Development of multi-epitope driven subunit vaccine against Fasciola gigantica using immunoinformatics approach

Subtractive proteomics-based vaccine targets annotation and reverse vaccinology approaches to identify multiepitope vaccine against Plesiomonas shigelloides

Plesiomonas shigelloides, an aquatic bacterium belonging to the Enterobacteriaceae family, is a frequent cause of gastroenteritis with diarrhea and gastrointestinal severe disease. Despite decades of research, discovering a licensed and globally accessible vaccine is still years away. Developing a putative vaccine that can combat the Plesiomonas shigelloides infection by boosting population immunity against P. shigelloides is direly needed. In the framework of the current study, the entire proteome of P. shigelloides was explored using subtractive genomics integrated with the immunoinformatics approach for designing an effective vaccine construct against P. shigelloides. The overall stability of the vaccine construct was evaluated using molecular docking, which demonstrated that MEV showed higher binding affinities with toll-like receptors (TLR4: 51.5 ± 10.3, TLR2: 60.5 ± 9.2) and MHC receptors(MHCI: 79.7 ± 11.2 kcal/mol, MHCII: 70.4 ± 23.7). Further, the therapeutic efficacy of the vaccine construct for generating an efficient immune response was evaluated by computational immunological simulation. Finally, computer-based cloning and improvement in codon composition without altering amino acid sequence led to the development of a proposed vaccine. In a nutshell, the findings of this study add to the existing knowledge about the pathogenesis of this infection. The schemed MEV can be a possible prophylactic agent for individuals infected with P. shigelloides. Nevertheless, further authentication is required to guarantee its safeness and immunogenic potential.

In silico design of a novel multi-epitope vaccine against HCV infection through immunoinformatics approaches

Infection with the hepatitis C virus (HCV) is one of the causes of liver cancer, which is the world's sixth most prevalent and third most lethal cancer. The current treatments do not prevent reinfection; because they are expensive, their usage is limited to developed nations. Therefore, a prophylactic vaccine is essential to control this virus. Hence, in this study, an immunoinformatics method was applied to design a multi-epitope vaccine against HCV. The best B- and T-cell epitopes from conserved regions of the E2 protein of seven HCV genotypes were joined with the appropriate linkers to design a multi-epitope vaccine. In addition, cholera enterotoxin subunit B (CtxB) was included as an adjuvant in the vaccine construct. This study is the first to present this epitopes-adjuvant combination. The vaccine had acceptable physicochemical characteristics. The vaccine's 3D structure was predicted and validated. The vaccine's binding stability with Toll-like receptor 2 (TLR2) and TLR4 was confirmed using molecular docking and molecular dynamics (MD) simulation. The immune simulation revealed the vaccine's efficacy by increasing the population of B and T cells in response to vaccination. In silico expression in Escherichia coli (E. coli) was also successful.

A Multi-epitope Subunit Vaccine Identification and Development Against Scrub Typhus (Orientia tsutsugamushi) Using Immunoinformatics Approaches

Background The pathogen Orientia tsutsugamushi, which causes scrub typhus, is rapidly spreading throughout the tropics. As a measure to improve public health, the development of a vaccine for human use is essential. Scrub typhus is listed as one of the underdiagnosed and underreported febrile infections. This vector-borne zoonotic infection appears as eschar on the patient's skin. Methods Immunoinformatics was employed to predict the multi-epitope subunit vaccine that will activate both B and T cells. The final vaccine includes lipoprotein LprA as an adjuvant at the N-terminus along with B-cell, helper T lymphocyte (HTL), and cytotoxic T lymphocyte (CTL)-binding epitopes to boost immunogenicity. Assessing the vaccine's physiochemistry demonstrates that it is both antigenic and non-allergic. The vaccine structure was developed, enhanced, confirmed, and disulfide-engineered to provide the best possible model. Using molecular docking, the interaction of the produced vaccine with toll-like receptor 2 (TLR2) was analyzed, and the vaccine-receptor complex was stabilized by molecular dynamics (MD) simulation. According to in silico cloning, Escherichia coli can efficiently produce the recommended vaccine. Additionally, the efficacy of the in silico-developed vaccine must be evaluated in an in vitro and in vivo experiment. Results The developed vaccine successfully stimulates cellular and humoral immune responses. The vaccine, which has three B-cell epitopes, three HCL epitopes, and nine CTL epitopes, can bind firmly to immunological receptors. Dynamic investigations of the vaccine-receptor complex show a strong interaction and stable conformation. Conclusion In this study, the vaccine candidate demonstrated strong antigenicity, stability, and solubility while also being non-allergenic to host cells. The vaccine candidate's stability with the TLR2 immune receptor is established by binding studies, and in silico cloning verifies efficient and stable expression in the bacterial system.

In silico discovery of diagnostic/vaccine candidate antigenic epitopes and a multi-epitope peptide vaccine (NaeVac) design for the brain-eating amoeba Naegleria fowleri causing human meningitis

Naegleria fowleri, the brain-eating amoeba, is a free-living amoeboflagellate with three different life cycles (trophozoite, flagellated, and cyst) that lives in a variety of habitats around the world including warm freshwater and soil. It causes a disease called naegleriasis leading meningitis and primary amoebic meningoencephalitis (PAM) in humans. N. fowleri is transmitted through contaminated water sources such as insufficiently chlorinated swimming pool water or contaminated tap water, and swimmers are at risk. N. fowleri is found all over the world, and most infections were reported in both developed and developing countries with high mortality rates and serious clinical findings. Until now, there is no FDA approved vaccine and early diagnosis is urgent against this pathogen. In this study, by analyzing the N. fowleri vaccine candidate proteins (Mp2CL5, Nfa1, Nf314, proNP-A and proNP-B), it was aimed to discover diagnostic/vaccine candidate epitopes and to design a multi-epitope peptide vaccine against this pathogen. After the in silico evaluation, three prominent diagnostic/vaccine candidate epitopes (EAKDSK, LLPHIRILVY, and FYAKLLPHIRILVYS) with the highest antigenicities were discovered and a potentially highly immunogenic/antigenic multi-epitope peptide vaccine (NaeVac) was designed against the brain-eating amoeba N. fowleri causing human meningitis.

Molecular characterization of Anaplasma ovis Msp4 protein in strains isolated from ticks in Turkey: A multi-epitope synthetic vaccine antigen design against Anaplasma ovis using immunoinformatic tools

Tick-borne pathogens increasingly threaten animal and human health as well as cause great economic loss in the livestock industry. Among these pathogens, Anaplasma ovis causing a decrease in meat and milk yield is frequently detected in sheep in many countries including Turkey. This study aimed to reveal potential vaccine candidate epitopes in Msp4 protein using sequence data from Anaplasma ovis isolates and then to design a multi-epitope protein to be used in vaccine formulations against Anaplasma ovis. For this purpose, Msp4 gene was sequenced from Anaplasma ovis isolates (n:6) detected in ticks collected from sheep in Turkey and the sequence data was compared with previous sequences from different countries in order to detect the variations of Msp4 gene/protein. Potential vaccine candidate and diagnostic epitopes were predicted using various immunoinformatics tools. Among the discovered vaccine candidate epitopes, antigenic and conserved were selected, and then a multi-epitope protein was designed. The designed vaccine protein was tested for the assessment of TLR-2, IgG, and IFN-g responses by molecular docking and immune simulation analyses. Among the discovered epitopes, EVASEGSGVM and YQFTPEISLV epitopes with properties of high antigenicity, non-allergenicity, and non-toxicity were proposed to be used for Anaplasma ovis in further serodiagnostic and vaccine studies.

Immunoinformatic exploration of a multi-epitope-based peptide vaccine candidate targeting emerging variants of SARS-CoV-2

Many countries around the world are facing severe challenges due to the recently emerging variants of SARS-CoV-2. Over the last few months, scientists have been developing treatments, drugs, and vaccines to subdue the virus and prevent its transmission. In this context, a peptide-based vaccine construct containing pathogenic proteins of the virus known to elicit an immune response was constructed. An analysis of the spike protein-based epitopes allowed us to design an "epitope-based subunit vaccine" against coronavirus using the approaches of "reverse vaccinology" and "immunoinformatics." Computational experimentation and a systematic, comprehensive protocol were followed with an aim to develop and design a multi-epitope-based peptide (MEBP) vaccine candidate. Our study attempted to predict an MEBP vaccine by introducing mutations of SARS-CoV-2 (Delta, Lambda, Iota, Omicron, and Kappa) in Spike glycoprotein and predicting dual-purpose epitopes (B-cell and T-cell). This was followed by screening the selected epitopes based on antigenicity, allergenicity, and population coverage and constructing them into a vaccine by using linkers and adjuvants. The vaccine construct was analyzed for its physicochemical properties and secondary structure prediction, and a 3D structure was built, refined, and validated. Furthermore, the peptide-protein interaction of the vaccine construct with Toll-like receptor (TLR) molecules was performed. Immune profiling was performed to check the immune response. Codon optimization of the vaccine construct was performed to obtain the GC content before cloning it into the E. coli genome, facilitating its progression it into a vector. Finally, an in-silico simulation of the vaccine-protein complex was performed to comprehend its stability and conformational behavior.

Identification and characterization of codon usage pattern and influencing factors in HFRS-causing hantaviruses

Hemorrhagic fever with renal syndrome (HFRS) is an acute viral zoonosis carried and transmitted by infected rodents through urine, droppings, or saliva. The etiology of HFRS is complex due to the involvement of viral factors and host immune and genetic factors which hinder the development of potential therapeutic solutions for HFRS. Hantaan virus (HTNV), Dobrava-Belgrade virus (DOBV), Seoul virus (SEOV), and Puumala virus (PUUV) are predominantly found in hantaviral species that cause HFRS in patients. Despite ongoing prevention and control efforts, HFRS remains a serious economic burden worldwide. Furthermore, recent studies reported that the hantavirus nucleocapsid protein is a multi-functional protein and plays a major role in the replication cycle of the hantavirus. However, the precise mechanism of the nucleoproteins in viral pathogenesis is not completely understood. In the framework of the current study, various in silico approaches were employed to identify the factors influencing the codon usage pattern of hantaviral nucleoproteins. Based on the relative synonymous codon usage (RSCU) values, a comparative analysis was performed between HFRS-causing hantavirus and their hosts, suggesting that HTNV, DOBV, SEOV, and PUUV, were inclined to evolve their codon usage patterns that were comparable to those of their hosts. The results indicated that most of the overrepresented codons had AU-endings, which revealed that mutational pressure is the major force shaping codon usage patterns. However, the influence of natural selection and geographical factors cannot be ignored on viral codon usage bias. Further analysis also demonstrated that HFRS causing hantaviruses adapted host-specific codon usage patterns to sustain successful replication and transmission chains within hosts. To our knowledge, no study to date reported the factors influencing the codon usage pattern within hantaviral nucleoproteins. Thus, the proposed computational scheme can help in understanding the underlying mechanism of codon usage patterns in HFRS-causing hantaviruses which lend a helping hand in designing effective anti-HFRS treatments in future. This study, although comprehensive, relies on in silico methods and thus necessitates experimental validation for more solid outcomes. Beyond the identified factors influencing viral behavior, there could be other yet undiscovered influences. These potential factors should be targets for further research to improve HFRS therapeutic strategies.

Laterosporulin25: A probiotically produced, novel defensin-like bacteriocin and its immunogenic properties

Although multiple vaccines have been developed against infectious diseases, the rapid emergence of new pathogens develops an urgent need for novel strategies to combat infectious diseases. Antimicrobial peptides (AMPs) are excellent agents to fight against infectious diseases having unique multiple mechanisms of action against various pathogens. Apart from the direct applications, AMPs can also be developed as subunit vaccines or could be used as a highly immunogenic carrier protein with highly antigenic but non-immunogenic antigens. Here in the present study, we have identified a novel defensin-like bacteriocin, laterosporulin25 (LS25) upon genome mining of Brevibacillus laterosporus DSM25, a probiotic bacterial strain. By using immunoinformatic tools, we have studied the immunogenic and physiochemical properties of LS25. LS25 is characterized as defensin-like bacteriocin, having 51 amino acids and a molecular weight of 5862.7 Da. The modeled tertiary structure of LS25 is docked with TLR3 and TLR4-MD2 complex to confirm the facilitation of induced immune response that is further validated using molecular dynamics simulations and In-silico immune stimulations. Overall, detailed immunoinformatics analysis suggested LS25 as a potential candidate to be used as an adjuvant or carrier protein for subunit vaccine development, however, further in-vitro and in-vivo experiments are essential to validate its potential.

Structural immunoinformatics approach for rational design of a multi-epitope vaccine against triple negative breast cancer

TNBC is a highly malignant breast cancer known for its aggressive behavior affecting young female adults. The standard treatment for TNBC includes surgery, chemotherapy, and radiotherapy, which often have significant side effects. Therefore, novel preventive methods are required to combat TNBC effectively. In this study, we utilized immunoinformatics to construct an in-silico vaccine against TNBC using the TRIM25 molecule via the reverse vaccinology method. Four vaccines were designed by generating T and B-cell epitopes linked with four different linkers. The modeled vaccine was docked and the results showed that vaccine-3 exhibited the highest affinity with the immune receptors. The molecular dynamics results revealed that the binding affinity and stability of Vaccine-3 were greater than those of Vaccine 2 complexes. This study has great potential preventive measures for TNBC, and further research is warranted to evaluate its efficacy in preclinical settings. This study presents an innovative preventive strategy for triple-negative breast cancer (TNBC) through immunoinformatics and reverse vaccinology to develop an in-silico vaccine. Leveraging these innovative techniques offers a novel avenue for combating the complex challenges associated with TNBC. This approach demonstrates considerable potential as a significant breakthrough in preventive measures for this particularly aggressive and malignant form of breast cancer.

Immunogenic multi-epitope-based vaccine development to combat cyclosporiasis of immunocompromised patients applying computational biology method

Cyclospora cayetanensis infections, also known as cyclosporiasis, persist to be the prevalent emerging protozoan parasite and an opportunist that causes digestive illness in immunocompromised individuals. In contrast, this causal agent can affect people of all ages, with children and foreigners being the most susceptible populations. For most immunocompetent patients, the disease is self-limiting; in extreme circumstances, this illness can manifest as severe or persistent diarrhea as well as colonize on secondary digestive organs leading to death. According to recent reports, worldwide 3.55% of people are infected by this pathogen, with Asia and Africa being more prevalent. For the treatment, trimethoprim-sulfamethoxazole is the only licensed drug and does not appear to work as well in some patient populations. Therefore, the much more effective strategy to avoid this illness is immunization through the vaccine. This present study uses immunoinformatics for identifying a computational multi-epitope-based peptide vaccine candidate for Cyclospora cayetanensis. Following the review of the literature, a highly efficient, secure, and vaccine complex based on multi-epitopes was designed by utilizing the identified proteins. These selected proteins were then used to predict non-toxic and antigenic HTL-epitopes, B-cell-epitopes, and CTL-epitopes. Ultimately, both a few linkers and an adjuvant were combined to create a vaccine candidate with superior immunological epitopes. Then, to establish the vaccine-TLR complex binding constancy, the TLR receptor and vaccine candidates were placed into the FireDock, PatchDock, and ClusPro servers for molecular docking and iMODS server for molecular-dynamic simulation. Finally, this selected vaccine construct was cloned into Escherichia coli strain-K12; thus, the constructed vaccines against Cyclospora cayetanensiscould improve the host immune response and can be produced experimentally.

Recombinant T-cell epitope conjugation: A new approach for Dermatophagoides hypoallergen design

BACKGROUND

Allergen-specific immunotherapy (AIT) is the only clinical approach that can potentially cure some allergic diseases by inducing immunological tolerance. Dermatophagoides pteronyssinus is considered as the most important source of mite allergens worldwide, with high sensitization rates for the major allergens Der p 1, Der p 2 and Der p 23. The aim of this work is to generate a hypoallergenic hybrid molecule containing T-cell epitopes from these three major allergens.

METHODS

The hybrid protein termed Der p 2231 containing T-cell epitopes was purified by affinity chromatography. The human IgE reactivity was verified by comparing those with the parental allergens. The hybrid was also characterized immunologically through an in vivo mice model.

RESULTS

The hybrid rDer p 2231 stimulated in peripheral blood mononuclear cells (PBMCs) isolated from allergic patients with higher levels of IL- 2, IL-10, IL-15 and IFN-γ, as well as lower levels of IL-4, IL-5, IL-13, TNF-α and GM-CSF. The use of hybrid molecules as a therapeutic model in D. pteronyssinus allergic mice led to the reduction of IgE production and lower eosinophilic peroxidase activity in the airways. We found increased levels of IgG antibodies that blocked the IgE binding to the parental allergens in the serum of allergic patients. Furthermore, the stimulation of splenocytes from mice treated with rDer p 2231 induced higher levels of IL-10 and IFN-γ and decreased the secretion of IL-4 and IL-5, when compared with parental allergens and D. pteronyssinus extract.

CONCLUSIONS

rDer p 2231 has the potential to be used in AIT in patients co-sensitized with D. pteronyssinus major allergens, once it was able to reduce IgE production, inducing allergen-specific blocking antibodies, restoring and balancing Th1/Th2 immune responses, and inducing regulatory T-cells.

Partial characterization of purified glycoprotein from nutshell of Arachis hypogea L. towards macrophage activation and leishmaniacidal activity

Arachis hypogea L. protein fraction-2 (AHP-F2) from the Peanut shell was extracted and characterized and its potent immunomodulatory and anti-leishmanial role was determined in this present study. AHP-F2 was found to be a glycoprotein as the presence of carbohydrates were confirmed by the analysis of high-performance liquid chromatography (HPLC) yielded glucose, galactose, mannose, and xylose. AHP-F2 molecular mass was found to be ∼28 kDa as indicated in MALDI-TOF and peptide mass fingerprinting analysis followed by Mascot search. The peptide matches revealed the similarity of the mannose/glucose binding lectin with 71.07% in the BLAST analysis. After that, the 3D structure of the AHP-F2 model was designed and validated by the Ramachandran plot. The immunomodulatory role of AHP-F2 was established in murine peritoneal macrophages as induction of nitric oxide (NO), and stimulation of proinflammatory cytokines (IL-12 and IFN-γ) in a dose-dependent manner was observed. Interestingly, it was also found that AHP-F2 has interacted with the innate immune receptor, toll-like receptors (TLRs) as established in molecular docking as well as mRNA expression. The anti-leishmanial potential of AHP-F2 was revealed with a prominent inhibition of amastigote growth within the murine macrophages with prompt induction of nitrite release. Altogether, the isolated AHP-F2 from Arachis hypogea L. has strong immunomodulatory and anti-leishmanial potential which may disclose a new path to treat leishmaniasis.

Immunoinformatics Protocol to Design Multi-Epitope Subunit Vaccines

With the development of scientific technologies, the accessibility of genomic data, computational tools, software, databases, and machine learning, the field of immunoinformatics has emerged as an effective technique for immunologists to design potential vaccines in a short time. A large number of tools and databases are available to screen the genome sequences of parasites/pathogens and identify the highly immunogenic peptides or epitopes that can be used to design effective vaccines. In this chapter, we provide an easy-to-use protocol for the design of multi-epitope-based subunit vaccines. Though the computational immunoinformatics-based approaches have demonstrated their competency in designing potentially effective vaccine candidates quickly, their immunogenicity and safety must be evaluated in laboratory settings before they are tested in clinical trials.

Identification and design of a multi-epitope subunit vaccine against the opportunistic pathogen Staphylococcus epidermidis: An immunoinformatics approach

Staphylococcus epidermidis is one of the major causes of nosocomial infections around the globe that leads to a high rate of mortality and morbidity in both immunocompromised patients and preterm infants. Despite the alarming increase in multi-drug resistance, no promising vaccines are readily available against this pathogen. Thus, the present study is focused on designing a multi-epitope subunit vaccine using five antigenic proteins of S. epidermidis through an immunoinformatics approach. The final vaccine comprised B-cell, HTL, and CTL binding epitopes followed by Lipoprotein LprA adjuvant added at N-terminal to augment the immunogenicity. Physicochemical assessment of the vaccine reveals the antigenic and non-allergic nature. The vaccine structure was designed, refined, validated, and disulfide engineered to obtain the best model. Molecular docking and dynamics simulation of the proposed vaccine with toll-like receptors (TLR-2 and TLR-4) showed strong and stable interactions. MM-PBSA analysis was implemented as an efficient tool to determine the intermolecular binding free energies of the system. The vaccine was subjected to immune simulation to predict its immunogenic profile. In silico cloning suggested that the proposed vaccine can be expressed efficiently in E.coli. Furthermore, in vivo animal experiment is needed to determine the effectiveness of the in silico designed vaccine.Communicated by Ramaswamy H. Sarma.

Protective efficacy evaluation of immunogenic protein AHA_3793 of Aeromonas hydrophila as vaccine candidate for largemouth bass Micropterus salmoides

Aeromonas hydrophila is a Gram-negative pathogen that can infect various fish, including largemouth bass (Micropterus salmoides), which have caused huge economic losses. In present study, largemouth bass anti-A. hydrophila antibodies were produced, then a highly immunogenic outer membrane proteins, AHA_3793, was identified by combined western blotting and mass spectrometry analysis. Moreover, AHA_3793 was expressed, and its immunogenicity was further verified by western blotting. Subsequently, the protective efficacy of AHA_3793 were evaluated in largemouth bass. The results showed that rAHA_3793 could produce a relative percentage survival (RPS) of 61.76% for largemouth bass against A. hydrophila challenge. ELISA analysis showed the specific serum antibodies of largemouth bass against rAHA_3793 and A. hydrophila in vaccinated group in weeks 4 and 5 after immunization were significantly higher than those in control group, which suggested that rAHA_3793 induced production of specific serum antibodies against rAHA_3793 and A. hydrophila. The qRT-PCR analysis showed that expressions of CD4-2 and MHC IIα were also significantly up-regulated after immunization. These results collectively demonstrated that rAHA_3793 could induce a strong humoral immune response of largemouth bass, and then produce high immune protection effects against A. hydrophila infection.

Comprehensive computational analysis reveals YXXΦ[I/L/M/F/V] motif and YXXΦ-like tetrapeptides across HFRS causing Hantaviruses and their association with viral pathogenesis and host immune regulation

Hemorrhagic fever with renal syndrome (HFRS) is an acute zoonotic disease transmitted through aerosolized excrement of rodents. The etiology of HFRS is complex due to the involvement of viral factors and host immune and genetic factors. The viral species that dominantly cause HFRS are Puumala virus (PUUV), Seoul virus (SEOV), Dobrava-Belgrade virus (DOBV), and Hantaan virus (HTNV). Despite continuous prevention and control measures, HFRS remains a significant public health problem worldwide. The nucleocapsid protein of PUUV, SEOV, DOBV, and HTNV is a multifunctional viral protein involved in various stages of the viral replication cycle. However, the exact role of nucleoproteins in viral pathogenesis is yet to be discovered. Targeting a universal host protein exploited by most viruses would be a game-changing strategy that offers broad-spectrum solutions and rapid epidemic control. The objective of this study is to understand the replication and pathogenesis of PUUV, SEOV, DOBV, and HTNV by targeting tyrosine-based motif (YXXΦ[I/L/M/F/V]) and YXXΦ-like tetrapeptides. In the light of the current study, in silico analysis uncovered many different YXXΦ[I/L/M/F/V] motifs and YXXΦ-like tetrapeptides within nucleoproteins of PUUV, SEOV, DOBV, and HTNV. Following that, the 3D structures of nucleoproteins were predicted using AlphaFold2 to map the location of YXXΦ[I/L/M/F/V] motif and YXXΦ-like tetrapeptides in a 3D environment. Further, in silico analysis and characterization of Post Translational Modifications (PTMs) revealed multiple PTMs sites within YXXΦ[I/L/M/F/V] motif and YXXΦ-like tetrapeptides, which contribute to virulence and host immune regulation. Our study proposed that the predicted YXXΦ[I/L/M/F/V] motif and YXXΦ-like tetrapeptides may confer specific functions such as virulence, host immune regulation, and pathogenesis to nucleoproteins of PUUV, SEOV, DOBV, and HTNV. However, in vivo and in vitro studies on YXXΦ[I/L/M/F/V] motif and YXXΦ-like tetrapeptides will assign new biological roles to these antiviral targets.

Immunoinformatic analysis of the whole proteome for vaccine design: An application to Clostridium perfringens

Clostridium perfringens is a dangerous bacterium and known biological warfare weapon associated with several diseases, whose lethal toxins can produce necrosis in humans. However, there is no safe and fully effective vaccine against C. perfringens for humans yet. To address this problem, we computationally screened its whole proteome, identifying highly immunogenic proteins, domains, and epitopes. First, we identified that the proteins with the highest epitope density are Collagenase A, Exo-alpha-sialidase, alpha n-acetylglucosaminidase and hyaluronoglucosaminidase, representing potential recombinant vaccine candidates. Second, we further explored the toxins, finding that the non-toxic domain of Perfringolysin O is enriched in CTL and HTL epitopes. This domain could be used as a potential sub-unit vaccine to combat gas gangrene. And third, we designed a multi-epitope protein containing 24 HTL-epitopes and 34 CTL-epitopes from extracellular regions of transmembrane proteins. Also, we analyzed the structural properties of this novel protein using molecular dynamics. Altogether, we are presenting a thorough immunoinformatic exploration of the whole proteome of C. perfringens, as well as promising whole-protein, domain-based and multi-epitope vaccine candidates. These can be evaluated in preclinical trials to assess their immunogenicity and protection against C. perfringens infection.

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

BACKGROUND

Cervical cancer is the fourth most common cancer affecting women and is caused by human Papillomavirus (HPV) infections that are sexually transmitted. There are currently commercially available prophylactic vaccines that have been shown to protect vaccinated individuals against HPV infections, however, these vaccines have no therapeutic effects for those who are previously infected with the virus. The current study's aim was to use immunoinformatics to develop a multi-epitope vaccine with therapeutic potential against cervical cancer.

RESULTS

In this study, T-cell epitopes from E5 and E7 proteins of HPV16/18 were predicted. These epitopes were evaluated and chosen based on their antigenicity, allergenicity, toxicity, and induction of IFN-γ production (only in helper T lymphocytes). Then, the selected epitopes were sequentially linked by appropriate linkers. In addition, a C-terminal fragment of Mycobacterium tuberculosis heat shock protein 70 (HSP70) was used as an adjuvant for the vaccine construct. The physicochemical parameters of the vaccine construct were acceptable. Furthermore, the vaccine was soluble, highly antigenic, and non-allergenic. The vaccine's 3D model was predicted, and the structural improvement after refinement was confirmed using the Ramachandran plot and ProSA-web. The vaccine's B-cell epitopes were predicted. Molecular docking analysis showed that the vaccine's refined 3D model had a strong interaction with the Toll-like receptor 4. The structural stability of the vaccine construct was confirmed by molecular dynamics simulation. Codon adaptation was performed in order to achieve efficient vaccine expression in Escherichia coli strain K12 (E. coli). Subsequently, in silico cloning of the multi-epitope vaccine was conducted into pET-28a ( +) expression vector.

CONCLUSIONS

According to the results of bioinformatics analyses, the multi-epitope vaccine is structurally stable, as well as a non-allergic and non-toxic antigen. However, in vitro and in vivo studies are needed to validate the vaccine's efficacy and safety. If satisfactory results are obtained from in vitro and in vivo studies, the vaccine designed in this study may be effective as a therapeutic vaccine against cervical cancer.

Exploratory Algorithm of a Multi-epitope-based Subunit Vaccine Candidate Against Cryptosporidium hominis: Reverse Vaccinology-Based Immunoinformatic Approach

Cryptosporidiosis is the leading protozoan-induced cause of diarrheal illness in children, and it has been linked to childhood mortality, malnutrition, cognitive development, with retardation of growth. Cryptosporidium hominis, the anthroponotically transmitted species within the Cryptosporidium genus, contributes significantly to the global burden of infection, accounting for the majority of clinical cases in numerous nations, as well as its emergence in the last decade is largely due to detections obtained through noteworthy epidemiologic research. Nevertheless, there is no vaccine available, and the only licensed medication, nitazoxanide, has been demonstrated to have efficacy limitations in a number of patient groups recognized to be at high risk of complications. Therefore, current study delineates the computational vaccine design for Cryptosporidium hominis, the notable pathogen for enteric diarrhea. Firstly, a comprehensive literature search was conducted to identify six proteins based on their toxigenicity, allergenicity, antigenicity, and prediction of transmembrane helices to make up a multi-epitope-based subunit vaccine. Following that, antigenic non-toxic HTL epitope, CTL epitope with B cell epitope were predicted from the selected proteins and construct a vaccine candidate with adding an adjuvant and some linkers with immunologically superior epitopes. Afterwards, the constructed vaccine candidates and TLR2 receptor were put into the ClusPro server for molecular dynamic simulation to know the binding stability of the vaccine-TLR2 complex. Following that, Escherichia coli strain K12 was used as a cloning host for the chosen vaccine construct via the JCat server. As a result of the findings, it was resolute that the proposed chimeric peptide vaccine could improve the immune response to Cryptosporidium hominis.

Proteome based mapping and reverse vaccinology techniques to contrive multi-epitope based subunit vaccine (MEBSV) against Streptococcus pyogenes

Streptococcus pyogenes is a root cause of human infection like pharyngitis, tonsillitis, scarlet fever, impetigo, and respiratory tract infections. About 11 million individuals in the US suffer from pharyngitis every year. Unfortunately, no vaccine against S. pyogenes is available yet. The purpose of this study is to create a multiepitope-based subunit vaccine (MEBSV) targeting S. pyogenes top four highly antigenic proteins by using a combination of immunological techniques and molecular docking to tackle term group A streptococcal (GAS) infections. T-cell (HTL & CTL), B-cell, and IFN-γ of target proteins were forecasted and epitopes having high antigenic properties being selected for subsequent research. For designing of final vaccine, 5LBL, 9CTL, and 4HTL epitopes were joined by the KK, AAY, and GPGPG linkers. To enhance the immune response, the N-end of the vaccine was linked by adjuvant (Cholera enterotoxin subunit B) with a linker named EAAAK. With the addition of adjuvants and linkers, the construct size was 421 amino acids. IFN-γ and B-cell epitopes illustrate that the modeled construct is optimized for cell-mediated immune or humoral responses. The developed MEBSV structure was assessed to be highly antigenic, non-toxic, and non-allergenic. Moreover, disulphide engineering further enhanced the stability of the final vaccine protein. Molecular docking of the MEBSV with toll-like receptor 4 (TLR4) was conducted to check the vaccine's compatibility with the receptor. Besides, in-silico cloning has been carried out for credibility validation and proper expression of vaccine construct. These findings suggested that the multi-epitope vaccine produced might be a potential immunogenic against Group A streptococcus infections but further experimental testing is required to validate this study.

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

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

Designing of a Novel Multi-Antigenic Epitope-Based Vaccine against E. hormaechei: An Intergraded Reverse Vaccinology and Immunoinformatics Approach

Enterobacter hormaechei is involved in multiple hospital-associated infections and is resistant to beta-lactam and tetracycline antibiotics. Due to emerging antibiotics resistance in E. hormaechei and lack of licensed vaccine availability, efforts are required to overcome the antibiotics crisis. In the current research study, a multi-epitope-based vaccine against E. hormaechei was designed using reverse vaccinology and immunoinformatic approaches. A total number of 50 strains were analyzed from which the core proteome was extracted. One extracellular (curlin minor subunit CsgB) and two periplasmic membrane proteins (flagellar basal-body rod protein (FlgF) and flagellar basal body P-ring protein (FlgI) were prioritized for B and T-cell epitope prediction. Only three filtered TPGKMDYTS, GADMTPGKM and RLSAESQAT epitopes were used when designing the vaccine construct. The epitopes were linked via GPGPG linkers and EAAAK linker-linked cholera toxin B-subunit adjuvant was used to enhance the immune stimulation efficacy of the vaccine. Docking studies of the vaccine construct with immune cell receptors revealed better interactions, vital for generating proper immune reactions. Docked complexes of vaccine with MHC-I, MHC-II and Tool-like receptor 4 (TLR-4) reported the lowest binding energy of −594.1 kcal/mol, −706.7 kcal/mol, −787.2 kcal/mol, respectively, and were further subjected to molecular dynamic simulations. Net binding free energy calculations also confirmed that the designed vaccine has a strong binding affinity for immune receptors and thus could be a good vaccine candidate for future experimental investigations.

Development of peptide vaccine candidate using highly antigenic PE-PGRS family proteins to stimulate the host immune response against Mycobacterium tuberculosis H37Rv: an immuno-informatics approach

Tuberculosis (TB) is a fast spreading; transmissible disease caused by the Mycobacterium tuberculosis (M. tuberculosis). M. tuberculosis has a high death rate in its endemic regions due to a lack of appropriate treatment and preventative measures. We have used a vaccinomics strategy to create an effective multi-epitope vaccine against M. tuberculosis. The antigenic proteins with the highest antigenicity were utilised to predict cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and linear B-lymphocyte (LBL) epitopes. CTL and HTL epitopes were covered in 99.97% of the population. Seven epitopes each of CTL, HTL, and LBL were ultimately selected and utilised to develop a multi-epitope vaccine. A vaccine design was developed by combining these epitopes with suitable linkers and LprG adjuvant. The vaccine chimera was revealed to be highly immunogenic, non-allergenic, and non-toxic. To ensure a better expression within the Escherichia coli K12 (E. coli K12) host system, codon adaptation and in silico cloning were accomplished. Following that, various validation studies were conducted, including molecular docking, molecular dynamics simulation, and immunological simulation, all of which indicated that the designed vaccine would be stable in the biological environment and effective against M. tuberculosis infection. The immune simulation revealed higher levels of T-cell and B-cell activity, which corresponded to the actual immune response. Exposure simulations were repeated several times, resulting in increased clonal selection and faster antigen clearance. These results suggest that, if proposed vaccine chimera would test both in-vitro and in-vivo, it could be a viable treatment and preventive strategy for TB.Communicated by Ramaswamy H. Sarma.

A multi-epitope chimeric protein elicited a strong antibody response and partial protection against Edwardsiella ictaluri in Nile tilapia

Edwardsiella ictaluri infects several fish species and protection of the all the susceptible fish hosts from the pathogen using a monovalent vaccine is impossible because the species is composed of host-based genotypes that are genetic, serological and antigenic heterogenous. Here, immunoinformatic approach was employed to design a cross-immunogenic chimeric EiCh protein containing multi-epitopes. The chimeric EiCh protein is composed of 11 B-cell epitopes and 7 major histocompatibility complex class II epitopes identified from E. ictaluri immunogenic proteins previously reported. The 49.32 kDa recombinant EiCh protein was expressed in vitro in Escherichia coli BL-21 (DE3) after which inclusion bodies were successfully solubilized and refolded. Ab initio protein modelling revealed secondary and tertiary structures. Secondary structure was confirmed by circular dichroism spectroscopy. Antigenicity of the chimeric EiCh protein was exhibited by strong reactivity with serum from striped catfish and Nile tilapia experimentally infected with E. ictaluri. Furthermore, immunogenicity of the chimeric EiCh protein was investigated in vivo in Nile tilapia juveniles and it was found that the protein could strongly induce production of specific antibodies conferring agglutination activity and partially protected Nile tilapia juveniles with a relative survival percentage (RPS) of 42%. This study explored immunoinformatics as reverse vaccinology approach in vaccine design for aquaculture to manage E. ictaluri infections.

Development of a Candidate Multi-Epitope Subunit Vaccine against Klebsiella aerogenes: Subtractive Proteomics and Immuno-Informatics Approach

Klebsiella aerogenes is a Gram-negative bacterium which has gained considerable importance in recent years. It is involved in 10% of nosocomial and community-acquired urinary tract infections and 12% of hospital-acquired pneumonia. This organism has an intrinsic ability to produce inducible chromosomal AmpC beta-lactamases, which confer high resistance. The drug resistance in K. aerogenes has been reported in China, Israel, Poland, Italy and the United States, with a high mortality rate (~50%). This study aims to combine immunological approaches with molecular docking approaches for three highly antigenic proteins to design vaccines against K. aerogenes. The synthesis of the B-cell, T-cell (CTL and HTL) and IFN-γ epitopes of the targeted proteins was performed and most conserved epitopes were chosen for future research studies. The vaccine was predicted by connecting the respective epitopes, i.e., B cells, CTL and HTL with KK, AAY and GPGPG linkers and all these were connected with N-terminal adjuvants with EAAAK linker. The humoral response of the constructed vaccine was measured through IFN-γ and B-cell epitopes. Before being used as vaccine candidate, all identified B-cell, HTL and CTL epitopes were tested for antigenicity, allergenicity and toxicity to check the safety profiles of our vaccine. To find out the compatibility of constructed vaccine with receptors, MHC-I, followed by MHC-II and TLR4 receptors, was docked with the vaccine. Lastly, in order to precisely certify the proper expression and integrity of our construct, in silico cloning was carried out. Further studies are needed to confirm the safety features and immunogenicity of the vaccine.

Rational design of chimeric Multiepitope Based Vaccine (MEBV) against human T-cell lymphotropic virus type 1: An integrated vaccine informatics and molecular docking based approach

Human T-cell lymphotropic virus type 1 (HTLV-1) is an infectious virus that has been linked to adult T cell leukemia /lymphoma, aggressive CD4-T cell malignancy and many other immune-related medical illnesses. So far, no effective vaccine is known to combat HTLV-1, hence, the current research work was performed to design a potential multi-epitope-based subunit vaccine (MEBV) by adopting the latest methodology of reverse vaccinology. Briefly, three highly antigenic proteins (Glycoprotein, Accessory protein, and Tax protein) with no or minimal (<37%) similarity with human proteome were sorted out and potential B- and T-cell epitopes were forecasted from them. Highly antigenic, immunogenic, non-toxic, non-allergenic and overlapping epitopes were short-listed for vaccine development. The chosen T-cell epitopes displayed a strong binding affinity with their corresponding Human Leukocyte Antigen alleles and demonstrated 95.8% coverage of the world's population. Finally, nine Cytotoxic T Lymphocytes, six Helper T Lymphocytes and five Linear B Lymphocytes epitopes, joint through linkers and adjuvant, were exploited to design the final MEBV construct, comprising of 382 amino acids. The developed MEBV structure showed highly antigenic properties while being non-toxic, soluble, non-allergenic, and stable in nature. Moreover, disulphide engineering further enhanced the stability of the final vaccine protein. Additionally, Molecular docking analysis and Molecular Dynamics (MD) simulations confirmed the strong association between MEBV construct and human pathogenic immune receptor TLR-3. Repeated-exposure simulations and Immune simulations ensured the rapid antigen clearance and higher levels of cell-mediated immunity, respectively. Furthermore, MEBV codon optimization and in-silico cloning was carried out to confirm its augmented expression. Results of our experiments suggested that the proposed MEBV could be a potential immunogenic against HTLV-1; nevertheless, additional wet lab experiments are needed to elucidate our conclusion.

Promising Technologies in the Field of Helminth Vaccines

Helminths contribute a larger global burden of disease than both malaria and tuberculosis. These eukaryotes have caused human infections since before our earliest recorded history (i.e.: earlier than 1200 B.C. for Schistosoma spp.). Despite the prevalence and importance of these infections, helminths are considered a neglected tropical disease for which there are no vaccines approved for human use. Similar to other parasites, helminths are complex organisms which employ a plethora of features such as: complex life cycles, chronic infections, and antigenic mimicry to name a few, making them difficult to target by conventional vaccine strategies. With novel vaccine strategies such as viral vectors and genetic elements, numerous constructs are being defined for a wide range of helminth parasites; however, it has yet to be discussed which of these approaches may be the most effective. With human trials being conducted, and a pipeline of potential anti-helminthic antigens, greater understanding of helminth vaccine-induced immunity is necessary for the development of potent vaccine platforms and their optimal design. This review outlines the conventional and the most promising approaches in clinical and preclinical helminth vaccinology.

Prioritization of potential vaccine candidates and designing a multiepitope-based subunit vaccine against multidrug-resistant Salmonella Typhi str. CT18: A subtractive proteomics and immunoinformatics approach

Salmonella enterica serovar Typhi (S. Typhi), a causative agent of typhoid fever, is a Gram-negative, human-restricted pathogen that causes significant morbidity and mortality, particularly in developing countries. The currently available typhoid vaccines are not recommended to children below six years of age and have poor long-term efficacy. Due to these limitations and the emerging threat of multidrug-resistance (MDR) strains, the development of a new vaccine is urgently needed. The present study aims to design a multiepitope-based subunit vaccine (MESV) against MDR S. Typhi str. CT18 using a computational-based approach comprising subtractive proteomics and immunoinformatics. Firstly, we investigated the proteome of S. Typhi str. CT18 using subtractive proteomics and identified twelve essential, virulent, host non-homologous, and antigenic outer membrane proteins (OMPs) as potential vaccine candidates with low transmembrane helices (≤1) and molecular weight (≤110 kDa). The OMPs were mapped for cytotoxic T lymphocyte(CTL) epitopes, helper T lymphocyte (HTL) epitopes, and linear B lymphocyte (LBL) epitopes using various immunoinformatics tools and servers. A total of 6, 12, and 11 CTL, HTL, and LBL epitopes were shortlisted, respectively, based on their immunogenicity, antigenicity, allergenicity, toxicity, and hydropathicity potential. Four MESV constructs (MESVCs), MESVC-1, MESVC-2, MESVC-3, and MESVC-4, were designed by linking the CTL, HTL, and LBL epitopes with immune-modulating adjuvants, linkers, and PADRE (Pan HLA DR-binding epitope) sequences. The MESVCs were evaluated for their physicochemical properties, allergenicity, antigenicity, toxicity, and solubility potential to ensure their safety and immunogenic behavior. Secondary and tertiary structures of shortlisted MESVCs (MESVC-1, MESVC-3, and MESVC-4) were predicted, modeled, refined, validated, and then docked with various MHC I, MHC II, and TLR4/MD2 complex. Molecular dynamics (MD) simulation of the final selected MESVC-4 with TLR4/MD2 complex confirms its binding affinity and stability. Codon optimization and in silico cloning verified the translation efficiency and successful expression of MESVC-4 in E. coli str. K12. Finally, the efficiency of MESVC-4 to trigger an effective immune response was assessed by an in silico immune simulation. In conclusion, our findings show that the designed MESVC-4 can elicit humoral and cellular immune responses, implying that it may be used for prophylactic or therapeutic purposes. Therefore, it should be subjected to further experimental validations.

Design of a multi-epitope vaccine against cervical cancer using immunoinformatics approaches

Cervical cancer, caused by human papillomavirus (HPV), is the fourth most common type of cancer among women worldwide. While HPV prophylactic vaccines are available, they have no therapeutic effects and do not clear up existing infections. This study aims to design a therapeutic vaccine against cervical cancer using reverse vaccinology. In this study, the E6 and E7 oncoproteins from HPV16 were chosen as the target antigens for epitope prediction. Cytotoxic T lymphocytes (CTL) and helper T lymphocytes (HTL) epitopes were predicted, and the best epitopes were selected based on antigenicity, allergenicity, and toxicity. The final vaccine construct was composed of the selected epitopes, along with the appropriate adjuvant and linkers. The multi-epitope vaccine was evaluated in terms of physicochemical properties, antigenicity, and allergenicity. The tertiary structure of the vaccine construct was predicted. Furthermore, several analyses were also carried out, including molecular docking, molecular dynamics (MD) simulation, and in silico cloning of the vaccine construct. The results showed that the final proposed vaccine could be considered an effective therapeutic vaccine for HPV; however, in vitro and in vivo experiments are required to validate the efficacy of this vaccine candidate.

Exploring SARS-COV-2 structural proteins to design a multi-epitope vaccine using immunoinformatics approach: An in silico study

In December 2019, a new virus called SARS-CoV-2 was reported in China and quickly spread to other parts of the world. The development of SARS-COV-2 vaccines has recently received much attention from numerous researchers. The present study aims to design an effective multi-epitope vaccine against SARS-COV-2 using the reverse vaccinology method. In this regard, structural proteins from SARS-COV-2, including the spike (S), envelope (E), membrane (M), and nucleocapsid (N) proteins, were selected as target antigens for epitope prediction. A total of five helper T lymphocytes (HTL) and five cytotoxic T lymphocytes (CTL) epitopes were selected after screening the predicted epitopes for antigenicity, allergenicity, and toxicity. Subsequently, the selected HTL and CTL epitopes were fused via flexible linkers. Next, the cholera toxin B-subunit (CTxB) as an adjuvant was linked to the N-terminal of the chimeric structure. The proposed vaccine was analyzed for the properties of physicochemical, antigenicity, and allergenicity. The 3D model of the vaccine construct was predicted and docked with the Toll-like receptor 4 (TLR4). The molecular dynamics (MD) simulation was performed to evaluate the stable interactions between the vaccine construct and TLR4. The immune simulation was also conducted to explore the immune responses induced by the vaccine. Finally, in silico cloning of the vaccine construct into the pET-28 (+) vector was conducted. The results obtained from all bioinformatics analysis stages were satisfactory; however, in vitro and in vivo tests are essential to validate these results.

Immunogenic profiling and designing of a novel vaccine from capsid proteins of FMDV serotype Asia-1 through reverse vaccinology

Foot-and-mouth disease is one of the devastating transboundary animal diseases causing heavy losses to the livestock industry. Different vaccines based on the inactivated FMD virus are used against this disease, but lack of immunological memory and the need for high biocontainment are the major drawbacks of these vaccines. A novel vaccine comprising recombinant antigenic regions is effective, as they lack viruses for production. Considering the fact, capsid proteins vp4, vp2, vp3, and vp1 with 3C protease of FMDV serotype Asia-1 were analyzed through reverse vaccinology approaches in this study. The sequence and structural analysis of the proteins is carried out through various bioinformatic tools and the sequence analysis has figured out the acidic nature and thermal stability of the proteins, likewise, the phylogenetic analysis helped us to trace the FMDV isolates, elucidating that selected proteins belong to the strain (Group VII), which is currently circulating in Pakistan. Next, the B-cell and MHC Class-I epitopes are identified from the antigenic proteins by immunoinformatic tools. The highly conserved, antigenic, and non-allergenic epitopes are used to design the vaccine. Accordingly, the codon adaptation and in silico cloning of the corresponding genes is performed. Thus, the bacterial expression vector could be used for efficient expression and large-scale production of the vaccine.

Designing multi-epitope vaccine against Staphylococcus aureus by employing subtractive proteomics, reverse vaccinology and immuno-informatics approaches

Staphylococcus aureus is a deadly human bacterial pathogen that causes a wide variety of clinical manifestations. Invasive S. aureus infections in hospitals and the community are one of the main causes of mortality and morbidity, as virulent and multi-drug-resistant strains have evolved. There is an unmet and urgent clinical need for immune-based non-antibiotic approaches to treat these infections as the growing antibiotic resistance poses a significant public health danger. Subtractive proteomics assisted reverse vaccinology-based immunoinformatics pipeline was used in this study to target the suitable antigenic proteins for the development of multi-epitope vaccine (MEV). Three essential virulent and antigenic proteins were identified including Glycosyltransferase, Elastin Binding Protein, and Staphylococcal secretory antigen. A variety of immunoinformatics tools have been used to forecast T-cell and B-cell epitopes from target proteins. Seven CTL, five HTL, and eight LBL epitopes, connected through suitable linkers and adjuvant, were employed to design 444 amino acids long MEV construct. The vaccine was paired with the TLR4 agonist 50S ribosomal protein L7/L12 adjuvant to enhance the immune response towards the vaccine. The predicted MEV structure was assessed to be highly antigenic, non-toxic, non-allergenic, flexible, stable, and soluble. Molecular docking simulation of the MEV with the human TLR4 (toll-like receptor 4) and major histocompatibility complex molecules (MHCI and MHCII) was performed to validate the interactions with the receptors. Molecular dynamics (MD) simulation and MMGBSA binding free energy analyses were carried out for the stability evaluation and binding of the MEV docked complexes with TLR4, MHCI and MHCII. To achieve maximal vaccine protein expression with optimal post-translational modifications, MEV was reverse translated, its mRNA structure was analyzed, and finally in silico cloning was performed into E. coli expression host. These rigorous computational analyses supported the effectivity of proposed MEV in protection against infections associated with S. aureus. However, further experimental validations are required to fully evaluate the potential of proposed vaccine candidate.

Immunoinformatics analysis to design novel epitope based vaccine candidate targeting the glycoprotein and nucleoprotein of Lassa mammarenavirus (LASMV) using strains from Nigeria

Lassa mammarenavirus (LASMV) is responsible for a specific type of acute viral hemorrhagic fever known as Lassa fever. Lack of effective treatments and counter-measures against the virus has resulted in a high mortality rate in its endemic regions. Therefore, in this study, a novel epitope-based vaccine has been designed using the methods of immunoinformatics targeting the glycoprotein and nucleoprotein of the virus. After numerous robust analyses, two CTL epitopes, eight HTL epitopes and seven B-cell epitopes were finally selected for constructing the vaccine. All these most promising epitopes were found to be antigenic, non-allergenic, nontoxic and non-human homolog, which made them suitable for designing the subunit vaccine. Furthermore, the selected T-cell epitopes which were found to be fully conserved across different isolates of the virus, were also considered for final vaccine construction. After that, numerous validation experiments, i.e. molecular docking, molecular dynamics simulation and immune simulation were conducted, which predicted that our designed vaccine should be stable within the biological environment and effective in combating the LASMV infection. In the end, codon adaptation and in silico cloning studies were performed to design a recombinant plasmid for producing the vaccine industrially. However, further in vitro and in vivo assessments should be done on the constructed vaccine to finally confirm its safety and efficacy.Communicated by Ramaswamy H. Sarma.

Rational design of multimeric based subunit vaccine against Mycoplasma pneumonia: Subtractive proteomics with immunoinformatics framework

Mycoplasma pneumoniae is the prevalent cause of acquired respiratory infections around the globe. A multi-epitope vaccine (MEV) must be developed to combat infections of M. pneumoniae because there is no specific disease-modifying treatment or vaccination is present. The objective of this research is to design a vaccine that targets M. pneumoniae top five highly antigenic proteins using a combination of immunological techniques and molecular docking. T-cell (HTL & CTL), B-cell, and IFN-γ of target proteins were forecasted and highly conservative epitopes were chosen for further study. For designing of final vaccine, 4LBL, 7CTL, and 5HTL epitopes were joined by linkers of KK, AAY, and GPGPG. The N-end of the vaccine was linked to an adjuvant (Cholera enterotoxin subunit B) with a linker named EAAAK to enhance immunogenicity. After the addition of adjuvants and linkers, the size of the construct was 395 amino acids. The epitopes of IFN-γ and B-cells illustrate that the model construct is optimized for cell-mediated immune or humoral responses. To ensure that the final design is safer and immunogenic, properties like non-allergens, antigenicity, and various physicochemical properties were evaluated. Molecular docking of the vaccine with the toll-like receptor 4 (TLR4) was conducted to check the compatibility of the vaccine with the receptor. Besides, in-silico cloning was utilized for validation of the credibility and proper expression of the vaccine. Furthermore, to confirm that the multi-epitope vaccine created is protective and immunogenic, this research requires experimental validation.

Fasciolosis in India: An overview

Fasciolosis in ruminants is a relentless constraint in the livestock industry across the world. Immuno-prophylactic vaccines against fasciolosis may not come up in near future, rendering the control of this scourge with chemotherapy and snail population control. With the alarming threats of anti-fasciolid drug resistance reported from certain parts of the world; the control of fasciolosis should be directed towards the development of rapid and reliable diagnostic tools to execute the specific and discrete treatment. Understanding the epidemiology of Fasciola, its genomics and proteomics, host-parasite interplay, and advances in drug design research is vital for improving animal health that would ultimately succour to meet the ever-increasing demand for food. Due to possible differences in immune response depending on the species of the host and parasite, immuno-prophylactic studies in India should aim at achieving protective efficacy in buffalo against F. gigantica as workers from other countries concentrate primarily on vaccination of cattle and sheep against F. hepatica. This manuscript focused on the research that has been carried out in India for understanding the epidemiology, genetic diversity, immuno-diagnosis, and possible control measure in terms of immuno-prophylaxis and drug designing against tropical fasciolosis caused by Fasciola gigantica.

Designing a conserved peptide-based subunit vaccine against SARS-CoV-2 using immunoinformatics approach

The widespread of coronavirus (COVID-19) is a new global health crisis that poses a threat to the world. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) originated in bats and was discovered first in Wuhan, Hubei province, China in December 2019. Immunoinformatics and bioinformatics tools were employed for the construction of a multi-epitope subunit vaccine to prevent the diseases. The antigenicity, toxicity and allergenicity of all epitopes used in the construction of the vaccine were predicted and then conjugated with adjuvants and linkers. Vaccine Toll-Like Receptors (2, 3, 4, 8 and 9) complex was also evaluated. The vaccine construct was antigenic, non-toxic and non-allergic, which indicates the vaccines ability to induce antibodies in the host, making it an effective vaccine candidate.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-020-00062-x.

A comprehensive screening of the whole proteome of hantavirus and designing a multi-epitope subunit vaccine for cross-protection against hantavirus: Structural vaccinology and immunoinformatics study

Hantaviruses are an emerging zoonotic group of rodent-borne viruses that are having serious implications on global public health due to the increase in outbreaks. Since there is no permanent cure, there is increasing interest in developing a vaccine against the hantavirus. This research aimed to design a robust cross-protective subunit vaccine using a novel immunoinformatics approach. After careful evaluation, the best predicted cytotoxic & helper T-cell and B-cell epitopes from nucleocapsid proteins, glycoproteins, RdRp proteins, and non-structural proteins were considered as potential vaccine candidates. Among the four generated vaccine models with different adjuvant, the model with toll-like receptor-4 (TLR-4) agonist adjuvant was selected because of its high antigenicity, non-allergenicity, and structural quality. The selected model was 654 amino acids long and had a molecular weight of 70.5 kDa, which characterizes the construct as a good antigenic vaccine candidate. The prediction of the conformational B-lymphocyte (CBL) epitope secured its ability to induce the humoral response. Thereafter, disulfide engineering improved vaccine stability. Afterwards, the molecular docking confirmed a good binding affinity of -1292 kj/mol with considered immune receptor TLR-4 and the dynamics simulation showed high stability of the vaccine-receptor complex. Later, the in silico cloning confirmed the better expression of the constructed vaccine protein in E. coli K12. Finally, in in silico immune simulation, significantly high levels of immunoglobulin M (IgM), immunoglobulin G1 (IgG1), cytotoxic & helper T lymphocyte (CTL & HTL) populations, and numerous cytokines such as interferon-γ (IFN-γ), interleukin-2 (IL-2) etc. were found as coherence with actual immune response and also showed faster antigen clearance for repeated exposures. Nonetheless, experimental validation can demonstrate the safety and cross-protective ability of the proposed vaccine to fight against hantavirus infection.

Designing of a next generation multiepitope based vaccine (MEV) against SARS-COV-2: Immunoinformatics and in silico approaches

Coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory coronavirus 2 (SARS-COV-2) is a significant threat to global health security. Till date, no completely effective drug or vaccine is available to cure COVID-19. Therefore, an effective vaccine against SARS-COV-2 is crucially needed. This study was conducted to design an effective multiepitope based vaccine (MEV) against SARS-COV-2. Seven highly antigenic proteins of SARS-COV-2 were selected as targets and different epitopes (B-cell and T-cell) were predicted. Highly antigenic and overlapping epitopes were shortlisted. Selected epitopes indicated significant interactions with the HLA-binding alleles and 99.93% coverage of the world's population. Hence, 505 amino acids long MEV was designed by connecting 16 MHC class I and eleven MHC class II epitopes with suitable linkers and adjuvant. MEV construct was non-allergenic, antigenic, stable and flexible. Furthermore, molecular docking followed by molecular dynamics (MD) simulation analyses, demonstrated a stable and strong binding affinity of MEV with human pathogenic toll-like receptors (TLR), TLR3 and TLR8. Finally, MEV codons were optimized for its in silico cloning into Escherichia coli K-12 system, to ensure its increased expression. Designed MEV in present study could be a potential candidate for further vaccine production process against COVID-19. However, to ensure its safety and immunogenic profile, the proposed MEV needs to be experimentally validated.

Peptides to combat viral infectious diseases

Viral infectious diseases have resulted in millions of deaths throughout history and have created a significant public healthcare burden. Tremendous efforts have been placed by the scientific communities, health officials and government organizations to detect, treat, and prevent viral infection. However, the complicated life cycle and rapid genetic mutations of viruses demand continuous development of novel medicines with high efficacy and safety profiles. Peptides provide a promising outlook as a tool to combat the spread and re-emergence of viral infection. This article provides an overview of five viral infectious diseases with high global prevalence: influenza, chronic hepatitis B, acquired immunodeficiency syndrome, severe acute respiratory syndrome, and coronavirus disease 2019. The current and potential peptide-based therapies, vaccines, and diagnostics for each disease are discussed.

A multiple peptides vaccine against COVID-19 designed from the nucleocapsid phosphoprotein (N) and Spike Glycoprotein (S) via the immunoinformatics approach

Due to the current Coronavirus (COVID-19) pandemic, the rapid discovery of a safe and effective vaccine is an essential issue. Consequently, this study aims to predict a potential COVID-19 peptide-based vaccine utilizing the Nucleocapsid phosphoprotein (N) and Spike Glycoprotein (S) via the Immunoinformatics approach. To achieve this goal, several Immune Epitope Database (IEDB) tools, molecular docking, and safety prediction servers were used. According to the results, The Spike peptide SQCVNLTTRTQLPPAYTNSFTRGVY is predicted to have the highest binding affinity to the B-Cells. The Spike peptide FTISVTTEI has the highest binding affinity to the Major Histocompatibility Complex class 1 (MHC I) Human Leukocyte Allele HLA-B*1503 (according to the MDockPeP and HPEPDOCK servers, docking scores were −153.9 and −229.356, respectively). The Nucleocapsid peptides KTFPPTEPK and RWYFYYLGTGPEAGL have the highest binding affinity to the MHC I HLA-A0202 allele and the three the Major Histocompatibility Complex class 2 (MHC II) Human Leukocyte Allele HLA-DPA1*01:03/DPB1*02:01, HLA-DQA1*01:02/DQB1-*06:02, HLA-DRB1, respectively. Docking scores of peptide KTFPPTEPK were −153.9 and −220.876. In contrast, docking scores of peptide RWYFYYLGTGPEAGL were ranged from 218 to 318. Furthermore, those peptides were predicted as non-toxic and non-allergen. Therefore, the combination of those peptides is predicted to stimulate better immunological responses with respectable safety.

Design of a multi-epitope subunit vaccine for immune-protection against Leishmania parasite

Visceral Leishmaniasis (VL) is an insect-borne neglected disease caused by the protozoan parasite Leishmania donovani. In the absence of a commercial vaccine against VL, chemotherapy is currently the only option used for the treatment of VL. Vaccination has been considered as the most effective and powerful tool for complete eradication and control of infectious diseases. In this study, we aimed to design a peptide-based vaccine against L. donovani using immuno-bioinformatic tools. We identified 6 HTL, 18 CTL, and 25 B-cell epitopes from three hypothetical membrane proteins of L. donovani. All these epitopes were used to make a vaccine construct along with linkers. An adjuvant was also added at the N-terminal to enhance its immunogenicity. After that, we checked the quality of this vaccine construct and found that it is nontoxic, nonallergic, and thermally stable. A 3D structure of the vaccine construct was also generated by homology modeling to evaluate its interaction with innate immune receptors (TLR). Molecular docking was performed, which confirmed its binding with a toll-like receptor-2 (TLR-2). The stability of vaccine-TLR-2 complex and underlying interactions were evaluated using molecular dynamic simulation. Lastly, we carried out in silico cloning to check the expression of the final designed vaccine. The designed vaccine construct needs further experimental and clinical investigations to develop it as a safe and effective vaccine against VL infection.

Exploration of surface glycoprotein to design multi-epitope vaccine for the prevention of Covid-19

Stimulation and generation of T and B cell-mediated long-term immune response are essential for the curbing of a deadly virus such as SAR-CoV-2 (Severe Acute Respiratory Corona Virus 2). Immunoinformatics approach in vaccine design takes advantage of antigenic and non-allergenic epitopes present on the spike glycoprotein of SARS-CoV-2 to elicit immune responses. T cells and B cells epitopes were predicted, and the selected residues were subjected to allergenicity, antigenicity and toxicity screening which were linked by appropriate linkers to form a multi-epitope subunit vaccine. The physiochemical properties of the vaccine construct were analyzed, and the molecular weight, molecular formula, theoretical isoelectric point value, half-life, solubility score, instability index, aliphatic index and GRAVY were predicted. The vaccine structure was constructed, refined, validated, and disulfide engineered to get the best model. Molecular binding simulation and molecular dynamics simulation were carried out to predict the stability and binding affinity of the vaccine construct with TLRs. Codon acclimatization and in silico cloning were performed to confirm the vaccine expression and potency. Results obtained indicated that this novel vaccine candidate is non-toxic, capable of initiating the immunogenic response and will not induce an allergic reaction. The highest binding energy was observed in TLR4 (Toll-like Receptor 4) (−1398.1), and the least is TLR 2 (−1479.6). The steady rise in Th (T-helper) cell population with memory development was noticed, and IFN-g (Interferon gamma) was provoked after simulation. At this point, the vaccine candidate awaits animal trial to validate its efficacy and safety for use in the prevention of the novel COVID-19 (Coronavirus Disease 2019) infections.

Exploring membrane proteins of Leishmania major to design a new multi-epitope vaccine using immunoinformatics approach

Leishmaniasis is one of the major global endemic diseases. Among all the different forms of the disease, cutaneous Leishmaniasis has the highest prevalence worldwide. Treatment with current drugs has not had a significant effect on the improvement of the disease. An attempt to replace an appropriate vaccine that can stimulate host cellular immunity and induce the response of Major histocompatibility complex I (MHCI) and Major histocompatibility complex II (MHCII) against Leishmania is essential. Vaccine production remains a challenge despite the use of different antigens for vaccination against Leishmania major. Hence, we were used the immunoinformatics approach to design a new multi-epitope vaccine against L. major using immunogenic outer membrane proteins. Helper T-lymphocyte (HTL) and Cytotoxic T lymphocyte (CTL) epitopes were predicted and for final confirmation of the selected epitopes, docking analysis, and molecular dynamics simulation was performed. Then, GDGDG linker and profilin adjuvant were added to enhance the immunity of vaccines. The designed vaccine was evaluated in terms of molecular weight, PI, immunogenicity, and allergenicity. Moreover, the secondary and three-dimensional structure of the final construct was identified. In silico cloning approach was carried out to improve expression of the vaccine construct. Finally, molecular docking, followed by molecular dynamic was performed to determine the interaction between multi-epitope vaccine and TLR11. We hope that the designed vaccine can be a good candidate for the development of cutaneous leishmaniasis vaccine. but its effectiveness should be assessed in vivo.

Design of a multi-epitope vaccine against SARS-CoV-2 using immunoinformatics approach

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused COVID-19 disease in China. So far, no vaccine has licensed to protect against infection with COVID-19, therefore an effective COVID-19 vaccine needed. The aim of this study was to predict antigenic peptides of SARS-CoV-2 for designing the COVID-19 vaccine using immunoinformatic analysis. In this study, T and B-cell epitopes of S protein were predicted and screened based on the antigenicity, toxicity, allergenicity, and cross-reactivity with human proteomes. The epitopes were joined by the appropriate linker. LT-IIc as an adjuvant was attached to the end of the structure. The secondary and 3D structure of the vaccine was predicted. The refinement process was performed to improve the quality of the 3D model structure; the validation process is performed using the Ramachandran plot and ProSA z-score. The proposed vaccine's binding affinity to the HLA-A11:01 and HLA-DRB1_01:01 molecule was evaluated by molecular docking. Using molecular dynamics, the stability of vaccine-HLA complexes was also evaluated. Finally, in silico gene cloning was performed in the pET30a (+) vector. The findings suggest that the current vaccine may be a promising vaccine to prevent SARS-CoV-2 infection.

Computational design of a potential multi-epitope subunit vaccine using immunoinformatics to fight Ebola virus

Ebola virus (EBOV) is a rare but fatal disease that has been a burden to mankind for over 40 years. EBOV exhibits several symptoms including severe bleeding, organ failure and if left untreated causes death. It is assumed that fruit bats of the Pteropodidae family are natural hosts for the virus. Over the years, there has been no effective vaccine that can confer immunity to this virus. Considering the necessity of a vaccine against EBOV, this study to develop a multi-epitope subunit vaccine for the EBOV using the immunoinformatics approach was conducted. The construct was designed using structural and non-structural proteins of EBOV. Class I and Class II MHC epitopes were predicted and linked along with β defensin and compatible linkers. B-cell linear epitopes were also assessed and the physiological parameters of the vaccine were determined. The vaccine was capable of administration to humans and also is capable of an immune response. The vaccine was modeled further and affinity towards the TLR4 receptor was studied by docking and simulation for 20 ns. The trajectory analysis high affinity between the vaccine and the construct with an average hydrogen bond of 18. For ease of purification, the vaccine construct was ligated into pET28a(+) vector with His-tag. Concluding from the results, the vaccine construct has the potentiality to help develop immunity against the Ebola virus. Furthermore, experimental and immunological investigations will be required to verify the feasibility of the multi-epitope subunit construct as a commercial vaccine.

Bacterial protein azurin and derived peptides as potential anti-SARS-CoV-2 agents: insights from molecular docking and molecular dynamics simulations

The current pandemic SARS-CoV-2 has wreaked havoc in the world, and neither drugs nor vaccine is available for the treatment of this disease. Thus, there is an immediate need for novel therapeutics that can combat this deadly infection. In this study, we report the therapeutic assessment of azurin and its peptides: p18 and p28 against the viral structural S-protein and non-structural 3CL^pro and PL^pro proteins. Among the analyzed complexes, azurin docked relatively well with the S2 domain of S-protein compared to the other viral proteins. The derived peptide p18 bound to the active site domain of the PL^pro protein; however, in other complexes, lesser interactions were recorded. The second azurin derived peptide p28, fared the best among the docked proteins. p28 interacted with all the three viral proteins and the host ACE-2 receptor by forming several electrostatic and hydrogen bonds with the S-protein, 3CL^pro, and PL^pro. MD simulations indicated that p28 exhibited a strong affinity to S-protein and ACE-2 receptor, indicating a possibility of p28 as a protein-protein interaction inhibitor. Our data suggest that the p28 has potential as an anti-SARS-CoV-2 agent and can be further exploited to establish its validity in the treatment of current and future SARS-CoV crisis.Communicated by Ramaswamy H. Sarma.

Designing a vaccine for fascioliasis using immunogenic 24 kDa mu-class glutathione s-transferase

Fascioliasis, caused by the liver fluke Fasciola gigantica, is a significant zoonotic disease of the livestock and human, causing substantial economic loss worldwide. Triclabendazole (TCBZ) is the only drug available for the management of the disease against which there is an alarming increase in drug resistance. No vaccine is available commercially for the protection against this disease. Increasing resistance to TCBZ and the lack of a successful vaccine against fascioliasis demands the development of vaccines. In the present study, a structural immunoinformatics approach was used to design a multi-epitope subunit vaccine using the glutathione S-transferase (GST) protein of Fasciola gigantica. The GST antigen is a safe, non-allergic, highly antigenic, and effective vaccine candidate against various parasitic flukes and worms. The cytotoxic T lymphocytes, helper T lymphocytes, and B-cell epitopes were selected for constructing the vaccine based on their immunogenic behavior and binding affinity. The physicochemical properties, allergenicity, and antigenicity of the designed vaccine were analyzed. To elucidate the tertiary structure of the vaccine, homology modeling was performed, followed by structure refinement and docking against the TLR2 immune receptor. Molecular dynamics simulations showed a stable interaction between the vaccine and the receptor complex. Finally, in silico cloning was performed to evaluate the expression and translation of the vaccine construct in the E. coli expression system. Further studies require experimental validation for the safety and immunogenic behavior of the designed vaccine.

Design of a peptide-based subunit vaccine against novel coronavirus SARS-CoV-2

Coronavirus disease 2019 (COVID-19) is an emerging infectious disease that was first reported in Wuhan, China, and has subsequently spread worldwide. In the absence of any antiviral or immunomodulatory therapies, the disease is spreading at an alarming rate. A possibility of a resurgence of COVID-19 in places where lockdowns have already worked is also developing. Thus, for controlling COVID-19, vaccines may be a better option than drugs. An mRNA-based anti-COVID-19 candidate vaccine has entered a phase 1 clinical trial. However, its efficacy and potency have to be evaluated and validated. Since vaccines have high failure rates, as an alternative, we are presenting a new, designed multi-peptide subunit-based epitope vaccine against COVID-19. The recombinant vaccine construct comprises an adjuvant, cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and B-cell epitopes joined by linkers. The computational data suggest that the vaccine is non-toxic, non-allergenic, thermostable, with the capability to elicit a humoral and cell-mediated immune response. The stabilization of the vaccine construct is validated with molecular dynamics simulation studies. This unique vaccine is made up of 33 highly antigenic epitopes from three proteins that have a prominent role in host-receptor recognition, viral entry, and pathogenicity. We advocate this vaccine must be synthesized and tested urgently as a public health priority.

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The rapid increase of SARS-CoV-2 infections across the globe has triggered R&D on an effective vaccine.

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We present a multi-epitope subunit-based vaccine designed using an integrated immunoinformatics approach.

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Our vaccine is made up of 33 highly antigenic epitopes from three vital pathogen proteins.

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Computational data predict that the vaccine is non-toxic, non-allergenic, and immunogenic.

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An experimental evaluation of this vaccine is required to determine its practical immunogenic potency.