Rational design of a multivalent vaccine targeting arthropod-borne viruses using reverse vaccinology strategies

Viruses transmitted by arthropods, such as Dengue, Zika, and Chikungunya, represent substantial worldwide health threats, particularly in countries like India. The lack of approved vaccines and effective antiviral therapies calls for developing innovative strategies to tackle these arboviruses. In this study, we employed immunoinformatics methodologies, incorporating reverse vaccinology, to design a multivalent vaccine targeting the predominant arboviruses. Epitopes of B and T cells were recognized within the non-structural proteins of Dengue, Zika, and Chikungunya viruses. The predicted epitopes were enhanced with adjuvants β-defensin and RS-09 to boost the vaccine's immunogenicity. Sixteen distinct vaccine candidates were constructed, each incorporating epitopes from all three viruses. FUVAC-11 emerged as the most promising vaccine candidate through molecular docking and molecular dynamics simulations, demonstrating favorable binding interactions and stability. Its effectiveness was further evaluated using computational immunological studies confirming strong immune responses. The in silico cloning performed using the pET-28a(+) plasmid facilitates the future experimental implementation of this vaccine candidate, paving the way for potential advancements in combating these significant arboviral threats. However, further in vitro and in vivo studies are warranted to confirm the results obtained in this computational study, which highlights the effectiveness of immunoinformatics and reverse vaccinology in creating vaccines against major Arboviruses, offering a promising model for developing vaccines for other vector-borne diseases and enhancing global health security.

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

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

Computational Vaccine Design for Poxviridae Family Viruses

The computational approach to designing vaccines has several useful characteristics over traditional vaccine development, such as being highly specific, less time-consuming and less expensive. Thus, this chapter describes an immunoinformatics workflow to design a vaccine against a member of the Poxviridae family known as Monkeypox virus. The immunoinformatics approach uses several online servers to select highly antigenic and non-allergenic CTL, HTL, and B cell epitopes. Then, it links the predicted epitopes through linkers and submit them for 3D structure modeling. Afterward, the modeled vaccine is docked with TLRs to check the induction of the immune system. Finally, immune simulations are performed to check the level of several immune factors like IgG, IgM, cytokines and interleukins, among others, upon the injection of the constructed vaccine. This approach can be used to successfully design novel and effective vaccine candidates against emerging species from the Poxviridae family.

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

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

An Immunoinformatics Prediction of Novel Multi-Epitope Vaccines Candidate Against Surface Antigens of Nipah Virus

Nipah virus (NiV) is an emerging zoonotic virus causing outbreaks of encephalitis and respiratory illnesses in humans, with high mortality. NiV is considered endemic in Bangladesh and Southeast Asia. There are no licensed vaccines against NiV. This study aimed at predicting a dual-antigen multi-epitope subunit chimeric vaccine against surface-glycoproteins G and F of NiV. Targeted proteins were subjected to immunoinformatics analyses to predict antigenic B-cell and T-cell epitopes. The proposed vaccine designs were implemented based on the conservancy, population coverage, molecular docking, immune simulations, codon adaptation, secondary mRNA structure, and in-silico cloning. Total 40 T and B-cell epitopes were found to be conserved, antigenic (vaxijen-value > 0.4), non-toxic, non-allergenic, and human non-homologous. Of 12 hypothetical vaccines, two (NiV_BGD_V1 and NiV_BGD_V2) were strongly immunogenic, non-allergenic, and structurally stable. The proposed vaccine candidates show a negative Z-score (- 6.32 and - 6.67) and 83.6% and 89.3% of most rama-favored regions. The molecular docking confirmed the highest affinity of NiV_BGD_V1 and NiV_BGD_V2 with TLR-4 (ΔG = - 30.7) and TLR8 (ΔG = - 20.6), respectively. The vaccine constructs demonstrated increased levels of immunoglobulins and cytokines in humans and could be expressed properly using an adenoviral-based pAdTrack-CMV expression vector. However, more experimental investigations and clinical trials are needed to validate its efficacy and safety.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10989-022-10431-z.

Characterization of proteome wide antigenic epitopes to design proteins specific and proteome-wide ensemble vaccines against heartland virus using structural vaccinology and immune simulation approaches

Heartland virus is a single-stranded negative-sense RNA virus that infects humans and causes lethargy, myalgia, headaches, nausea, diarrhea, weight loss, arthralgia, loss of appetite, leukopenia, and easy bruising due thrombocytopenia. The unavailability of antiviral drugs for HRTV infection is a major obstacle to treat this infection, therefore supportive care management is adopted in the case of a severe ailment. In this scientific study, proteins specific and proteome-wide Helper T-cell (HTL), linear B cell, and cytotoxic T-cell (CTL) epitopes mapping joined together with suitable linkers to design multi-epitopes subunit vaccine (MEVC). The constructed four vaccines from nucleocapsid protein, replicase, glycoprotein and finally whole proteome-wide constructs demonstrated stronger antigenic and non-allergenic behavior. Physiochemical properties evaluation also reported easy and efficient expression and downstream analysis of the constructs. Molecular docking of these constructs with toll-like receptor 7 (TLR7) revealed good binding and further validation based on MM/GBSA also demonstrated stronger interaction between the vaccine constructs and TLR7. Moreover, in silico cloning reported CAI value of 0.96 for each construct and excellent GC contents percentage required for experimental analysis. Furthermore, immune simulation-based immune response surveillance revealed that upon the injection of antigen the primary and secondary antibodies were produced between 5-15 days, and a more robust neutralization of the antigen by the proteome-wide vaccine construct was observed. This research could pave the way for the development of dynamic and efficient vaccines that contain a unique mix of numerous HRTV derived antigenic peptides to control HRTV infection.

TN strain proteome mediated therapeutic target mapping and multi-epitopic peptide-based vaccine development for Mycobacterium leprae

Leprosy is a significant universal health problem that is remarkably still a concern in developing countries due to infection frequency. New therapeutic molecules and next-generation vaccines are urgently needed to accelerate the leprosy-free world. In this direction, the present study was performed using two routes: proteome-mediated therapeutic target identification and mapping as well as multi-epitopic peptide-based novel vaccine development using state of the art of computational biology for the TN strain of M. leprae. The TN strain was selected from 65 Mycobacterium strains, and TN strain proteome mediated 83 therapeutic protein targets were mapped and characterized according to subcellular localization. Also, drug molecules were mapped with respect to protein targets localization. The Druggability potential of proteins was also evaluated. For multi-epitope peptide-based vaccine development, the four common types of B and T cell epitopes were identified (SLFQSHNRK, VVGIGQHAA, MMHRSPRTR, LGVDQTQPV) and combined with the suitable peptide linker. The vaccine component had an acceptable protective antigenic score (0.9751). The molecular docking of vaccine components with TLR4/MD2 complex exhibited a low ACE value (-244.12) which signifies the proper binding between the two molecules. The estimated free Gibbs binding energy ensured accurate protein-protein interactions (-112.46 kcal/mol). The vaccine was evaluated through adaptive immunity stimulation as well as immune interactions. The molecular dynamic simulation was carried out by using CHARMM topology-based parameters to minimize the docked complex. Subsequently, the Normal Mode Analysis in the internal coordinates showed a low eigen-value (1.3982892e-05), which also signifies the stability of molecular docking. Finally, the vaccine components were adopted for reverse transcription and codon optimization in E. coli strain K12 for the pGEX-4T1 vector, which supports in silico cloning of the vaccine components against the pathogen. The study directs the experimental study for therapeutics molecules discovery and vaccine candidate development with higher reliability.

Multi-epitope based vaccine design against Staphylococcus epidermidis: A subtractive proteomics and immunoinformatics approach

Staphylococcus epidermidis has emerged as a major contributor of nosocomial infections across the world. With the increased rate of emerging resistant and previously undefined infectious diseases, there is a growing need to develop a novel vaccine possessing required immunogenic properties. The adopted reverse vaccinology approach identified "IMPNQILTI" of LysM domain protein, "YSYTYTIDA" of staphylococcal secretory antigen SsaA, and "YNYDANTGQ" neutral metalloproteinaseas potential peptides for vaccine design. The 9-mer epitope of target proteins is antigenic, virulent, surface-exposed, non-allergenic, and conserved across various strains of S. epidermidis. Protein-protein interactions study indicated the involvement of target proteins in major biological pathways for S. epidermidis pathogenesis. Protein-peptide docking was performed, and population coverage analysis showed significant interactions of T-cell epitopes with the HLA-binding molecules while covering 90.58% of the world's population. Further, a multi-epitope vaccine of 177 amino acids long was constructed. Docking with Toll-like receptor (TLR-2) molecule confirmed the effective interaction of the vaccine with the receptor. The vaccine efficiency in generating an effective immune response in the host was evaluated by immune simulation. Finally, in silico cloning confirmed that the constructed vaccine can be efficiently expressed in E. coli. However, the designed vaccine needs experimental validation to determine the effectiveness and immunogenicity profile, which will ensure an active immunity against S. epidermidis.

Immunoinformatic Approaches for Vaccine Designing for Pathogens with Unclear Pathogenesis

Designing a vaccine against a pathogen has been the toughest challenge to fight against any infectious diseases. To overcome this problem, use of artificial neural network with immuno-informatics is emerging as a front runner solution. For a successful designing of a potent vaccine, prediction of T-cell/B-cell epitopes, antigen processing and presentation analysis, antigenic potential analysis of epitopes, usages of linkers, population coverage, codon optimization, allergenicity assessment, toxicity prediction of construct, and finally protein-peptide docking for stability of vaccine are important steps. To achieve this, several bioinformatics software, tools and online web servers have been developed for each application, which have their own advantages and limitations. Scientists must evaluate these parameters and should take the decision to apply more suitable and precise servers for each analysis and prediction based on their accuracy, suitability, and robustness.

Structure-guided design of multi-epitopes vaccine against variants of concern (VOCs) of SARS-CoV-2 and validation through In silico cloning and immune simulations

Severe Acute Respiratory Syndrome Corovirus2 (SARS-CoV-2) has been determined to be the cause of the current pandemic. Typical symptoms of patient having COVID-19 are fever, runny nose, cough (dry or not) and dyspnea. Several vaccines are available in markets that are tackling current pandemic. Many different strains of SAR-CoV-2 have been evolved with the passage of time. The emergence of VOCs particularly the B.1.351 ("South African") variant of SARS-CoV-2 has been reported to be more resistant than other SARS-CoV-2 strains to the current vaccines. Thus, the current research is focused to design multi-epitope subunit Vaccine (MEV) using structural vaccinology techniques. As a result, the designed MEV exhibit antigenic properties and possess therapeutic features that can trigger an immunological response against COVID-19. Furthermore, validation of the MEV using immune simulation and in silico cloning revealed that the proposed vaccine candidate effectively triggered the immune response. Conclusively, the developed MEV needs further wet lab exploration and could be a viable vaccine to manage and prevent COVID-19.

Design of a peptide-based vaccine from late stage specific immunogenic cross-reactive antigens of PE/PPE proteins of Mycobacterium tuberculosis

Since decades now, Tuberculosis (TB) is among the leading cause of death globally. Innovative and extensive research strategies are necessary to lower TB incidence and achieve the End TB Strategy milestone. Epitope-based vaccine designing and development provides a promising solution with high efficacy and effectiveness. Mining of less studied genes of Mycobacterium tuberculosis (Mtb) is crucial for recognizing potential antigenic peptide epitopes which can mount protective immune response in host. Many proteins from ESX associated Proline-Glutamate (PE)/ Proline-Proline-Glutamate (PPE) family are virulence factors and alter host mediated immune response against the pathogen. In the present study, we have targeted 34 late stage expressing (being expressed at 90 days) PE/PPE proteins of Mtb for prediction and identification of promiscuous, immunogenic and cross-reactive CD4⁺ T cell specific epitopes. We found a total of 149 promiscuous and cross-reactive epitopes out of which 42 were antigenic as well. Further, we shortlisted top 10 Promiscuous, Cross-reactive CD4⁺ T cell specific, Antigenic Peptide Epitopes (PCAPEs) which were characterized to be non-allergenic and pro-inflammatory cytokine inducing in nature. These epitopes also showed strong binding affinity for CD8⁺ T cell restricted Major Histo-compatibility Complex (MHC) class I alleles. Additionally, these PCAPEs showed wide population coverage of 99.6% globally for both MHC class I and class II alleles. Molecular docking studies were conducted to confirm the affinity of these shortlisted peptides for widely occurring MHC alleles. Additionally, we performed codon adaptation and in silico cloning of the recombinant vaccine construct incorporating EsxA (ESAT-6) as an adjuvant and the 10 selected PCAPEs joined by linkers. The recombinant vaccine construct showed strong affinity for Toll-like receptor2 (TLR2) immune receptor in docking studies. In silico prediction based study using C-ImmSim server shows significant population of Th1 type immune cells with memory cells lasting for months in response to our vaccine administration. Since, majority of TB vaccines under clinical trials are antigens expressed at early stages; a combinatorial approach inclusive of peptide epitopes derived from proteins being expressed at all stages could be a promising strategy to design and develop effective TB vaccine. Synthesis and experimental validation of this multi-epitopic recombinant TB vaccine construct may result in an effective vaccine to confer protection against Mtb.

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.

Prediction and identification of T cell epitopes of COVID-19 with balanced cytokine response for the development of peptide based vaccines

Recent outbreak of 2019 novel Corona virus poses serious challenge for the global health system. In lieu of paucity of experimental data, tools and the very basic understanding of host immune responses against SARS-CoV-2, well thought effective measures are needed to control COVID-19 pandemic. We have identified specific overlapping antigenic peptide epitopes (OAPE) within the 4 structural proteins of SARS-CoV-2 predictive of triggering robust CD4 and CD8 T cell responses in host using bio-informatics tools (NetMHC4.0, IEDB, and Vaxijen2.0). We speculate an early release of pro-inflammatory cytokines for protection and later release of anti-inflammatory cytokines for prevention of immunopathology in designing a vaccine for Covid-19. Therefore, the selected immunogenic OAPE were subjected to in silico tools (IL-6-Pred, IFNepitope and PIP-EL) for analyzing their pro-inflammatory response. The OAPEs found to be pro-inflammatory in nature were further subjected to prediction servers (IL-4-Pred, IL-10-Pred, Pre-AIP) to characterize them as inducers of anti-inflammatory response as well. We finally filtered out 12 OAPE which had affinity for both CD4 and CD8 T cells as well as were inducers of pro-inflammatory and anti-inflammatory cytokines. On confirmation of OAPE binding affinity for respective T cell specific MHC allele using docking studies (pepATTRACT, Hex8.0 and Discovery studio) they were found to be have more immunogenic potential than the 3 negative control peptides (NCPs) included in the study. Additionally, we constructed CTxB-adjuvanated multi-epitopic vaccine inclusive of the 12 OAPEs which was non-toxic, non-allergenic and capable of inducing both pro-inflammatory and anti-inflammatory cytokines. A successful in silico cloning and docking of modeled subunit vaccine construct with toll like receptor-2 (TLR-2) confirmed the high efficacy of our multi-epitopic vaccine which can through a balanced interplay of cytokines help in creating a steady-state immune equilibrium. In silico immune simulation studies with the vaccine using C-ImmSim server also showed higher percentage of T cells along with production of pro-inflammatory as well as some anti-inflammatory cytokines. Experimental validation of this prediction based study on Peripheral Blood Mononuclear Cells (PBMCs) of un-infected individuals, patients and recovered individuals will facilitate production of high priority effective SARS -CoV-2 vaccine candidate.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-021-00098-7.

Immunogenomics guided design of immunomodulatory multi-epitope subunit vaccine against the SARS-CoV-2 new variants, and its validation through in silico cloning and immune simulation

Reports of the novel and more contagious strains of SARS-CoV-2 originating in different countries have further aggravated the pandemic situation. The recent substitutions in spike protein may be critical for the virus to evade the host's immune system and therapeutics that have already been developed. Thus, this study has employed an immunoinformatics pipeline to target the spike protein of this novel strain to construct an immunogenic epitope (CTL, HTL, and B cell) vaccine against the new variant. Our investigation revealed that 12 different epitopes imparted a critical role in immune response induction. This was validated by an exploration of physiochemical properties and experimental feasibility. In silico and host immune simulation confirmed the expression and induction of both primary and secondary immune factors such as IL, cytokines, and antibodies. The current study warrants further lab experiments to demonstrate its efficacy and safety.

Genome-wide screening of vaccine targets prioritization and reverse vaccinology aided design of peptides vaccine to enforce humoral immune response against Campylobacter jejuni

Campylobacter jejuni, gram-negative bacteria, is an infectious agent of foodborne disease-causing bloody diarrhea, abdominal pain, fever, Guillain-Barré syndrome (GBS) and Miller Fisher syndrome in humans. Campylobacter spp. with multidrug resistance to fluoroquinolones, tetracycline, and erythromycin are reported. Hence, an effective vaccine candidate would provide long-term immunity against C. jejuni infections. Thus, we used a subtractive proteomics pipeline to prioritize essential proteins, which impart a critical role in virulence, replication and survival. Five proteins, i.e. Single-stranded DNA-binding protein, UPF0324 membrane protein Cj0999c, DNA translocase FtsK, 50S ribosomal protein L22, and 50S ribosomal protein L1 were identified as virulent proteins and selected for vaccine designing. We reported that the multi-epitopes subunit vaccine based on CTL, HTL and B-cell epitopes combination possess strong antigenic properties and associates no allergenic reaction. Further investigation revealed that the vaccine interacts with the immune receptor (TLR-4) and triggered the release of primary and secondary immune factors. Moreover, the CAI and GC contents obtained through codon optimization were reported to be 0.93 and 53% that confirmed a high expression in the selected vector. The vaccine designed in this study needs further scientific consensus and will aid in managing C. jejuni infections.

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.

An immunoinformatics approach for design and validation of multi-subunit vaccine against Cryptosporidium parvum

An immunoinformatics-based approach is explored for potential multi-subunit vaccine candidates against Cryptosporidium parvum. We performed protein structure based systematic methodology for the development of a proficient multi-subunit vaccine candidate against C. parvum based on their probability of antigenicity, allergenicity and transmembrane helices as the screening criteria. The best-screened epitopes like B-cell epitopes (BCL), Helper T-lymphocytes (HTL) and cytotoxic T- lymphocytes (CTL) were joined by using the appropriate linkers to intensify and develop the presentation and processing of the antigenic molecules. Modeller software was used to generate the best 3D model of the subunit protein. RAMPAGE and other web servers were employed for the validation of the modeled protein. Furthermore, the predicted modeled structure was docked with the two known receptors like TLR2 and TLR4 through ClusPro web server. Based on the docking score, the multi-subunit vaccine docked with TLR2 was subjected to energy minimization by molecular dynamics (MD) simulation to examine their stability within a solvent system. From the simulation study, we found that the residue Glu-107 of subunit vaccine formed a hydrogen bond interaction with Arg-299 of the TLR2 receptor throughout the time frame of the MD simulation. The overall results showed that the multi-subunit vaccine could be an efficient vaccine candidate against C. parvum.

Immunoinformatics and structural vaccinology driven prediction of multi-epitope vaccine against Mayaro virus and validation through in-silico expression

The Mayaro virus (MAYV) belongs to genus "Alphavirus" and family "Togaviridae". MAYV has distribution in the Amazonia, Central and Northeastern regions of Brazil. The abundance of mosquito vector Haemagogus janthinomys has major role in the outbreaks of arthralgia disease in Brazil. Vaccination or immunization is an alternative approach for the protection against this disease. To search the effective candidate for vaccine against Mayaro virus, various immunoinformatics tools were used to predict both the B and T cell epitopes from five structural polyproteins (capsid, E2, 6K, E3and E1). A multi subunit vaccine was designed and the final sequence was modeled for docking with TLR-3. Human b defensin based on previous studies was used as linker. The docked complexes of vaccine-TLR-3 were then subjected to dynamics stability and RMSD and RMSF results suggested that the complexes are stable. Further, to validate our final vaccine construct, in silico cloning was carried out using E. coli as host. The CAI value of 0.96 suggests that the vaccine construct properly expresses in the host. The current findings will be useful for the future experimental validations to ratify the immunogenicity and safety of the supposed structure of vaccine, and ultimately to treat the Mayaro virus, associated infections.

[In silico cloning and comparative analysis of NAD1 gene in three common human parasites]

OBJECTIVE

To in silico clone the NAD1 gene of three common parasites and analyze their bioinformatics, so as to lay the foundation for further research on the NAD gene.

METHODS

By using the in silico cloning method, the full length cDNA (s) of NAD 1 genes of Clonorchis sinensis, Ascaris lumbricoides and Schistosoma japonicum were got, then their physical and chemical properties, compositions of amino acids, subcellular localizations, binary and ternary structures were contrastively analyzed.

RESULTS

The three kinds of NAD1 proteins were similar in the relative molecular weight, subcellular localization, and physical and chemical properties. The NAD1 proteins were highly similar in binary and ternary structures of A. lumbricoides and S. japonicum. The phylogenetic analysis showed that C. sinensis, A. lumbricoides and S. japonicum belonged to the different evolutionary branches with a certain of genetic distance.

CONCLUSIONS

The three NAD1 genes got from C. sinensis, A. lumbricoides and S. japonicum by in silico cloning belong to the same gene of different species, which can be widely used in the researches of heritable variation of parasites.