediated responses. The resultant epitopes were fused using appropriate linkers (EAAAK, KK, AAY and GPGPG) and adjuvant (50S ribosomal protein L7/L12) to enhance the vaccine's immunogenicity. The physicochemical properties and population coverage were also anticipated for the constructed vaccine. Adding together, docking and dynamics simulation studies were performed on the modelled vaccine against TLR-4 to provide insight into the stability. Finally, the designed vaccine was cloned into the pET28 (+) vector and immunological simulation studies were carried out. These results demonstrate that our designed vaccine had the potency to trigger humoral and cellular immune responses. Based on these collective evidences, the final proposed vaccine could be an interesting therapeutics for the management of TNBC in the near future. Schematic representation of an efficient vaccine design framework by combining the range of immunoinformatics strategies.

Design and generation of mRNAs encoding conserved regions of SARS-CoV-2 ORF1ab for T cell-mediated immune activation

Aim

To generate mRNAs encoding conserved regions within SARS-CoV-2 ORF1ab which can induce strong T-cell responses to overcome the immune invasion of newly emergent variants.

Methods

We selected two conserved regions with a high density of T-cell epitopes using immunoinformatics for mRNA synthesis. The ability of testing mRNAs to activate T cells for IFN-γ production was examined by an ELISpot assay and flow cytometry.

Results

Two synthesized mRNAs were successfully translated in MDA-MB-231 cells and had comparable potency to the spike mRNA to induce CD4+ and CD8+ T-cell responses in peripheral blood mononuclear cells in 29 out of 34 participants.

Conclusion

This study provides a proof-of-concept for the use of SARS-CoV-2 conserved regions to develop booster vaccines capable of eliciting T-cell-mediated immunity.

Vaccinomics Approach for Multi-Epitope Vaccine Design against Group A Rotavirus Using VP4 and VP7 Proteins

Rotavirus A is the most common cause of Acute Gastroenteritis globally among children <5 years of age. Due to a segmented genome, there is a high frequency of genetic reassortment and interspecies transmission which has resulted in the emergence of novel genotypes. There are concerns that monovalent (Rotarix: GlaxoSmithKline Biologicals, Rixensart, Belgium) and pentavalent (RotaTeq: MERCK & Co., Inc., Kenilworth, NJ, USA) vaccines may be less effective against non-vaccine strains, which clearly shows the demand for the design of a vaccine that is equally effective against all circulating genotypes. In the present study, a multivalent vaccine was designed from VP4 and VP7 proteins of RVA. Epitopes were screened for antigenicity, allergenicity, homology with humans and anti-inflammatory properties. The vaccine contains four B-cell, three CTL and three HTL epitopes joined via linkers and an N-terminal RGD motif adjuvant. The 3D structure was predicted and refined preceding its docking with integrin. Immune simulation displayed promising results both in Asia and worldwide. In the MD simulation, the RMSD value varied from 0.2 to 1.6 nm while the minimum integrin amino acid fluctuation (0.05-0.1 nm) was observed with its respective ligand. Codon optimization was performed with an adenovirus vector in a mammalian expression system. The population coverage analysis showed 99.0% and 98.47% in South Asia and worldwide, respectively. These computational findings show potential against all RVA genotypes; however, in-vitro/in-vivo screening is essential to devise a meticulous conclusion.

Design of a multi-epitopic vaccine against Epstein-Barr virus via computer-based methods

Background

Scientific findings have shown that Epstein-Barr virus (EBV) plays a key role in the development of some tumor diseases. Therefore, this study intends to take a practical step in controlling the pathogenicity of this virus by designing an effective vaccine based on the virus Capsid Envelope and Epstein–Barr nuclear immunogen (EBNA) Proteins Epitopes. Currently, there are no effective drugs or vaccines to treat or prevent EBV infection. So, we applied a computer-based strategy to design an epitope vaccine

Results

We designed a powerful multi-epitope peptide vaccine against EBV using in silico analysis. The vaccine is made up of 844 amino acids derived from three different types of proteins (Envelope, Capsid, EBNA) found in two different viral strains. responses. These epitopes have a high immunogenic capacity and are not likely to cause allergies. To enhance the vaccine immunogenicity, we used rOv-ASP-1, a recombinant Onchocerca volvulus activation associated protein-1, as an adjuvant and linked it to the vaccine’s N and C terminus. The physicochemical and immunological properties of the vaccine structure were evaluated. The proposed vaccine was stable, with a stability index of 33.57 and a pI of 10.10, according to bioinformatic predictions. Docking analysis revealed that the vaccine protein binds correctly with immunological receptors.

Conclusion

Our results demonstrated that the multi-epitope vaccine might be potentially immunogenic and induce humoral and cellular immune responses against EBV. This vaccine can interact appropriately with immunological receptors Also, it has a high-quality structure and suitable characteristics such as high stability.

Design and In Silico Validation of a Novel MZF-1-Based Multi-Epitope Vaccine to Combat Metastatic Triple Negative Breast Cancer

Immunotherapy is emerging as a potential therapeutic strategy for triple negative breast cancer (TNBC) owing to the immunogenic landscape of its tumor microenvironment. Interestingly, peptide-based cancer vaccines have garnered a lot of attention as one of the most promising cancer immunotherapy regimens. Thus, the present study intended to design a novel, efficacious peptide-based vaccine against TNBC targeting myeloid zinc finger 1 (MZF1), a transcription factor that has been described as an oncogenic inducer of TNBC metastasis. Initially, the antigenic peptides from MZF1 were identified and evaluated based on their likelihood to induce immunological responses. The promiscuous epitopes were then combined using a suitable adjuvant (50S ribosomal L7/L12 protein) and linkers (AAY, GPGPG, KK, and EAAAK) to reduce junctional immunogenicity. Furthermore, docking and dynamics analyses against TLR-4 and TLR-9 were carried out to understand more about their structural stability and integrity. Finally, the constructed vaccine was subjected to in silico cloning and immune simulation studies. Overall, the findings imply that the designed chimeric vaccine could induce strong humoral and cellular immune responses in the desired organism. In light of these findings, the final multi-epitope vaccine could be used as an effective prophylactic treatment for TNBC and may pave the way for future research.

Recent trends in next generation immunoinformatics harnessed for universal coronavirus vaccine design

The ongoing pandemic of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has globally devastated public health, the economies of many countries and quality of life universally. The recent emergence of immune-escaped variants and scenario of vaccinated individuals being infected has raised the global concerns about the effectiveness of the current available vaccines in transmission control and disease prevention. Given the high rate mutation of SARS-CoV-2, an efficacious vaccine targeting against multiple variants that contains virus-specific epitopes is desperately needed. An immunoinformatics approach is gaining traction in vaccine design and development due to the significant reduction in time and cost of immunogenicity studies and increasing reliability of the generated results. It can underpin the development of novel therapeutic methods and accelerate the design and production of peptide vaccines for infectious diseases. Structural proteins, particularly spike protein (S), along with other proteins have been studied intensively as promising coronavirus vaccine targets. Numbers of promising online immunological databases, tools and web servers have widely been employed for the design and development of next generation COVID-19 vaccines. This review highlights the role of immunoinformatics in identifying immunogenic peptides as potential vaccine targets, involving databases, and prediction and characterization of epitopes which can be harnessed for designing future coronavirus vaccines.

Design of multi-epitope based vaccine against Mycobacterium tuberculosis: a subtractive proteomics and reverse vaccinology based immunoinformatics approach

Tuberculosis is an airborne transmissible disease caused by Mycobacterium tuberculosis that infects millions of lives worldwide. There is still no single comprehensive therapy or preventative available for the lethal illness. Currently, the available vaccine, BCG is ineffectual in preventing the prophylactic adult pulmonary TB and reactivation of latent tuberculosis. Therefore, this investigation was intended to design a new multi-epitope vaccine that can address the existing problems. The subtractive proteomics approach was implemented to prioritize essential, virulence, druggable, and antigenic proteins as suitable vaccine candidates. Furthermore, a reverse vaccinology-based immunoinformatics technique was employed to identify potential B-cell, helper T lymphocytes (HTL), and cytotoxic T lymphocytes (CTL) epitopes from the target proteins. Immune-stimulating adjuvant, linkers, and PADRE (Pan HLA-DR epitopes) amino acid sequences along with the selected epitopes were used to construct a chimeric multi-epitope vaccine. The molecular docking and normal mode analysis (NMA) were carried out to evaluate the binding mode of the designed vaccine with different immunogenic receptors (MHC-I, MHC-II, and Tlr4). In addition, the MD simulation, followed by essential dynamics study and MMPBSA analysis, was carried out to understand the dynamics and stability of the complexes. In-silico cloning was accomplished using E.coli as an expression system to express the designed vaccine successfully. Finally, the immune simulation study has foreseen that our designed vaccine could induce a significant immune response by elevation of different immunoglobulins in the host. However, there is an imperative need for the experimental validation of the designed vaccine in animal models to confer effectiveness and safety.HIGHLIGHTSMulti-epitope based vaccine was designed against Mycobacterium tuberculosis using subtractive proteomics and Immunoinformatics approach.The vaccine was found to be antigenic, non-allergenic, immunogenic, and stable based on in-silico prediction.Population coverage analysis of the proposed vaccine predicts an effective response in the world population.The molecular docking, MD simulation, and MM-PBSA study confirm the stable interaction of the vaccine with immunogenic receptors.In silico cloning and immune simulation of the vaccine demonstrated its successful expression in E.coli and induction of immune response in the host. Communicated by Ramaswamy H. Sarma.

Exploring staphylococcal superantigens to design a potential multi-epitope vaccine against Staphylococcus aureus: an in-silico reverse vaccinology approach

Staphylococcus aureus is a horrifying bacteria capable of causing millions of deaths yearly across the globe. A major contribution to the success of S. aureus as an ESKAPE pathogen is the abundance of virulence factors that can manipulate the innate and adaptive immune system of the individual. Currently, no vaccine is available to treat S. aureus-mediated infections. In this study, we present in-silico approaches to design a stable, safe and immunogenic vaccine that could help to control the infections associated with the bacteria. Three vital pathogenic secreted toxins of S. aureus, such as staphylococcal enterotoxin A (SEA), staphylococcal enterotoxin B (SEB), Toxic-shock syndrome toxin (TSST-1), were selected using the reverse vaccinology approach to design the multi-epitope vaccine (MEV). Linear B-lymphocyte, cytotoxic T-lymphocyte (CTL) and helper T-lymphocyte (HTL) epitopes were predicted from these selected proteins. For designing the multi-epitope vaccine (MEV), B-cell epitopes were joined with the KK linker, CTL epitopes were joined with the AAY linker, and HTL epitopes were joined with the GPGPG linker. Finally, to increase the immune response to the vaccine, a human β-defensin-3 (hBD-3) adjuvant was added to the N-terminus of the MEV construct. The final MEV was found to be antigenic and non-allergen in nature. In-silico immune simulation and cloning analysis predicted the immune-stimulating potential of the designed MEV construct along with the cloning feasibility in the pET28a(+) vector with the E. coli expression system. This immunoinformatics study provides a platform for designing a suitable, safe and effective vaccine against S. aureus.Communicated by Ramaswamy H. Sarma.

Structural evolution of Delta lineage of SARS-CoV-2

One of the main obstacles in prevention and treatment of COVID-19 is the rapid evolution of the SARS-CoV-2 Spike protein. Given that Spike is the main target of common treatments of COVID-19, mutations occurring at this virulent factor can affect the effectiveness of treatments. The B.1.617.2 lineage of SARS-CoV-2, being characterized by many Spike mutations inside and outside of its receptor-binding domain (RBD), shows high infectivity and relative resistance to existing cures. Here, utilizing a wide range of computational biology approaches, such as immunoinformatics, molecular dynamics (MD), analysis of intrinsically disordered regions (IDRs), protein-protein interaction analyses, residue scanning, and free energy calculations, we examine the structural and biological attributes of the B.1.617.2 Spike protein. Furthermore, the antibody design protocol of Rosetta was implemented for evaluation the stability and affinity improvement of the Bamlanivimab (LY-CoV55) antibody, which is not capable of interactions with the B.1.617.2 Spike. We observed that the detected mutations in the Spike of the B1.617.2 variant of concern can cause extensive structural changes compatible with the described variation in immunogenicity, secondary and tertiary structure, oligomerization potency, Furin cleavability, and drug targetability. Compared to the Spike of Wuhan lineage, the B.1.617.2 Spike is more stable and binds to the Angiotensin-converting enzyme 2 (ACE2) with higher affinity.

In silico design of a promiscuous chimeric multi-epitope vaccine against Mycobacterium tuberculosis

Tuberculosis (TB) is a global health threat, killing approximately 1.5 million people each year. The eradication of Mycobacterium tuberculosis, the main causative agent of TB, is increasingly challenging due to the emergence of extensive drug-resistant strains. Vaccination is considered an effective way to protect the host from pathogens, but the only clinically approved TB vaccine, Bacillus Calmette-Guérin (BCG), has limited protection in adults. Multi-epitope vaccines have been found to enhance immunity to diseases by selectively combining epitopes from several candidate proteins. This study aimed to design a multi-epitope vaccine against TB using an immuno-informatics approach. Through functional enrichment, we identified eight proteins secreted by M. tuberculosis that are either required for pathogenesis, secreted into extracellular space, or both. We then analyzed the epitopes of these proteins and selected 16 helper T lymphocyte epitopes with interferon-γ inducing activity, 15 cytotoxic T lymphocyte epitopes, and 10 linear B-cell epitopes, and conjugated them with adjuvant and Pan HLA DR-binding epitope (PADRE) using appropriate linkers. Moreover, we predicted the tertiary structure of this vaccine, its potential interaction with Toll-Like Receptor-4 (TLR4), and the immune response it might elicit. The results showed that this vaccine had a strong affinity for TLR4, which could significantly stimulate CD4⁺ and CD8⁺ cells to secrete immune factors and B lymphocytes to secrete immunoglobulins, so as to obtain good humoral and cellular immunity. Overall, this multi-epitope protein was predicted to be stable, safe, highly antigenic, and highly immunogenic, which has the potential to serve as a global vaccine against TB.

Immunoinformatic-Based Multi-Epitope Vaccine Design for Co-Infection of Mycobacterium tuberculosis and SARS-CoV-2

(1) Background: Many co-infections of Mycobacterium tuberculosis (MTB) and severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) have emerged since the occurrence of the SARS-CoV-2 pandemic. This study aims to design an effective preventive multi-epitope vaccine against the co-infection of MTB and SARS-CoV-2. (2) Methods: The three selected proteins (spike protein, diacylglycerol acyltransferase, and low molecular weight T-cell antigen TB8.4) were predicted using bioinformatics, and 16 epitopes with the highest ranks (10 helper T lymphocyte epitopes, 2 CD8⁺ T lymphocytes epitopes, and 4 B-cell epitopes) were selected and assembled into the candidate vaccine referred to as S7D5L4. The toxicity, sensitization, stability, solubility, antigenicity, and immunogenicity of the S7D5L4 vaccine were evaluated using bioinformatics tools. Subsequently, toll-like receptor 4 docking simulation and discontinuous B-cell epitope prediction were performed. Immune simulation and codon optimization were carried out using immunoinformatics and molecular biology tools. (3) Results: The S7D5L4 vaccine showed good physical properties, such as solubility, stability, non-sensitization, and non-toxicity. This vaccine had excellent antigenicity and immunogenicity and could successfully simulate immune responses in silico. Furthermore, the normal mode analysis of the S7D5L4 vaccine and toll-like receptor 4 docking simulation demonstrated that the vaccine had docking potential and a stable reaction. (4) Conclusions: The S7D5L4 vaccine designed to fight against the co-infection of MTB and SARS-CoV-2 may be safe and effective. The protective efficacy of this promising vaccine should be further verified using in vitro and in vivo experiments.

Design of a multi-epitope-based vaccine consisted of immunodominant epitopes of structural proteins of SARS-CoV-2 using immunoinformatics approach

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has shown rapid global spread and has resulted in a significant death toll worldwide. In this study, we aimed to design a multi-epitope vaccine against SARS-CoV-2 based on structural proteins S, M, N, and E. We identified B- and T-cell epitopes and then the antigenicity, toxicity, allergenicity, and similarity of predicted epitopes were analyzed. T-cell epitopes were docked with corresponding HLA alleles. Consequently, the selected T- and B-cell epitopes were included in the final construct. All selected epitopes were connected with different linkers and flagellin and pan-HLA DR binding epitopes (PADRE) as an adjuvant were used in the vaccine construct. Furthermore, molecular docking was used to evaluate the complex between the final vaccine construct and two alleles, HLA-A*02:01 and HLA-DRB1*01:01. Finally, codons were optimized for in silico cloning into pET28a(+) vector using SnapGene. The final vaccine construct comprised 11 CTL, HTL, and B-cell epitopes corresponding to 394 amino acid residues. In silico evaluation showed that the designed vaccine might potentially promote an immune response. Further in vivo preclinical and clinical testing is required to determine the safety and efficacy of the designed vaccine.

Design of a potential Sema4A-based multi-epitope vaccine to combat triple-negative breast cancer: an immunoinformatic approach

Immunotherapy is revamping the therapeutic strategies for TNBC owing to its higher mutational burden and tumour-associated antigens. One of the most intriguing developments in cancer immunotherapy is the focus on peptide-based cancer vaccines. Thus, the current work aims to develop an efficient peptide-based vaccine against TNBC that targets Sema4A, which has recently been identified as a major regulator of TNBC progression. Initially, the antigenic peptides derived from Sema4A were determined and evaluated based on their capability to provoke immunological responses. The assessed epitopes were then linked with a suitable adjuvant (RpfB and RpfE) and appropriate linkers (AAY, GPGPG, KK and EAAAK) to preclude junctional immunogenicity. Eventually, docking and dynamics simulations are performed against TLR-2, TLR-4, TLR-7 and TLR-9 to assess the interaction between the vaccine construct and TLR receptors, as the TLR signalling pathway is critical in the host immune response. The developed vaccine was then exposed to in silico cloning and immune simulation analysis. The findings suggest that the designed vaccine could potentially evoke significant humoral and cellular immune responses in the intended organism. Considering these outcomes, the final multi-epitope vaccine could be employed to serve as an effective choice for TNBC management and may open new avenues for further studies.

An In silico study of derivative of Newcastle disease virus epitopes based vaccine against Hemagglutunin neuraminidase protein

The causative agent of Newcastle disease (ND) is Newcastle disease virus. It belongs to avian species of Orthoavulavirus, Avulavirinae subfamily and if left untreated it may cause epidemic in poultry. Many vaccines have been made against Newcastle disease based on inactivated and attenuated viruses but become useless due to the genetic changes in the virus. We have recently reported epitope based vaccine by using immunoinformatics approaches. The vaccine was previously constructed against Hemagglutunin neuraminidase protein of Newcastle disease virus. Here we extended our work to develop several chimera of the proposed vaccine to design a new multi-epitope vaccine by shuffling the cytotoxic T lymphocytes (CTL) segments of the vaccine. Total 5040 constructs have been analyzed by shuffling 7 CTL epitopes. Highest antigenic multi-epitope construct was selected for the further study. Our new multi-epitope vaccine (MEV) construct contains 259 amino acids and is immunogenic, more antigenic and non-allergen. The refinement of the structure of MEV construct was performed. Molecular docking analyses showed its maximum binding with avian Toll-like 4 receptor. Subsequently, immune simulations showed its predicted ability to induce the host primary and secondary responses. Study suggests that our new multi-epitope vaccine chimera is more effective and stable protein against Newcastle disease virus strains in Pakistan. However, further studies are required to validate the vaccine through In vitro and In vivo studies.

Proteomic Approach for Comparative Analysis of the Spike Protein of SARS-CoV-2 Omicron (B.1.1.529) Variant and Other Pango Lineages

The novel SARS-CoV-2 variant, Omicron (B.1.1.529), is being testified, and the WHO has characterized Omicron as a variant of concern due to its higher transmissibility and very contagious behavior, immunization breakthrough cases. Here, the comparative proteomic study has been conducted on spike-protein, hACE2 of five lineages (α, β, δ, γ and Omicron. The docking was performed on spike protein- hACE-2 protein using HADDOCK, and PRODIGY was used to analyze the binding energy affinity using a reduced Haddock score. Followed by superimposition in different variant-based protein structures and calculated the esteem root mean square deviation (RMSD). This study reveals that Omicron was seen generating a monophyletic clade. Further, as α variant is the principal advanced strain after Wuhan SARS-CoV-2, and that is the reason it was showing the least likeness rate with the Omicron and connoting Omicron has developed of late with the extreme number of mutations. α variant has shown the highest binding affinity with hACE2, followed by β strain, and followed with γ. Omicron showed a penultimate binding relationship, while the δ variant was seen as having the least binding affinity. This proteomic basis in silico analysis of variable spike proteins of variants will impart light on the development of vaccines and the identification of mutations occurring in the upcoming variants.

In-silico design of an immunoinformatics based multi-epitope vaccine against Leishmania donovani

BACKGROUND

Visceral Leishmaniasis (VL) is a fatal vector-borne parasitic disorder occurring mainly in tropical and subtropical regions. VL falls under the category of neglected tropical diseases with growing drug resistance and lacking a licensed vaccine. Conventional vaccine synthesis techniques are often very laborious and challenging. With the advancement of bioinformatics and its application in immunology, it is now more convenient to design multi-epitope vaccines comprising predicted immuno-dominant epitopes of multiple antigenic proteins. We have chosen four antigenic proteins of Leishmania donovani and identified their T-cell and B-cell epitopes, utilizing those for in-silico chimeric vaccine designing. The various physicochemical characteristics of the vaccine have been explored and the tertiary structure of the chimeric construct is predicted to perform docking studies and molecular dynamics simulations.

RESULTS

The vaccine construct is generated by joining the epitopes with specific linkers. The predicted tertiary structure of the vaccine has been found to be valid and docking studies reveal the construct shows a high affinity towards the TLR-4 receptor. Population coverage analysis shows the vaccine can be effective on the majority of the world population. In-silico immune simulation studies confirms the vaccine to raise a pro-inflammatory response with the proliferation of activated T and B cells. In-silico codon optimization and cloning of the vaccine nucleic acid sequence have also been achieved in the pET28a vector.

CONCLUSION

The above bioinformatics data support that the construct may act as a potential vaccine. Further wet lab synthesis of the vaccine and in vivo works has to be undertaken in animal model to confirm vaccine potency.

Artificial Intelligence-Based Data-Driven Strategy to Accelerate Research, Development, and Clinical Trials of COVID Vaccine

The global COVID-19 (coronavirus disease 2019) pandemic, which was caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has resulted in a significant loss of human life around the world. The SARS-CoV-2 has caused significant problems to medical systems and healthcare facilities due to its unexpected global expansion. Despite all of the efforts, developing effective treatments, diagnostic techniques, and vaccinations for this unique virus is a top priority and takes a long time. However, the foremost step in vaccine development is to identify possible antigens for a vaccine. The traditional method was time taking, but after the breakthrough technology of reverse vaccinology (RV) was introduced in 2000, it drastically lowers the time needed to detect antigens ranging from 5-15 years to 1-2 years. The different RV tools work based on machine learning (ML) and artificial intelligence (AI). Models based on AI and ML have shown promising solutions in accelerating the discovery and optimization of new antivirals or effective vaccine candidates. In the present scenario, AI has been extensively used for drug and vaccine research against SARS-COV-2 therapy discovery. This is more useful for the identification of potential existing drugs with inhibitory human coronavirus by using different datasets. The AI tools and computational approaches have led to speedy research and the development of a vaccine to fight against the coronavirus. Therefore, this paper suggests the role of artificial intelligence in the field of clinical trials of vaccines and clinical practices using different tools.

Design of a Recombinant Multivalent Epitope Vaccine Based on SARS-CoV-2 and Its Variants in Immunoinformatics Approaches

The development of an effective multivalent vaccine against SARS-CoV-2 variants is an important means to improve the global public health situation caused by COVID-19. In this study, we identified the antigen epitopes of the main global epidemic SARS-CoV-2 and mutated virus strains using immunoinformatics approach, and screened out 8 cytotoxic T lymphocyte epitopes (CTLEs), 17 helper T lymphocyte epitopes (HTLEs), 9 linear B-cell epitopes (LBEs) and 4 conformational B-cell epitopes (CBEs). The global population coverage of CTLEs and HTLEs was 93.16% and 99.9% respectively. These epitopes were spliced together by corresponding linkers and recombined into multivalent vaccine. In silico tests, the vaccine protein was a non-allergen and the docking with TLR-3 molecule showed a strong interaction. The results of immune simulation showed that the vaccine may be helpful to initiate both cellular and humoral immunity against all VOC. The optimistic immunogenicity of the vaccine was confirmed in vivo and in vitro finally. Therefore, our vaccine may have potential protection against SARS-CoV-2 and its variants.

Development of multivalent vaccine targeting M segment of Crimean Congo Hemorrhagic Fever Virus (CCHFV) using immunoinformatic approaches

Crimean-Congo Hemorrhagic Fever (CCHF) is a tick-borne viral infection with no licensed vaccine or therapeutics available for its treatment. In the present study we have developed the first multi-epitope subunit vaccine effective against all the seven genotypes of CCHF virus (CCHFV). The vaccine contains five B-cell, two MHC-II (HTL), and three MHC-I (CTL) epitopes screened from two structural glycoproteins (Gc and Gn in M segment) of CCHFV with an N-terminus human β-defensin as an adjuvant, as well as an N-terminus EAAAK sequence. The epitopes were rigorously investigated for their antigenicity, allergenicity, IFN gamma induction, anti-inflammatory responses, stability, and toxicity. The three-dimensional structure of the vaccine was predicted and docked with TLR-3, TLR-8, and TLR-9 receptors to find the strength of the binding complexes via molecular dynamics simulation. After codon adaptation, the subunit vaccine construct was developed in a pDual-GC plasmid and has population coverage of 98.47% of the world's population (HLA-I & II combined). The immune simulation studies were carried out on the C-ImmSim in-silico interface showing a marked increase in the production of cellular and humoral response (B-cell and T-cell) as well as TGFβ, IL-2, IL-10, and IL-12 indicating that the proposed vaccine would be able to sufficiently provoke both humoral and cell-mediated immune responses. Thus, making it a new and promising vaccine candidate against CCHFV.

Immunomodulatory and Allergenic Properties of Antimicrobial Peptides

With the growing problem of the emergence of antibiotic-resistant bacteria, the search for alternative ways to combat bacterial infections is extremely urgent. While analyzing the effect of antimicrobial peptides (AMPs) on immunocompetent cells, their effect on all parts of the immune system, and on humoral and cellular immunity, is revealed. AMPs have direct effects on neutrophils, monocytes, dendritic cells, T-lymphocytes, and mast cells, participating in innate immunity. They act on B-lymphocytes indirectly, enhancing the induction of antigen-specific immunity, which ultimately leads to the activation of adaptive immunity. The adjuvant activity of AMPs in relation to bacterial and viral antigens was the reason for their inclusion in vaccines and made it possible to formulate the concept of a “defensin vaccine” as an innovative basis for constructing vaccines. The immunomodulatory function of AMPs involves their influence on cells in the nearest microenvironment, recruitment and activation of other cells, supporting the response to pathogenic microorganisms and completing the inflammatory process, thus exhibiting a systemic effect. For the successful use of AMPs in medical practice, it is necessary to study their immunomodulatory activity in detail, taking into account their pleiotropy. The degree of maturity of the immune system and microenvironment can contribute to the prevention of complications and increase the effectiveness of therapy, since AMPs can suppress inflammation in some circumstances, but aggravate the response and damage of organism in others. It should also be taken into account that the real functions of one or another AMP depend on the types of total regulatory effects on the target cell, and not only on properties of an individual peptide. A wide spectrum of biological activity, including direct effects on pathogens, inactivation of bacterial toxins and influence on immunocompetent cells, has attracted the attention of researchers, however, the cytostatic activity of AMPs against normal cells, as well as their allergenic properties and low stability to host proteases, are serious limitations for the medical use of AMPs. In this connection, the tasks of searching for compounds that selectively affect the target and development of an appropriate method of application become critically important. The scope of this review is to summarize the current concepts and newest advances in research of the immunomodulatory activity of natural and synthetic AMPs, and to examine the prospects and limitations of their medical use.

In silico design of recombinant multi-epitope vaccine against influenza A virus

Background

Influenza A virus is one of the leading causes of annual mortality. The emerging of novel escape variants of the influenza A virus is still a considerable challenge in the annual process of vaccine production. The evolution of vaccines ranks among the most critical successes in medicine and has eradicated numerous infectious diseases. Recently, multi-epitope vaccines, which are based on the selection of epitopes, have been increasingly investigated.

Results

This study utilized an immunoinformatic approach to design a recombinant multi-epitope vaccine based on a highly conserved epitope of hemagglutinin, neuraminidase, and membrane matrix proteins with fewer changes or mutate over time. The potential B cells, cytotoxic T lymphocytes (CTL), and CD4 T cell epitopes were identified. The recombinant multi-epitope vaccine was designed using specific linkers and a proper adjuvant. Moreover, some bioinformatics online servers and datasets were used to evaluate the immunogenicity and chemical properties of selected epitopes. In addition, Universal Immune System Simulator (UISS) in silico trial computational framework was run after influenza exposure and recombinant multi-epitope vaccine administration, showing a good immune response in terms of immunoglobulins of class G (IgG), T Helper 1 cells (TH1), epithelial cells (EP) and interferon gamma (IFN-g) levels. Furthermore, after a reverse translation (i.e., convertion of amino acid sequence to nucleotide one) and codon optimization phase, the optimized sequence was placed between the two EcoRV/MscI restriction sites in the PET32a⁺ vector.

Conclusions

The proposed “Recombinant multi-epitope vaccine” was predicted with unique and acceptable immunological properties. This recombinant multi-epitope vaccine can be successfully expressed in the prokaryotic system and accepted for immunogenicity studies against the influenza virus at the in silico level. The multi-epitope vaccine was then tested with the Universal Immune System Simulator (UISS) in silico trial platform. It revealed slight immune protection against the influenza virus, shedding the light that a multistep bioinformatics approach including molecular and cellular level is mandatory to avoid inappropriate vaccine efficacy predictions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04581-6.

Long-Term SARS-CoV-2 Specific Immunity Is Affected by the Severity of Initial COVID-19 and Patient Age

The coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently the greatest medical challenge. Although crucial to the future management of the pandemic, the factors affecting the persistence of long-term SARS-CoV-2 immunity are not well understood. Therefore, we determined the extent of important correlates of SARS-CoV-2 specific protection in 200 unvaccinated convalescents after COVID-19. To investigate the effective memory response against the virus, SARS-CoV-2 specific T cell and humoral immunity (including virus-neutralizing antibodies) was determined over a period of one to eleven months. SARS-CoV-2 specific immune responses were present in 90% of individual patients. Notably, immunosuppressed patients did not have long-term SARS-CoV-2 specific T cell immunity. In our cohort, the severity of the initial illness influenced SARS-CoV-2 specific T cell immune responses and patients’ humoral immune responses to Spike (S) protein over the long-term, whereas the patients’ age influenced Membrane (M) protein-specific T cell responses. Thus, our study not only demonstrated the long-term persistence of SARS-CoV-2 specific immunity, it also determined COVID-19 severity and patient age as significant factors affecting long-term immunity.

Computational Design of a Multi-epitope Vaccine Against Clostridium chauvoei: An Immunoinformatics Approach

Blackleg is an infectious disease of animals that is commonly caused by Clostridium chauvoei and characterized by localized muscle necrosis. In this study, proteome-mining and immunoinformatics approaches were applied to identify novel antigenic proteins and to construct a multi-epitope vaccine against C. chauvoei. All proteins of C. chauvoei strains were retrieved from the NCBI Microbial Genome Database containing both genomic and proteomic data of prokaryotes. The proteins were analyzed to exclude non-redundant sequences and to determine antigenic, virulent, and non-allergenic vaccine candidates through several online tools, resulting in seven protein candidates. Cytotoxic T and B cell epitopes of these proteins were evaluated through the tools present in the immune epitope database and the prioritized antigenic epitopes were then conjugated via appropriate linkers to construct the vaccine candidate. After the evaluation of physicochemical properties of the construct, the tertiary structure was modeled and refined through trRosetta and GalaxyRefine, respectively. The quality of the 3D structure was validated by ERRAT score, z-score, and Ramachandran plot and the construct was then docked with bovine Toll-like receptor 4 (TLR 4) using ClusPro. The docked complex was subjected to Molecular Mechanics/Generalized Born Surface Area in the HawkDock server and normal mode analysis in the iMODS simulation suite to assess the binding energy and stability of the complex, respectively. Overall, the vaccine construct was found stable and energetically feasible for bovine TLR 4 binding. Therefore, it can be used as a multi-epitope vaccine construct in clostridial vaccines to control the blackleg disease.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10989-021-10279-9.

Antibody Response to SARS-CoV-2 Membrane Protein in Patients of the Acute and Convalescent Phase of COVID-19

Understanding the course of the antibody response directed to individual epitopes of SARS-CoV-2 proteins is crucial for serological assays and establishment of vaccines. Twenty-one synthetic peptides were synthesized that have ten amino acids overlap and cover the complete membrane (M) protein. Plasma samples from 32 patients having acute disease and 30 patients from the convalescent phase were studied. Only peptide M01 (aa 1–20) and to a lesser extent peptide M21 (aa 201–222) showed specific reactivity as compared to historical control plasma samples. Peptide M01 was recognized by IgM- (71.9%) and IgG-specific antibodies (43.8%) during the acute phase as early as day 8 PIO. In a longitudinal analysis, a higher reactivity was observed for the IgM response directed to peptide M01 following day 20 PIO as compared to earlier time points of the acute phase. In the convalescent phase, antibody reactivity to the two M-specific peptides was significantly lower (<30% seropositivity). A fusion protein encoding major parts of RBD also showed higher rates of recognition during acute (50.0%) and lower rates in the convalescent phase (23.3%). Taken together, our results suggest that during the acute phase of COVID-19 antibodies are raised to two linear epitopes of the SARS-CoV-2 M protein, located at the very N- and C-termini, showing almost similar levels of reactivity as immunodominant linear epitopes derived from the spike and nucleocapsid protein. Anti-M is also present in the convalescent phase of COVID-19 patients, however at lower levels, with the N-terminus of the M protein as a preferred target.

An immunoinformatics approach for the design of a multi-epitope vaccine targeting super antigen TSST-1 of Staphylococcus aureus

Background

TSST-1 is a secretory and pyrogenic superantigen that is being responsible for staphylococcal mediated food poisoning and associated clinical manifestations. It is one of the main targets for the construction of vaccine candidates against Staphylococcus aureus. Most of the vaccines have met failure due to adverse reactions and toxicity reported during late clinical studies. To overcome this, an immunoinformatics approach is being used in the present study for the design of a multi-epitope vaccine to circumvent the problems related to toxicity and allergenicity.

Results

In this study, a multi-epitope vaccine against Staphylococcus aureus targeting TSST-1 was designed through an immunoinformatics approach. B cell and T cell epitopes were predicted in silico and mapped with linkers to avoid junctional immunogenicity and to ensure the efficient presentation of exposed epitopes through HLA. β-defensin and PADRE were adjusted at the N-terminal end of the final vaccine as adjuvants. Physiochemical parameters, antigenicity, and allergenicity of the vaccine construct were determined with the help of online servers. The three-dimensional structure of the vaccine protein was predicted and validated with various tools. The affinity of the vaccine with TLR-3 was studied through molecular docking studies and the interactions of two proteins were visualized using LigPlot⁺. The vaccine was successfully cloned in silico into pET-28a (+) for efficient expression in E. coli K12 system. Population coverage analysis had shown that the vaccine construct can cover 83.15% of the global population. Immune simulation studies showed an increase in the antibody levels, IL-2, IFN-γ, TGF-β, B cell, and T cell populations and induced primary, secondary, and tertiary immune responses.

Conclusion

Multi-epitope vaccine designed through a computational approach is a non-allergic and non-toxic antigen. Preliminary in silico reports have shown that this vaccine could elicit both B cell and T cell responses in the host as desired.

Current and prospective computational approaches and challenges for developing COVID-19 vaccines

SARS-CoV-2, which causes COVID-19, was first identified in humans in late 2019 and is a coronavirus which is zoonotic in origin. As it spread around the world there has been an unprecedented effort in developing effective vaccines. Computational methods can be used to speed up the long and costly process of vaccine development. Antigen selection, epitope prediction, and toxicity and allergenicity prediction are areas in which computational tools have already been applied as part of reverse vaccinology for SARS-CoV-2 vaccine development. However, there is potential for computational methods to assist further. We review approaches which have been used and highlight additional bioinformatic approaches and PK modelling as in silico methods which may be useful for SARS-CoV-2 vaccine design but remain currently unexplored. As more novel viruses with pandemic potential are expected to arise in future, these techniques are not limited to application to SARS-CoV-2 but also useful to rapidly respond to novel emerging viruses.

Immunoinformatics and molecular modeling approach to design universal multi-epitope vaccine for SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmittable and pathogenic human coronavirus that caused a pandemic situation of acute respiratory syndrome, called COVID-19, which has posed a significant threat to global health security. The aim of the present study is to computationally design an effective peptide-based multi-epitope vaccine (MEV) against SARS-CoV-2. The overall model quality of the vaccine candidate, immunogenicity, allergenicity, and physiochemical analysis have been conducted and validated. Molecular dynamics studies confirmed the stability of the candidate vaccine. The docked complexes during the simulation revealed a strong and stable binding interactions of MEV with human and mice toll-like receptors (TLR), TLR3 and TLR4. Finally, candidate vaccine codons have been optimized for their in silico cloning in E. coli expression system, to confirm increased expression. The proposed MEV can be a potential candidate against SARS-CoV-2, but experimental validation is needed to ensure its safety and immunogenicity status.