A novel in silico minigene vaccine based on CD4+ T-helper and B-cell epitopes of EG95 isolates for vaccination against cystic echinococcosis

Defeating a superbug: A breakthrough in vaccine design against multidrug-resistant Pseudomonas aeruginosa using reverse vaccinology

BACKGROUND

Multidrug-resistant Pseudomonas aeruginosa has become a major cause of severe infections. Due to the lack of approved vaccines, this study has presented putative vaccine candidates against it.

METHODS

P. aeruginosa 24Pae112 as a reference strain was retrieved from GenBank database. The surface-exposed, antigenic, non-allergenic, and non-homologous human proteins were selected. The conserved domains of selected proteins were evaluated, and the prevalence of proteins was assessed among 395 genomes. Next, linear and conformational B-cell epitopes, and human MHC II binding sites were determined. Finally, five conserved and highly antigenic B-cell epitopes from OMPs were implanted on the three platforms as multi-epitope vaccines, including FliC, the bacteriophage T7 tail, and the cell wall-associated transporter proteins. The immunoreactivity was investigated using molecular docking and immune simulation. Furthermore, molecular dynamics simulation was done to refine the chimeric cell-wall-associated transporter-TLR4 complex as the best interaction.

RESULTS

Among 6494 total proteins of P. aeruginosa 24Pae112, 16 proteins (seven OMPs and nine secreted) were ideal according to the defined criteria. These proteins had a molecular weight of 110 kDa and were prevalent in ≥ 75% of P. aeruginosa genomes. Among the presented multi-epitope vaccines, the chimeric cell-wall-associated transporter had the strongest interaction with TLR4. Moreover, the immune simulation response revealed that the bacteriophage T7 tail chimeric protein had the strongest ability to stimulate the immune system. In addition, molecular docking and molecular dynamic simulation indicated the proper and stable interactions between the chimeric cell-wall-associated transporter and TLR4.

CONCLUSION

This study proposed 16 shortlisted proteins as promising immunogenic targets. Two novel platforms (e.g. cell-wall-associated transporter and bacteriophage T7 tail proteins) for designing of multi-epitope vaccines (MEVs), showed the better performance compared to FliC. In our future studies, these two MEVs will receive more scrutiny to evaluate their immunoreactivity.

Identification of a dominant murine T-cell epitope in recombinant protein P29 from Echinococcus granulosus

Echinococcus granulosus causes echinococcosis, an important zoonotic disease worldwide and a major public health issue. Vaccination is an economical and practical approach for controlling E. granulosus. We have previously revealed that a recombinant protein P29 (rEg.P29) is a good vaccine candidate against E. granulosus. However, T cell immunogenic epitopes have not been identified. In the present study, we use rEg.P29-immunized mice as models to screen immunogenic epitopes for the construction of a novel multi-epitope vaccine. We search for immunodominant epitopes from an overlapping peptide library to screen the peptides of rEg.P29. Our results confirm that rEg.P29 immunization in mice elicits the activation of T cells and induces cellular immune responses. Further analyses show that a T cell epitope within amino acids 86–100 of rEg.P29 elicits significant antigen-specific IFN-γ production in CD4+ and CD8+ T cells and promotes specific T-cell activation and proliferation. Collectively, these results provide a reference for the construction of a novel vaccine against broad E. granulosus genotypes based on epitopes of rEg.P29.

Implementation of Vaccinomics and In-Silico Approaches to Construct Multimeric Based Vaccine Against Ovarian Cancer

One of the most common gynecologic cancers is ovarian cancer and ranked third after the other two most common cancers: cervical and uterine. The highest mortality rate has been observed in the case of ovarian cancer. To treat ovarian cancer, an immune-informatics approach was used to design a multi-epitope vaccine (MEV) structure. Epitopes prediction of the cancer testis antigens (NY-ESO-1), A-Kinase anchor protein (AKAP4), Acrosin binding protein (ACRBP), Piwi-like protein (PIWIL3), and cancer testis antigen 2 (LAGE-1) was done. Non-toxic, highly antigenic, non-allergenic, and overlapping epitopes were shortlisted for vaccine construction. Chosen T-cell epitopes displayed a robust binding attraction with their corresponding Human Leukocyte Antigen (HLA) alleles demonstrated 97.59% of population coverage. The vaccine peptide was established by uniting three key constituents, comprising the 14 epitopes of CD8 + cytotoxic T lymphocytes (CTLs), 5 helper epitopes, and the adjuvant. For the generation of the effective response of CD4 + cells towards the T-helper cells, granulocyte–macrophage-colony-stimulating factor (GM-CSF) was applied. With the addition of adjuvants and linkers, the construct size was 547 amino acids. The developed MEV structure was predicted to be antigenic, non-toxic, non-allergenic, and firm in nature. I-tasser anticipated the 3D construction of MEV. Moreover, disulfide engineering further enhanced the stability of the final vaccine protein. In-silico cloning and vaccine codon optimization were done to analyze the up-regulation of its expression. The outcomes established the vaccine’s immunogenicity and safety profile, besides its aptitude to encourage both humoral and cellular immune responses. The offered vaccine, grounded on our in-silico investigation, may be considered for ovarian cancer immunotherapy.

A novel multi-objective metaheuristic algorithm for protein-peptide docking and benchmarking on the LEADS-PEP dataset

Protein-peptide interactions have attracted the attention of many drug discovery scientists due to their possible druggability features on most key biological activities such as regulating disease-related signaling pathways and enhancing the immune system's responses. Different studies have utilized some protein-peptide-specific docking algorithms/methods to predict protein-peptide interactions. However, the existing algorithms/methods suffer from two serious limitations which make them unsuitable for protein-peptide docking problems. First, it seems that the prevalent approaches require to be modified and remodeled for weighting the unbounded forces between a protein and a peptide. Second, they do not employ state-of-the-art search algorithms for detecting the 3D pose of a peptide relative to a protein. To address these restrictions, the present study aims to introduce a novel multi-objective algorithm, which first generates some potential 3D poses of a peptide, and then, improves them through its operators. The candidate solutions are further evaluated using Multi-Objective Pareto Front (MOPF) optimization concepts. To this end, van der Waals, electrostatic, solvation, and hydrogen bond energies between the atoms of a protein and designated peptide are computed. To evaluate the algorithm, it is first applied to the LEADS-PEP dataset containing 53 protein-peptide complexes with up to 53 rotatable branches/bonds and then compared with three popular/efficient algorithms. The obtained results indicate that the MOPF-based approaches which reduce the backbone RMSD between the original and predicted states, achieve significantly better results in terms of the success rate in predicting the near-native conditions. Besides, a comparison between the different types of search algorithms reveals that efficient ones like the multi-objective Trader/differential evolution algorithm can predict protein-peptide interactions better than the popular algorithms such as the multi-objective genetic/particle swarm optimization algorithms.

Design of a Novel Multi-Epitope Vaccine Against Echinococcus granulosus in Immunoinformatics

All the time, echinococcosis is a global zoonotic disease which seriously endangers public health all over the world. In order to speed up the development process of anti-Echinococcus granulosus vaccine, at the same time, it can also save economic cost. In this study, immunoinformatics tools and molecular docking methods were used to predict and screen the antigen epitopes of Echinococcus granulosus, to design a multi-epitope vaccine containing B- and T-cell epitopes. The multi-epitope vaccine could activate B lymphocytes to produce specific antibodies theoretically, which could protect the human body against Echinococcus granulosus infection. It also could activate T lymphocytes and clear the infected parasites in the body. In this study, four CD8+ T-cell epitopes, three CD4+ T-cell epitopes and four B-cell epitopes of Protein EgTeg were identified by immunoinformatics methods. Meanwhile, three CD8+ T-cell epitopes, two CD4+ T-cell epitopes and four B-cell epitopes of Protein EgFABP1 were identified. We constructed the multi-epitope vaccine using linker proteins. The study based on the traditional methods of antigen epitope prediction, further optimized the prediction results combined with molecular docking technology and improved the precision and accuracy of the results. Finally, in vivo and in vitro experiments had verified that the vaccine designed in this study had good antigenicity and immunogenicity.

Interferon-alpha position in combating with COVID-19: A systematic review

The newborn coronaivus disease 2019 (COVID‐19) pandemic has become the foremost concern of health system worldwide. Interferon typeI (IFN‐I) are among the well‐known antiviruses. Hence IFN‐α have gained much attention as a treatment for COVID‐19 recently. To sum up the efficiency of IFN‐α against COVID‐19, we searched PubMed, SCOPUS, and EMBASE, from the date of genesis to the 1st of October 2020. Discharge from hospital and virus clearance considered as primary and secondary outcomes, respectively. We compared the aforementioned outcomes of patients treated with standard care protocol and the patients treated with IFN‐α in addition to standard care protocol. Out of 356 identified records, 14 studies were subjected for full‐text screening. Finally, a systematic review was performed with inclusion of five studies. Majority of the participants were males (ranged from 43.50% to 90.0%). We found that time of viral clearance and polymerase chain reaction negative (days) in most studies were decreased in the INF‐α + standard care group. The mean days of virus's clearance in INF‐α group and standard group reported 27.3 and 32.43. Likewise, the average days of hospitalization was found also lower in INF‐α group (18.55 vs. 24.36). This study provides a stand to conclude that early administration of INF‐α may be accounted as a promising treatment of COVID‐19.

Vaccination with rEGVac elicits immunoprotection against different stages of Echinococcus granulosus life cycle: A pilot study

Vaccination against dog-sheep transmission cycle is necessary to control cystic echinococcosis (CE) infection. A multi-epitope multi-antigenic recombinant vaccine was developed-comprising the three putative vaccine antigens EG95, Eg14-3-3 and EgEnolase-was cloned and expressed. In a pilot experiment, the multi-antigen vaccine was assessed in 15 dogs and 15 sheep (five experimental groups and three animals in each group) by two subcutaneous doses 28 days apart. To evaluate the efficacy of the vaccine candidate first immunological analysis were done comprising IgG and IgE antibodies and the cytokine IL-4 in sera of the immunized dogs and sheep. Serum IgG, IgE, and IL-4, in particular in the dogs, were increased after the two rounds of vaccine candidate injection, while the total number of hydatid cysts was reduced (~85.43%). This pilot trial indicated significant immune protection efficacy against E. granulosus especially in dogs, while its efficacy in sheep was not as high as dogs. The multi-antigenic candidate vaccine is proposed as a protective vaccine modality in both dogs and sheep.

A domain-based vaccine construct against SARS-CoV-2, the causative agent of COVID-19 pandemic: development of self-amplifying mRNA and peptide vaccines

Introduction: Coronavirus disease 2019 (COVID-19) is undoubtedly the most challenging pandemic in the current century with more than 293,241 deaths worldwide since its emergence in late 2019 (updated May 13, 2020). COVID-19 is caused by a novel emerged coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Today, the world needs crucially to develop a prophylactic vaccine scheme for such emerged and emerging infectious pathogens. Methods: In this study, we have targeted spike (S) glycoprotein, as an important surface antigen to identify its B- and T-cell immunodominant regions. We have conducted a multi-method B-cell epitope (BCE) prediction approach using different predictor algorithms to discover the most potential BCEs. Besides, we sought among a pool of MHC class I and II-associated peptide binders provided by the IEDB server through the strict cut-off values. To design a broad-coverage vaccine, we carried out a population coverage analysis for a set of candidate T-cell epitopes and based on the HLA allele frequency in the top most-affected countries by COVID-19 (update 02 April 2020). Results: The final determined B- and T-cell epitopes were mapped on the S glycoprotein sequence, and three potential hub regions covering the largest number of overlapping epitopes were identified for the vaccine designing (I531-N711; T717-C877; and V883-E973). Here, we have designed two domain-based constructs to be produced and delivered through the recombinant protein- and gene-based approaches, including (i) an adjuvanted domain-based protein vaccine construct (DPVC), and (ii) a self-amplifying mRNA vaccine (SAMV) construct. The safety, stability, and immunogenicity of the DPVC were validated using the integrated sequential (i.e. allergenicity, autoimmunity, and physicochemical features) and structural (i.e. molecular docking between the vaccine and human Toll-like receptors (TLRs) 4 and 5) analysis. The stability of the docked complexes was evaluated using the molecular dynamics (MD) simulations. Conclusion: These rigorous in silico validations supported the potential of the DPVC and SAMV to promote both innate and specific immune responses in preclinical studies.

Update on treatment and preventive interventions against COVID-19: an overview of potential pharmacological agents and vaccines

The outbreak of coronavirus disease 2019 (COVID-19) triggered by the new member of the coronaviridae family, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has created an unprecedented challenge for global health. In addition to mild to moderate clinical manifestations such as fever, cough, and fatigue, severe cases often developed lethal complications including acute respiratory distress syndrome (ARDS) and acute lung injury. Given the alarming rate of infection and increasing trend of mortality, the development of underlying therapeutic and preventive treatment, as well as the verification of its effectiveness, are the top priorities. Current research mainly referred to and evaluated the application of the empirical treatment based on two precedents, severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS), including antiviral drugs targeting different stages of virus replication, immunotherapy modulating the overactivated inflammation response, and other therapies such as herbal medicine and mesenchymal stem cells. Besides, the ongoing development of inventing prophylactic interventions such as various vaccines by companies and institutions worldwide is crucial to decline morbidity and mortality. This review mainly focused on promising candidates for the treatment of COVID-19 and collected recently updated evidence relevant to its feasibility in clinical practice in the near future.

Identification of combined T-cell and B-cell reactive Echinococcus granulosus 95 antigens for the potential development of a multi-epitope vaccine

Background

Identification of combined T-cell and B-cell reactive Eg95 antigens for the potential development of a multi-epitope vaccine against Echinococcus granulosus (EG), the causative agent of cystic echinococcosis (CE).

Methods

This study involved the recombinant expression of Eg95 along with associated immune rabbit antiserum preparation. Bioinformatics technology was used to facilitate the analysis of Eg95 molecules. PCR was subsequently used to amplify genetic sequences of the epitopes encoding the T-cell and B-cell reactive peptide fragments. SDS-PAGE was used to assess the expression levels of three proteins. Eg95 serum and patient antiserum, which were assessed using Western blot in order to identify suitable antigenic epitope peptides. ELISA detection assay facilitated comparison of the immune reactivity of the short peptide epitopes. The assay results could be used to determine an EG epitope-based vaccine candidate list from suitably reactive Eg95 epitopes.

Results

Eg95 molecules have 3 T-B table. The phage display systems were successfully built using the M13KE carrier. Expression of the three fusion protein peptides were detected. Western blot showed Eg95 antiserum against EG facilitated identification of the three T-cell and B-cell reactive epitopes. After the reaction intensities analyzed by the ELISA, both of the short peptide epitopes Eg95-2 and Eg95-3 showed strong signal strength and associated antigenicity when combined with patient serum and rabbit anti-rEg95 serum.

Conclusions

This study used bioinformatics methods to construct successfully a T-cell and B-cell epitope phage display system for the Eg95 antigen from EG. The two epitopes of Eg95-2 and Eg95-3 demonstrated strong antigenicity with potential applications for peptide vaccine development.

Immunoinformatics Approach for Multiepitopes Vaccine Prediction against Glycoprotein B of Avian Infectious Laryngotracheitis Virus

Infectious laryngotracheitis virus (ILTV) is a gallid herpesvirus type 1, a member of the genus Iltovirus. It causes an infection in the upper respiratory tract mainly trachea which results in significant economic losses in the poultry industry worldwide. Vaccination against ILTV produced latent infected carriers' birds, which become a source of virus transmission to nonvaccinated flocks. Thus this study aimed to design safe multiepitopes vaccine against glycoprotein B of ILT virus using immunoinformatic tools. Forty-four sequences of complete envelope glycoprotein B were retrieved from GenBank of National Center for Biotechnology Information (NCBI) and aligned for conservancy by multiple sequence alignment (MSA). Immune Epitope Database (IEDB) analysis resources were used to predict and analyze candidate epitopes that could act as a promising peptide vaccine. For B cell epitopes, thirty-one linear epitopes were predicted using Bepipred. However eight epitopes were found to be on both surface and antigenic epitopes using Emini surface accessibility and antigenicity, respectively. Three epitopes (₁₉₀KKLP₁₉₃, ₃₈₆YSSTHVRS₃₉₃, and ₃₁₇KESV₃₂₀) were proposed as B cell epitopes. For T cells several epitopes were interacted with MHC class I with high affinity and specificity, but the best recognized epitopes were ₁₁₈YVFNVTLYY₁₂₆, ₃₃₅VSYKNSYHF₃₄₃, and ₆₂₂YLLYEDYTF₆₃₀. MHC-II binding epitopes, ₃₀₁FLTDEQFTI₃₀₉,₂₇₇FLEIANYQV₂₈₅, and ₇₄₃IASFLSNPF₇₅₁, were proposed as promising epitopes due to their high affinity for MHC-II molecules. Moreover the docked ligand epitopes from MHC-1 molecule exhibited high binding affinity with the receptors; BF chicken alleles (BF2 2101 and 0401) expressed by the lower global energy of the molecules. In this study nine epitopes were predicted as promising vaccine candidate against ILTV. In vivo and in vitro studies are required to support the effectiveness of these predicted epitopes as a multipeptide vaccine through clinical trials.

Functional expression and impact of testis-specific gene antigen 10 in breast cancer: a combined in vitro and in silico analysis

Introduction: Testis-specific gene antigen 10 (TSGA10) is a less-known gene, which is involved in the vague biological paths of different cancers. Here, we investigated the TSGA10 expression using different concentrations of glucose under hypoxia and also its interaction with the hypoxia-inducible factor 1 (HIF-1). Methods: The breast cancer MDA-MB-231 and MCF-7 cells were cultured with different concentrations of glucose (5.5, 11.0 and 25.0 mM) under normoxia/hypoxia for 24, 48, and 72 hours and examined for the HIF-1α expression and cell migration by Western blotting and scratch assays. The qPCR was employed to analyze the expression of TSGA10. Three-dimensional (3D) structure and the energy minimization of the interacting domain of TSGA10 were performed by MODELLER v9.17 and Swiss-PDB viewer v4.1.0/UCSF Chimera v1.11. The UCSF Chimera v1.13.1 and Hex 6.0 were used for the molecular docking simulation. The Cytoscape v3.7.1 and STRING v11.0 were used for protein-protein interaction (PPI) network analysis. The HIF-1a related hypoxia pathways were obtained from BioModels database and reconstructed in CellDesigner v4.4.2. Results: The increased expression of TSGA10 was found to be significantly associated with the reduced metastasis in the MDA-MB-231 cells, while an inverse relationship was seen between the TSGA10 mRNA level and cellular migration but not in the MCF-7 cells. The C-terminal domain of TSGA10 interacted with HIF-1α with high affinity, resulting in PPI network with 10 key nodes (HIF-1α, VEGFA, HSP90AA1, AKT1, ARNT, TP53, TSGA10, VHL, JUN, and EGFR). Conclusions: Collectively, TSGA10 functional expression alters under the hyper-/hypo-glycemia and hypoxia, which indicates its importance as a candidate bio-target for the cancer therapy.

A multi-method and structure-based in silico vaccine designing against Echinococcus granulosus through investigating enolase protein

Introduction: Hydatid disease is a ubiquitous parasitic zoonotic disease, which causes different medical, economic and serious public health problems in some parts of the world. The causal organism is a multi-stage parasite named Echinococcus granulosus whose life cycle is dependent on two types of mammalian hosts viz definitive and intermediate hosts.

Methods: In this study, enolase, as a key functional enzyme in the metabolism of E. granulosus (EgEnolase), was targeted through a comprehensive in silico modeling analysis and designing a host-specific multi-epitope vaccine. Three-dimensional (3D) structure of enolase was modeled using MODELLER v9.18 software. The B-cell epitopes (BEs) were predicted based on the multi-method approach and via some authentic online predictors. ClusPro v2.0 server was used for docking-based T-helper epitope prediction. The 3D structure of the vaccine was modeled using the RaptorX server. The designed vaccine was evaluated for its immunogenicity, physicochemical properties, and allergenicity. The codon optimization of the vaccine sequence was performed based on the codon usage table of E. coli K12. Finally, the energy minimization and molecular docking were implemented for simulating the vaccine binding affinity to the TLR-2 and TLR-4 and the complex stability.

Results: The designed multi-epitope vaccine was found to induce anti-EgEnolase immunity which may have the potential to prevent the survival and proliferation of E. granulosus into the definitive host.

Conclusion: Based on the results, this step-by-step immunoinformatics approach could be considered as a rational platform for designing vaccines against such multi-stage parasites. Furthermore, it is proposed that this multi-epitope vaccine is served as a promising preventive anti-echinococcosis agent.

Phage antibody library screening for the selection of novel high-affinity human single-chain variable fragment against gastrin receptor: an in silico and in vitro study

BACKGROUND

As a membrane G protein coupled receptors (GPCRs) family, gastrin/cholecystokinin-2 receptor (CCK2R) plays a key role in the initiation and development of gastric cancer.

OBJECTIVES

Targeting CCK2R by immunotherapeutics such as single-chain variable fragments (scFvs) may provide an effective treatment modality against gastric cancer. Thus, the main objective of this study was to isolate scFvs specific to CCK2R.

METHODS

To isolate scFvs specific to the CCK2R, we capitalized on a semi-synthetic diverse phage antibody library (PAL) and a solution-phase biopanning process. The library was panned against a biotinylated peptide of the second extracellular loop (ECL2) of CCK2R. After four rounds of biopanning, the selected soluble scFv clones were screened by enzyme-linked immunosorbent assay (ELISA) and examined for specific binding to the peptide. The selected scFvs were purified using immobilized metal affinity chromatography (IMAC). The binding affinity and specificity of the scFvs were examined by the surface plasmon resonance (SPR), immunoblotting and flow cytometry assays and molecular docking using ZDOCK v3.0.2.

RESULTS

Ten different scFvs were isolated, which displayed binding affinity ranging from 0.68 to 8.0 (nM). Immunoblotting and molecular docking analysis revealed that eight scFvs were able to detect the denatured form of CCK2R protein. Of the isolated scFvs, two scFvs showed high-binding affinity to the human gastric adenocarcinoma AGS cells.

CONCLUSIONS

Based on our findings, a couple of the selected scFvs showed markedly high-binding affinity to immobilized CCK2R peptide and CCK2R-overexpressing AGS cells. Therefore, these scFvs are proposed to serve as targeting and/or treatment agents in the diagnosis and immunotherapy of CCK2R-positive tumors. Graphical abstract ᅟ.

In silico design of a triple-negative breast cancer vaccine by targeting cancer testis antigens

Introduction: Triple-negative breast cancer (TNBC) is an important subtype of breast cancer, which occurs in the absence of estrogen, progesterone and HER-2 receptors. According to the recent studies, TNBC may be a cancer testis antigen (CTA)-positive tumor, indicating that the CTA-based cancer vaccine can be a treatment option for the patients bearing such tumors. Of these antigens (Ags), the MAGE-A family and NY-ESO-1 as the most immunogenic CTAs are the potentially relevant targets for the development of an immunotherapeutic way of the breast cancer treatment. Methods: In the present study, immunoinformatics approach was used to design a multi-epitope peptide vaccine to combat the TNBC. The vaccine peptide was constructed by the fusion of three crucial components, including the CD8+ cytotoxic T lymphocytes (CTLs) epitopes, helper epitopes and adjuvant. The epitopes were predicted from the MAGE-A and NY-ESO-1 Ags. In addition, the granulocyte-macrophage-colony-stimulating factor (GM-CSF) was used as an adjuvant to promote the CD4+ T cells towards the T-helper for more strong induction of CTL responses. The components were conjugated by proper linkers. Results: The vaccine peptide was examined for different physiochemical characteristics to confirm the safety and immunogenic behavior. Furthermore, the 3D-structure of the vaccine peptide was predicted based on the homology modeling approach using the MODELLER v9.17 program. The vaccine structure was also subjected to the molecular dynamics simulation study for structure refinement. The results verified the immunogenicity and safety profile of the constructed vaccine as well as its capability for stimulating both the cellular and humoral immune responses. Conclusion: Based on our in-silico analyses, the proposed vaccine may be considered for the immunotherapy of TNBC.

A novel B- and helper T-cell epitopes-based prophylactic vaccine against Echinococcus granulosus

Introduction: In this study, we targeted the worm stage of Echinococcus granulosus to design a novel multi-epitope B- and helper T-cell based vaccine construct for immunization of dogs against this multi-host parasite.

Methods: The vaccine was designed based on the local Eg14-3-3 antigen (Ag). DNA samples were extracted from the protoscoleces of the infected sheep’s liver, and then subjected to the polymerase chain reaction (PCR) with 14-3-3 specific forward and reverse primers. For the vaccine designing, several in silico steps were undertaken. Three-dimensional (3D) structure of the local Eg14-3-3 Ag was modeled by EasyModeller software. The protein modeling accuracy was then analyzed via various validation assays. Potential transmembrane helix, signal peptide, post-translational modifications and allergenicity of Eg14-3-3 were evaluated as the preliminary measures of B-cell epitopes (BEs ) prediction. Having used many web-servers, a well-designed process was carried out for improved prediction of BEs. High ranked linear and conformational BEs were utilized for engineering the final vaccine construct. Possible T-helper epitopes (TEs) were identified by the molecular docking between 13-mer fragments of the Eg14-3-3 Ag and two high frequent dog class II MHC alleles (i.e., DLA-DRB1*01101 and DRB1*01501). The epitopes coverage was evaluated by Shannon’s variability plot.

Results: The final designed construct was analyzed based on different physicochemical properties, which was then codon optimized for high-level expression in Escherichia coli k12. This minigene construct is the first dog-specific epitopic vaccine construct that is established based on TEs with high-binding affinity to canine MHC alleles.

Conclusion: This in silico study is the first part of a multi-antigenic vaccine designing work that represents as a novel dog-specific vaccine against E. granulosus. Here, we present key data on the step-by-step methodologies used for designing this de novo vaccine, which is under comprehensive in vivo investigations.