In silico predicted mycobacterial epitope elicits in vitro T-cell responses

Cross-variant immune shield: computational multiepitope vaccine design against B.617.2 to Omicron sub-lineages in SARS-CoV-2

The COVID-19 pandemic had a profound impact on global health. This study focuses on an in-depth analysis of the structural proteins (Spike (S), Nucleocapsid (N), Membrane (M), and Envelope (E) protein) of SARS-CoV-2 and its variants, aiming to develop a multiepitope vaccine construct that targets the virus independently of its variants. The analysis began by examining genetic variations in viral proteins relative to the reference strain Wuhan-Hu2, particularly in the S, M, N, and E proteins. T-cell epitope predictions for MHC Class-I and Class-II binding were conducted, shedding light on potential cytotoxic and helper T lymphocyte recognition. Identification of linear B-cell epitopes laid the groundwork for antibody-based humoral immune responses. The safety and efficacy of these epitopes were assessed for antigenicity, allergenicity, toxicity, immunogenicity, and conservancy. Population coverage analysis indicated promising global effectiveness of the designed vaccine construct. By incorporating 28 epitopes, we validated that was designed vaccine construct for stability through structural analysis. Molecular dynamics simulations and docking studies revealed its robust interaction with Toll-like receptor 4 (TLR4). Immune simulation studies suggested that the vaccine construct could induce a potent immune response by enhancing antibody titers, B-cell proliferation, memory cell development, and activation of T cells and natural killer cells upon administration. This comprehensive approach offers a promising multiepitope vaccine against SARS-CoV-2, with the potential for broad global coverage and strong immunogenicity. Further experimental validation holds the prospect of introducing a novel candidate vaccine to aid in the ongoing battle against the COVID-19 pandemic.

Peptide-based vaccine design against Hendra virus through immunoinformatics approach

The Hendra virus (HeV) has resulted in epidemics of respiratory and neurological illnesses in animals. Humans have contracted diseases with high fatality rates as a result of infected domestic animals, but effective vaccinations and therapies are currently not available against HeV. Herein, we analyzed the proteome of HeV and constructed an effective and innovative multi-epitope vaccine using immunoinformatics techniques. The vaccine construct was generated, targeting one matrix protein, with the help of the five selected B and T cell epitopes, linkers, and adjuvants and evaluated for their immunogenic properties. In-silico analysis revealed that the epitopes were able to interact with immune receptors and had high antigenic qualities. The post-translational modifications (PTMs), globular, disordered regions, and the active site of the vaccine were predicted, and the strong interactions between the vaccine and Toll-like receptor 5 were observed in molecular docking, indicating their potential significance in the immune response to the designed vaccine. The structural and dynamic stability of the vaccine were ensured by the molecular dynamic simulations. The results of the immune simulations indicated that the designed vaccine might activate B and T cells, which produce high levels of antibodies and cytokines to fight HeV infection. The developed vaccine is useful due to its non-toxicity, non-sensitization, good immunogenicity, non-allergic, and antigenic properties, accessed by various tools; however, experimental verification is needed to confirm the findings of the current study.

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

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

Computational prediction of B and T-cell epitopes of Kyasanur Forest Disease virus marker proteins towards the development of precise diagnosis and potent subunit vaccine

Kyasanur Forest Disease (KFD), also known as 'monkey fever', caused by KFD Virus (KFDV), is a highly neglected tropical disease endemic to Western Ghat region of Karnataka, India. Recently, KFD, which is fatal for both monkeys and humans with a mortality rate of 2-10% has been found to spread from its epicenter to neighboring districts and states also. The current ELISA based KFD detection method is very non-specific due to cross-reactivity with other flaviviruses. Further, presently available formalin-inactivated vaccine has been found to be less effective leading to disease susceptibility and severity. To address these, the present study was aimed at predicting the potent specific B and T-cell epitopes of KFDV immunogenic marker proteins using diverse computational tools aiming at developing precise diagnostic method and an effective subunit vaccine. Here, we have chosen E, NS1 and NS5 proteins as markers of KFDV by taking into account of their differential and non-overlapping sequences with selected arboviruses. Based on the linear and nonlinear epitope prediction tools and important biophysical parameters, we identified three potential linear and ten nonlinear B-cell epitopes. We also predicted T-cell epitope peptides which binds to MHC class-I and class-II receptors for the effective T-cell activation. Thus, our molecular docking and molecular dynamics simulation analysis has identified six different TH-cell epitopes based on the distribution frequency of MHC-II haplotypes in the human population and one TC-cell epitope from NS5 protein that has maximum interaction with class-I MHC. Overall, we have successfully identified potential B and T-cell epitope marker peptides present in the envelope and two non-structural proteins.Communicated by Ramaswamy H. Sarma.

Employing an immunoinformatics approach revealed potent multi-epitope based subunit vaccine for lymphocytic choriomeningitis virus

BACKGROUND

Lymphocytic choriomeningitis virus (LCMV) infects many individuals worldwide and causes severe infection in the immunosuppressant recipient, spontaneous abortion, and congenital disabilities in infants.

OBJECTIVES

There is no specific vaccine or therapeutics available to protect against LCMV infection; thus, there is a need to design a potential vaccine to combat the virus by developing immunity in the population. Herein, we attempted to design a potent multi-epitope vaccine for LCMV using immunoinformatics methods.

METHODS

The whole proteome of the virus was screened and mapped to extract immunodominant B-cell and T-cell epitopes which were fused with appropriate linkers (EAAAK, GGGS, AAY, GPGPG, and AAY), PADRE sequence (13aa) and an adjuvant (50 S ribosomal protein L7/L12) to formulate a multi-epitope vaccine ensemble. Codon adaptation and in silico cloning of the constructed vaccine were carried out using bioinformatics tools. The secondary and tertiary structure of the vaccine construct was predicted and refined. The physicochemical profile of the designed vaccine was analyzed, and the multi-epitope vaccine's potential to bind Toll-like receptors (TLR2 and TLR4) was evaluated through molecular docking and molecular dynamics simulations. Computational immune simulation of the designed vaccine antigen was performed using the C-ImmSim server.

RESULTS

The designed multi-epitope-based vaccine (613 aa) comprised 26 immunodominant (six B-cell, nine cytotoxic T lymphocytes, and 11 helper T lymphocytes) epitopes and is predicted antigenic, non-toxic, non-allergen, soluble, and topographically accessible with a suitable physicochemical profile. The designed vaccine is expected to cover a broad worldwide population (96.35 %) and stimulate a robust adaptive immune response against the virus upon administration. In silico cloning of the constructed vaccine in PET28a (+) vector ensured its optimal expression in the Escherichia coli system. Molecular docking, molecular dynamics simulation, and binding free energy estimation collectively support the stability and energetically favourable interaction of the modeled vaccine-TLR2/4 complexes.

CONCLUSION

The designed multi-epitope vaccine in the present study could serve as a potential vaccine candidate to protect against LMCV infection; however, the experimental validation and safety testing of the vaccine is warranted to validate the study's outcomes.

Identification of a Potential Vaccine against Treponema pallidum Using Subtractive Proteomics and Reverse-Vaccinology Approaches

Syphilis, a sexually transmitted infection, is a deadly disease caused by Treponema pallidum. It is a Gram-negative spirochete that can infect nearly every organ of the human body. It can be transmitted both sexually and perinatally. Since syphilis is the second most fatal sexually transmitted disease after AIDS, an efficient vaccine candidate is needed to establish long-term protection against infections by T. pallidum. This study used reverse-vaccinology-based immunoinformatic pathway subtractive proteomics to find the best antigenic proteins for multi-epitope vaccine production. Six essential virulent and antigenic proteins were identified, including the membrane lipoprotein TpN32 (UniProt ID: O07950), DNA translocase FtsK (UniProt ID: O83964), Protein Soj homolog (UniProt ID: O83296), site-determining protein (UniProt ID: F7IVD2), ABC transporter, ATP-binding protein (UniProt ID: O83930), and Sugar ABC superfamily ATP-binding cassette transporter, ABC protein (UniProt ID: O83782). We found that the multiepitope subunit vaccine consisting of 4 CTL, 4 HTL, and 11 B-cell epitopes mixed with the adjuvant TLR-2 agonist ESAT6 has potent antigenic characteristics and does not induce an allergic response. Before being docked at Toll-like receptors 2 and 4, the developed vaccine was modeled, improved, and validated. Docking studies revealed significant binding interactions, whereas molecular dynamics simulations demonstrated its stability. Furthermore, the immune system simulation indicated significant and long-lasting immunological responses. The vaccine was then reverse-transcribed into a DNA sequence and cloned into the pET28a (+) vector to validate translational activity as well as the microbial production process. The vaccine developed in this study requires further scientific consensus before it can be used against T. pallidum to confirm its safety and efficacy.

Immunoinformatics approach to epitope-based vaccine design against the SARS-CoV-2 in Bangladeshi patients

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the ongoing coronavirus disease 2019 (COVID-19) pandemic which has brought a great challenge to public health. After the first emergence of novel coronavirus SARS-CoV-2 in the city of Wuhan, China, in December 2019. As of March 2020, SARS-CoV-2 was first reported in Bangladesh and since then the country has experienced a steady rise in infections, resulting in 13,355,191 cases and 29,024 deaths as of 27 February 2022. Bioinformatics techniques are used to predict B cell and T cell epitopes from the new SARS-CoV-2 spike glycoprotein in order to build a unique multiple epitope vaccine. The immunogenicity, antigenicity scores, and toxicity of these epitopes were evaluated and chosen based on their capacity to elicit an immune response.

RESULT

The best multi-epitope of the possible immunogenic property was created by combining epitopes. EAAAK, AAY, and GPGPG linkers were used to connect the epitopes. In several computer-based immune response analyses, this vaccine design was found to be efficient, as well as having high population coverage.

CONCLUSION

This research is entirely reliant on the development of epitope-based vaccines, and these in silico findings would represent a major step forward in the development of a vaccine that might eradicate SARS-CoV-2 in Bangladeshi patients.

Designing multi-epitope based peptide vaccine targeting spike protein SARS-CoV-2 B1.1.529 (Omicron) variant using computational approaches

Millions of lives have been infected since the SARS-CoV-2 outbreak in 2019. The high human-to-human transmission rate has warranted a need for a vaccine to protect people. Although some vaccines are in use, due to the high mutation rate in the SARS-CoV-2 multiple variants, the current vaccines may not be sufficient to immunize people against new variant threats. One of the emerging concern variants is B1.1.529 (Omicron), which carries ~ 30 mutations in the Spike protein (S) of SARS-CoV-2 and is predicted to evade antibody recognition even from vaccinated people. We used a structure-based approach and an epitope prediction server to develop a Multi-Epitope based Subunit Vaccine (MESV) involving SARS-CoV-2 B1.1.529 variant spike glycoprotein. The predicted epitope with better antigenicity and non-toxicity was used for designing and predicting vaccine construct features and structure models. In addition, the MESV construct In silico cloning in the pET28a expression vector predicted the construct to be highly translational. The proposed MESV vaccine construct was also subjected to immune simulation prediction and was found to be highly antigenic and elicit a cell-mediated immune response. Therefore, the proposed MESV in the present study has the potential to be evaluated further for vaccine production against the newly identified B1.1.529 (Omicron) variant of concern.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11224-022-02027-6.

Exploring whole proteome to contrive multi-epitope-based vaccine for NeoCoV: An immunoinformtics and in-silico approach

Neo-Coronavirus (NeoCoV) is a novel Betacoronavirus (β-CoVs or Beta-CoVs) discovered in bat specimens in South Africa during 2011. The viral sequence is highly similar to Middle East Respiratory Syndrome, particularly that of structural proteins. Thus, scientists have emphasized the threat posed by NeoCoV associated with human angiotensin-converting enzyme 2 (ACE2) usage, which could lead to a high death rate and faster transmission rate in humans. The development of a NeoCoV vaccine could provide a promising option for the future control of the virus in case of human infection. In silico predictions can decrease the number of experiments required, making the immunoinformatics approaches cost-effective and convenient. Herein, with the aid of immunoinformatics and reverse vaccinology, we aimed to formulate a multi-epitope vaccine that may be used to prevent and treat NeoCoV infection. Based on the NeoCoV proteins, B-cell, cytotoxic T lymphocyte (CTL), and helper T lymphocyte (HTL) epitopes were shortlisted. Four vaccines (Neo-1-4) were devised by fusing shortlisted epitopes with appropriate adjuvants and linkers. The secondary and three-dimensional structures of final vaccines were then predicted. The binding interactions of these potential vaccines with toll-like immune receptors (TLR-2, TLR-3, and TLR-4) and major histocompatibility complex molecules (MHC-I and II) reveal that they properly fit into the receptors' binding domains. Besides, Neo-1 and Neo-4 vaccines exhibited better docking energies of -101.08 kcal/mol and -114.47 kcal/mol, respectively, with TLR-3 as compared to other vaccine constructs. The constructed vaccines are highly antigenic, non-allergenic, soluble, non-toxic, and topologically assessable with good physiochemical characteristics. Codon optimization and in-silico cloning confirmed efficient expression of the designed vaccines in Escherichia coli strain K12. In-silico immune simulation indicated that Neo-1 and Neo-4 vaccines could induce a strong immune response against NeoCoV. Lastly, the binding stability and strong binding affinity of Neo-1 and Neo-4 with TLR-3 receptor were validated using molecular dynamics simulations and free energy calculations (Molecular Mechanics/Generalized Born Surface Area method). The final vaccines require experimental validation to establish their safety and effectiveness in preventing NeoCoV infections.

In silico Designing of an Epitope-Based Vaccine Against Common E. coli Pathotypes

Escherichia coli (E. coli) is a Gram-negative bacterium that belongs to the family Enterobacteriaceae. While E. coli can stay as an innocuous resident in the digestive tract, it can cause a group of symptoms ranging from diarrhea to live threatening complications. Due to the increased rate of antibiotic resistance worldwide, the development of an effective vaccine against E. coli pathotypes is a major health priority. In this study, a reverse vaccinology approach along with immunoinformatics has been applied for the detection of potential antigens to develop an effective vaccine. Based on our screening of 5,155 proteins, we identified lipopolysaccharide assembly protein (LptD) and outer membrane protein assembly factor (BamA) as vaccine candidates for the current study. The conservancy of these proteins in the main E. coli pathotypes was assessed through BLASTp to make sure that the designed vaccine will be protective against major E. coli pathotypes. The multitope vaccine was constructed using cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL), and B cell lymphocyte (BCL) epitopes with suitable linkers and adjuvant. Following that, it was analyzed computationally where it was found to be antigenic, soluble, stable, and non-allergen. Additionally, the adopted docking study, as well as all-atom molecular dynamics simulation, illustrated the promising predicted affinity and free binding energy of this constructed vaccine against the human Toll-like receptor-4 (hTLR-4) dimeric state. In this regard, wet lab studies are required to prove the efficacy of the potential vaccine construct that demonstrated promising results through computational validation.

Immunoinformatics guided modeling of CCHF_GN728, an mRNA-based universal vaccine against Crimean-Congo hemorrhagic fever virus

The Crimean-Congo hemorrhagic fever virus (CCHFV) is a lethal human pathogen belonging to the Nairoviridae family that causes Crimean-Congo hemorrhagic fever (CCHF), a tick-borne infection with an alarming mortality rate of up to 80%. CCHFV is the most widespread tick-borne virus with the potential to trigger a pandemic. To date, no vaccines or therapeutics for CCHF have been authorized. In this study, we implemented immunoinformatics approach for developing CCHF_GN728, a universal mRNA-based multi-epitope vaccine against CCHFV. Glycoprotein precursor (GPC) and nucleoprotein (NP) from the virus were selected and screened for potential immunogenic T- and B-cell epitopes. Our developed antigen exhibited the potential to generate 99.95% population coverage worldwide. Stable epitope-allele interaction was confirmed using molecular docking and dynamics simulation. In silico immune simulation corroborated immune cell response to antigen clearance rate. Optimized codons ensured efficient expression of the mRNA in the host cell. The vaccine exhibited stable and strong interactions with the Toll-like receptors. Our findings suggest that the CCHF_GN728 vaccine will trigger specific anti-CCHFV immune responses. Our model is ready for wet-lab experimentation to assess the efficacy of this putative vaccine candidate.

Prediction of suitable T and B cell epitopes for eliciting immunogenic response against SARS-CoV-2 and its mutant

Spike glycoprotein of SARS-CoV-2 is mainly responsible for the recognition and membrane fusion within the host and this protein has an ability to mutate. Hence, T cell and B cell epitopes were derived from the spike glycoprotein sequence of wild SARS-CoV-2. The proposed T cell and B cell epitopes were found to be antigenic and conserved in the sequence of SARS-CoV-2 mutant (B.1.1.7). Thus, the proposed epitopes are effective against SARS-CoV-2 and its B.1.1.7 mutant. MHC-I that best interacts with the proposed T cell epitopes were found, using immune epitope database. Molecular docking and molecular dynamic simulations were done for ensuring a good binding between the proposed MHC-I and T cell epitopes. The finally proposed T cell epitope was found to be antigenic, non-allergenic, non-toxic and stable. Further, the finally proposed B cell epitopes were also found to be antigenic. The population conservation analysis has ensured the presence of MHC-I molecule (respective to the finally proposed T cell) in human population of most affected countries with SARS-CoV-2. Thus the proposed T and B cell epitope could be effective in designing an epitope-based vaccine, which is effective on SARS-CoV-2 and its B.1.1.7mutant.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13721-021-00348-w.

Designing of a Multi-epitope Vaccine against the Structural Proteins of Marburg Virus Exploiting the Immunoinformatics Approach

Marburg virus disease (MVD) caused by the Marburg virus (MARV) generally appears with flu-like symptoms and leads to severe hemorrhagic fever. It spreads via direct contact with infected individuals or animals. Despite being considered to be less threatening in terms of appearances and the number of infected patients, the high fatality rate of this pathogenic virus is a major concern. Until now, no vaccine has been developed to combat this deadly virus. Therefore, vaccination for this virus is necessary to reduce its mortality. Our current investigation focuses on the design and formulation of a multi-epitope vaccine based on the structural proteins of MARV employing immunoinformatics approaches. The screening of potential T-cell and B-cell epitopes from the seven structural proteins of MARV was carried out through specific selection parameters. Afterward, we compiled the shortlisted epitopes by attaching them to an appropriate adjuvant and linkers. Population coverage analysis, conservancy analysis, and MHC cluster analysis of the shortlisted epitopes were satisfactory. Importantly, physicochemical characteristics, human homology assessment, and structure validation of the vaccine construct delineated convenient outcomes. We implemented disulfide bond engineering to stabilize the tertiary or quaternary interactions. Furthermore, stability and physical movements of the vaccine protein were explored using normal-mode analysis. The immune simulation study of the vaccine complexes also exhibited significant results. Additionally, the protein-protein docking and molecular dynamics simulation of the final construct exhibited a higher affinity toward toll-like receptor-4 (TLR4). From simulation trajectories, multiple descriptors, namely, root mean square deviations (rmsd), radius of gyration (Rg), root mean square fluctuations (RMSF), solvent-accessible surface area (SASA), and hydrogen bonds, have been taken into account to demonstrate the inflexible and rigid nature of receptor molecules and the constructed vaccine. Inclusively, our findings suggested the vaccine constructs' ability to regulate promising immune responses against MARV pathogenesis.

In-silico immunoinformatic analysis of SARS-CoV-2 virus for the development of putative vaccine construct

COVID-19 (CoronaVirus disease 2019) is caused by the SARS-CoV-2 virus (severe acute respiratory syndrome corona virus 2). SARS-CoV-2 virus is highly contagious and affects the human respiratory tract resulting in symptoms such as high fever, body ache, cough, dysfunctions of tastebuds and smelling sense of body. The objective of the present study involves immunoinformatic analysis to predict COVID-19 protein for vaccine construct based on the genomic information SARS-CoV-2 virus. At present, as per WHO estimates, around 133 COVID-19 novel vaccines under development. Three amino acid sequences of SARS-CoV-2 were retrieved from the NCBI database for the analysis of vaccine construct. This study involves computational and immunoinformatic methods. The Immunoinformatic tools used in the present study are NetCTL server, IFN epitope server, Toxin PRED, BCPred, CTL + HTL + ADJUVANTS + LINKERS, AlgPredserver, VaxiJenserver, ProtParam to predict vaccine construct. The secondary and tertiary structure prediction is done by PSIPRED, I-TASSER, Galaxy refine, prosA + Ramachandran. Finally, docking of the vaccine constructs and ligand was done with the help of Cluspro 2.0. C-ImmSimm webserver to simulate the potential vaccine construct. The present study demonstrated three potential Vaccine constructs for the SARS-CoV-2 virus, which were docked with TLR8 (Toll-likereceptor8). Interestingly from these, all constructs one having a high potential for the inhibition effect of the SARS-CoV-2virus. Immunological simulation data shows significant elevated amount of memory B cell; also, the high response was seen in TH(Helper) and TC(cytotoxic) cell population from the vaccine construct proposed in the current study. Hence, these constructs are suitable vaccine candidates that might be useful in developing a novel vaccine.

Design of a novel multiple epitope-based vaccine: An immunoinformatics approach to combat SARS-CoV-2 strains

BACKGROUND

Since the SARS-CoV-2 outbreak in December 2019 in Wuhan, China, the virus has infected more than 153 million individuals across the world due to its human-to-human transmission. The USA is the most affected country having more than 32-million cases till date. Sudden high fever, pneumonia and organ failure have been observed in infected individuals.

OBJECTIVES

In the current situation of emerging viral disease, there is no specific vaccine, or any therapeutics available for SARS-CoV-2, thus there is a dire need to design a potential vaccine to combat the virus by developing immunity in the population. The purpose of present study was to develop a potential vaccine by targeting B and T-cell epitopes using bioinformatics approaches.

METHODS

B- and T-cell epitopes are predicted from novel M protein-SARS-CoV-2 for the development of a unique multiple epitope vaccine by applying bioinformatics approaches. These epitopes were analyzed and selected for their immunogenicity, antigenicity scores, and toxicity in correspondence to their ability to trigger immune response. In combination to epitopes, best multi-epitope of potential immunogenic property was constructed. The epitopes were joined using EAAAK, AAY and GPGPG linkers.

RESULTS

The constructed vaccine showed good results of worldwide population coverage and promising immune response. This constructed vaccine was subjected to in-silico immune simulations by C-ImmSim. Chimeric protein construct was cloned into PET28a (+) vector for expression study in Escherichia coli using snapgene.

CONCLUSION

This vaccine design proved effective in various computer-based immune response analysis as well as showed good population coverage. This study is solely dependent on developing M protein-based vaccine, and these in silico findings would be a breakthrough in the development of an effective vaccine to eradicate SARS-CoV-2 globally.

In silico prediction of B and T cell epitopes based on NDV fusion protein for vaccine development against Newcastle disease virus

Newcastle disease (ND) is known as the most common diseases of economic importance worldwide. Vaccination against virulent strains of Newcastle disease virus (NDV) has failed during some outbreaks. Here, we aimed to assess the epitopes of NDV fusion protein as targets for a peptide-based vaccine. To explore the most antigenic epitopes on the F protein, we retrieved virulent strains of genotype VII from National Center for Biotechnology Information (NCBI). Linear and conformational B-cell epitopes were identified. Moreover, T-cell epitopes with high and moderate binding affinities to human major histocompatibility complex (MHC) class I and class II alleles were predicted using bioinformatics tools. Subsequently, the overlapped epitopes of B-cell and MHC class I and MHC class II were determined. To validate our predictions, the best epitopes were docked, to chicken MHC class I (B-F) alleles using the HADDOCK flexible docking server. Seven ‘high ranked epitopes’ were identified. Among them, ‘LYCTRIVTF’ and ‘MRATYLETL’ showed the highest scores. The other five epitopes including LSGEFDATY, LTTPPYMALK, LYLTELTTV, DCIKITQQV and SIAATNEAV obtained very encouraging results as well. SIAATNEAV had been recognized as a neutralizing epitope of F protein using monoclonal antibodies before. Taken together, our results demonstrated that the identified epitopes needed to be tested by in vitro and in vivo experiments.

Immuno-informatics design of a multimeric epitope peptide based vaccine targeting SARS-CoV-2 spike glycoprotein

Developing an efficacious vaccine for SARS-CoV-2 infection is critical to stemming COVID-19 fatalities and providing the global community with immune protection. We have used a bioinformatic approach to aid in designing an epitope peptide-based vaccine against the spike protein of the virus. Five antigenic B cell epitopes with viable antigenicity and a total of 27 discontinuous B cell epitopes were mapped out structurally in the spike protein for antibody recognition. We identified eight CD8+ T cell 9-mers and 12 CD4+ T cell 14-15-mer as promising candidate epitopes putatively restricted by a large number of MHC I and II alleles, respectively. We used this information to construct an in silico chimeric peptide vaccine whose translational rate was highly expressed when cloned in pET28a (+) vector. With our In silico test, the vaccine construct was predicted to elicit high antigenicity and cell-mediated immunity when given as a homologous prime-boost, triggering of toll-like receptor 5 by the adjuvant linker. The vaccine was also characterized by an increase in IgM and IgG and an array of Th1 and Th2 cytokines. Upon in silico challenge with SARS-CoV-2, there was a decrease in antigen levels using our immune simulations. We, therefore, propose that potential vaccine designs consider this approach.

In silico identification of epitope-based vaccine candidates against HTLV-1

Human T cell leukemia virus type-1 (HTLV-1) is the cause of adult T cell leukemia/lymphoma (ATL), uveitis, and certain pulmonary diseases. In recent decades, many scientists have proposed the development of different treatment and prevention strategies to combat HTLV-1 infection. In this study, we used bioinformatics tools to predict peptide and protein vaccine candidates against HTLV-1 that can potentially induce antibody production and both CD4+ and CD8+ T cell immune responses. Five critical proteins, viz., Hbz, Tax, Pol, Gag, and Env, were analyzed for predicting immunogenic T and B cell epitopes and subsequently evaluated using bioinformatics tools. Based on the predictions, the most antigenic epitopes were selected, and their interaction with immune receptors was investigated. We also designed a protein vaccine candidate with an eight-epitopes-rich domain, including overlapping epitopes detected on both B and T cells. Then, the interaction of the epitope and the designed protein with immune receptors was validated in an in silico docking study. The docking analysis showed that the O2 epitope and D8 protein interact strongly with immune receptors, especially the HLA-A*02:01 receptor. The stability of the interactions was investigated by molecular dynamics (MD) for 100 ns. The root mean square deviation, radius of gyration, hydrogen bonds, and solvent-accessible surface area were calculated for the 100 ns trajectory period. MD studies demonstrated that the O2-HLA-A*02:01 and D8-HLA-A*02:01 complexes were stable during the simulation. Analysis of in silico results showed that the peptide and the designed protein could elicit humoral and cell-mediated immune responses.Communicated by Ramaswamy H. Sarma.

Revisiting potential druggable targets against SARS-CoV-2 and repurposing therapeutics under preclinical study and clinical trials: A comprehensive review

Coronavirus disease-19 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is one of the most contagious diseases in human history that has already affected millions of lives worldwide. To date, no vaccines or effective therapeutics have been discovered yet that may successfully treat COVID-19 patients or contain the transmission of the virus. Scientific communities across the globe responded rapidly and have been working relentlessly to develop drugs and vaccines, which may require considerable time. In this uncertainty, repurposing the existing antiviral drugs could be the best strategy to speed up the discovery of effective therapeutics against SARS-CoV-2. Moreover, drug repurposing may leave some vital information on druggable targets that could be capitalized in target-based drug discovery. Information on possible drug targets and the progress on therapeutic and vaccine development also needs to be updated. In this review, we revisited the druggable targets that may hold promise in the development of the anti-SARS-CoV-2 agent. Progresses on the development of potential therapeutics and vaccines that are under the preclinical studies and clinical trials have been highlighted. We anticipate that this review will provide valuable information that would help to accelerate the development of therapeutics and vaccines against SARS-CoV-2 infection.

Immunoinformatic design of a COVID-19 subunit vaccine using entire structural immunogenic epitopes of SARS-CoV-2

Coronavirus disease 2019 (COVID-19) is an acute pneumonic disease, with no prophylactic or specific therapeutical solution. Effective and rapid countermeasure against the spread of the disease’s associated virus, SARS-CoV-2, requires to incorporate the computational approach. In this study, we employed various immunoinformatics tools to design a multi-epitope vaccine polypeptide with the highest potential for activating the human immune system against SARS-CoV-2. The initial epitope set was extracted from the whole set of viral structural proteins. Potential non-toxic and non-allergenic T-cell and B-cell binding and cytokine inducing epitopes were then identified through a priori prediction. Selected epitopes were bound to each other with appropriate linkers, followed by appending a suitable adjuvant to increase the immunogenicity of the vaccine polypeptide. Molecular modelling of the 3D structure of the vaccine construct, docking, molecular dynamics simulations and free energy calculations confirmed that the vaccine peptide had high affinity for Toll-like receptor 3 binding, and that the vaccine-receptor complex was highly stable. As our vaccine polypeptide design captures the advantages of structural epitopes and simultaneously integrates precautions to avoid relevant side effects, it is suggested to be promising for elicitation of an effective and safe immune response against SARS-CoV-2 in vivo.

Epitope-Based Immunoinformatics Approach on Nucleocapsid Protein of Severe Acute Respiratory Syndrome-Coronavirus-2

With an increasing fatality rate, severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) has emerged as a promising threat to human health worldwide. Recently, the World Health Organization (WHO) has announced the infectious disease caused by SARS-CoV-2, which is known as coronavirus disease-2019 (COVID-2019), as a global pandemic. Additionally, the positive cases are still following an upward trend worldwide and as a corollary, there is a need for a potential vaccine to impede the progression of the disease. Lately, it has been documented that the nucleocapsid (N) protein of SARS-CoV-2 is responsible for viral replication and interferes with host immune responses. We comparatively analyzed the sequences of N protein of SARS-CoV-2 for the identification of core attributes and analyzed the ancestry through phylogenetic analysis. Subsequently, we predicted the most immunogenic epitope for the T-cell and B-cell. Importantly, our investigation mainly focused on major histocompatibility complex (MHC) class I potential peptides and NTASWFTAL interacted with most human leukocyte antigen (HLA) that are encoded by MHC class I molecules. Further, molecular docking analysis unveiled that NTASWFTAL possessed a greater affinity towards HLA and also available in a greater range of the population. Our study provides a consolidated base for vaccine design and we hope that this computational analysis will pave the way for designing novel vaccine candidates.

Immunoinformatics-guided design of an epitope-based vaccine against severe acute respiratory syndrome coronavirus 2 spike glycoprotein

AIMS

With a large number of fatalities, coronavirus disease-2019 (COVID-19) has greatly affected human health worldwide. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the virus that causes COVID-19. The World Health Organization has declared a global pandemic of this contagious disease. Researchers across the world are collaborating in a quest for remedies to combat this deadly virus. It has recently been demonstrated that the spike glycoprotein (SGP) of SARS-CoV-2 is the mediator by which the virus enters host cells.

MAIN METHODS

Our group comprehensibly analyzed the SGP of SARS-CoV-2 through multiple sequence analysis and a phylogenetic analysis. We predicted the strongest immunogenic epitopes of the SGP for both B cells and T cells.

KEY FINDINGS

We focused on predicting peptides that would bind major histocompatibility complex class I. Two optimal epitopes were identified, WTAGAAAYY and GAAAYYVGY. They interact with the HLA-B*15:01 allele, which was further validated by molecular docking simulation. This study also found that the selected epitopes are able to be recognized in a large percentage of the world's population. Furthermore, we predicted CD4+ T-cell epitopes and B-cell epitopes.

SIGNIFICANCE

Our study provides a strong basis for designing vaccine candidates against SARS-CoV-2. However, laboratory work is required to validate our theoretical results, which would lay the foundation for the appropriate vaccine manufacturing and testing processes.

Exploring HCV genome to construct multi-epitope based subunit vaccine to battle HCV infection: Immunoinformatics based approach

Hepatitis C Virus (HCV) infection is a major cause of chronic liver disease, hepatocellular carcinoma, and the single most common indication for liver transplantation. HCV vaccines eliciting specific T-cell responses, have been considered as potent method to prevent HCV infection. Despite several reports on progress of vaccine, these vaccine failed in mediating clinical relevance activity against HCV in humans. In this study we integrated both immunoinformatic and molecular docking approach to present a multiepitope vaccine against HCV by designating 17 conserved epitopes from eight viral proteins such as Core protein, E1, E2, NS2, NS34A, NS4B, NS5A, and NS5B. The epitopes were prioritized based on conservation among epitopes of T cell, B cell and IFN-γ that were then scanned for non-homologous to host and antigenicity. The prioritized epitopes were then linked together by AAY linker and adjuvant (β-defensin) were attached at N-terminal to enhance immunogenic potential. The construct thus formed were subjected to structural modeling and physiochemical characteristics. The modeled structure were successfully docked to antigenic receptor TLR-3 and In-silico cloning confers the authenticity of its expression efficiency. However, the proposed construct need to be validate experimentally to ensure its safety and immunogenic profile.

Designing a multi-epitope vaccine against blood-stage of Plasmodium falciparum by in silico approaches

Plasmodium falciparum causes the most severe form of malaria disease and is the major cause of infection-related mortalities in the world. Due to increasing in P. falciparum resistance to the first-line antimalarial drugs, an effective vaccine for the control and elimination of malaria infection is urgent. Because the pathogenesis of malaria disease results from blood-stage infection, and all of the symptoms and clinical illness of malaria occur during this stage, there is a strong rationale to develop vaccine against this stage. In the present study, different structural-vaccinology and immuno informatics tools were applied to design an effective antibody-inducing multi-epitope vaccine against the blood-stage of P. falciparum. The designed multi-epitope vaccine was composed of three main parts including B cell epitopes, T helper (Th) cell epitopes, and two adjuvant motives (HP91 and RS09), which were linked to each other via proper linkers. B cell and T cell epitopes were derived from four protective antigens expressed on the surface of merozoites, which are critical to invade the erythrocytes. HP91 and RS09 adjuvants and Th cell epitopes were used to induce, enhance and direct the best form of humoral immune-response against P. falciparum surface merozoite antigens. The vaccine construct was modeled, and after model quality evaluation and refinement by different software, the high-quality 3D-structure model of the vaccine was achieved. Analysis of immunological and physicochemical features of the vaccine showed acceptable results. We believe that this multi-epitope vaccine can be effective for preventing malaria disease caused by P. falciparum.

In silico rational design of a novel tetra-epitope tetanus vaccine with complete population coverage using developed immunoinformatics and surface epitope mapping approaches

Presentation of many unwanted epitopes within tetanus toxoid vaccine to lymphocyte clones may lead to production of many unwanted antibodies. Moreover an ideal vaccine must cover all individuals in a population that is dependent to the kinds of human leukocyte antigen alleles. Concerning these issues, our study was aimed to in silico design of a multi-epitope tetanus vaccine (METV) in order to improve population coverage and protectivity of tetanus vaccine as well as reduction of complications. Concerning these issues, a novel rational filtration was implemented to design a novel METV using immunoinformatics and surface epitope mapping approaches. Prediction of epitopes for tetanus toxin was performed in the candidate country in which the frequency had been gathered from almost all geographical distributions. The most strong binder epitopes for major histocompatibility complex class II were selected and among them the surface epitopes of native toxin were selected. The population coverage of the selected epitopes was estimated. The final candidate epitopes had highly population coverage. Molecular docking was performed to prediction of binding affinity of our candidate epitopes to the HLA-DRB1 alleles. At first, 680 strong binder epitopes were predicted. Among them 11 epitopes were selected. Finally, 4 epitopes had the most population coverage and suggested as a tetra-epitope tetanus vaccine. 99.41% of inessential strong binders were deleted using our tree steps filtration. HLA-DP had the most roles in epitope presentation. Molecular docking analysis proved the strong binding affinity of candidate epitopes to the HLA-DRB1 alleles. In conclusion, we theoretically reduced 99.41% of unwanted antibodies using our novel filtration strategies. Our tetra-epitope tetanus vaccine showed 100% population coverage in the candidate country. Furthermore, it was demonstrated that HLA-DP and HLA-DQ had more potential in epitope presentation in comparison to HLA-DRB1.

Mycobacteria-Specific T Cells May Be Expanded From Healthy Donors and Are Near Absent in Primary Immunodeficiency Disorders

Mycobacterial Infections can be severe in patients with T-cell deficiency or phagocyte disorders, and treatment is frequently complicated by antimicrobial resistance. Restoration of T-cell immunity via stem cell transplantation facilitates control of mycobacterial infections, but presence of active infections during transplantation is associated with a higher risk of mortality. Adoptive T cell immunotherapy has been successful in targeting viruses, but has not been attempted to treat mycobacterial infections. We sought to expand and characterize mycobacterial-specific T-cells derived from healthy donors in order to determine suitability for adoptive immunotherapy. Mycobacteria-specific T-cells (MSTs) were generated from 10 healthy donors using a rapid ex vivo expansion protocol targeting five known mycobacterial target proteins (AG85B, PPE68, ESXA, ESXB, and ADK). MSTs were compared to T-cells expanded from the same donors using lysate from M. tuberculosis or purified protein derivative from M. avium (sensitin). MST expansion from seven patients with primary immunodeficiency disorders (PID) and two patients with IFN-γ autoantibodies and invasive M. avium infections. MSTs expanded from healthy donors recognized a median of 3 of 5 antigens, with production of IFN-γ, TNF, and GM-CSF in CD4⁺ T cells. Comparison of donors who received BCG vaccine (n = 6) to those who did not (n = 4) showed differential responses to PPE68 (p = 0.028) and ADK (p = 0.015) by IFN-γ ELISpot. MSTs expanded from lysate or sensitin also recognized multiple mycobacterial antigens, with a statistically significant differences noted only in the response to PPE68 (p = 0.016). MSTs expanded from patients with primary immunodeficiency (PID) and invasive mycobacterial infections showed activity against mycobacterial antigens in only two of seven subjects, whereas both patients with IFN-γ autoantibodies recognized mycobacterial antigens. Thus, MSTs can be generated from donors using a rapid expansion protocol regardless of history of BCG immunization. Most tested PID patients had no detectable T-cell immunity to mycobacteria despite history of infection. MSTs may have clinical utility for adoptive immunotherapy in T-cell deficient patients with invasive mycobacterial infections.

Immunoinformatics Approach for Epitope-Based Peptide Vaccine Design and Active Site Prediction against Polyprotein of Emerging Oropouche Virus

Oropouche virus (OROV) is an emerging pathogen which causes Oropouche fever and meningitis in humans. Several outbreaks of OROV in South America, especially in Brazil, have changed its status as an emerging disease, but no vaccine or specific drug target is available yet. Our approach was to identify the epitope-based vaccine candidates as well as the ligand-binding pockets through the use of immunoinformatics. In this report, we identified both T-cell and B-cell epitopes of the most antigenic OROV polyprotein with the potential to induce both humoral and cell-mediated immunity. Eighteen highly antigenic and immunogenic CD8⁺ T-cell epitopes were identified, including three 100% conserved epitopes (TSSWGCEEY, CSMCGLIHY, and LAIDTGCLY) as the potential vaccine candidates. The selected epitopes showed 95.77% coverage for the mixed Brazilian population. The docking simulation ensured the binding interaction with high affinity. A total of five highly conserved and nontoxic linear B-cell epitopes "NQKIDLSQL," "HPLSTSQIGDRC," "SHCNLEFTAITADKIMSL," "PEKIPAKEGWLTFSKEHTSSW," and "HHYKPTKNLPHVVPRYH" were selected as potential vaccine candidates. The predicted eight conformational B-cell epitopes represent the accessibility for the entered virus. In the posttherapeutic strategy, ten ligand-binding pockets were identified for effective inhibitor design against emerging OROV infection. Collectively, this research provides novel candidates for epitope-based peptide vaccine design against OROV.

Design of an epitope-based peptide vaccine againstCryptococcus neoformans.. [DOI: 10.1101/434779] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Introduction

This study aimed to design an immunogenic epitope for Cryptococcus neoformans the etiological agent of cryptococcosis using in silico simulations, for epitope prediction, we selected the mannoprotein antigen MP88 which it’s known to induce protective immunity.

Material & method

A total of 39 sequences of MP88 protein with length 378 amino acids were retrieved from the National Center for Biotechnology Information database (NCBI) in the FASTA format were used to predict antigenic B-cell and T cell epitopes via different bioinformatics tools at Immune Epitope Database and Analysis Resource (IEDB). The tertiary structure prediction of MP88 was created in RaptorX, and visualized by UCSF Chimera software.

Result

A Conserved B-cell epitopesAYSTPA, AYSTPAS, PASSNCK, and DSAYPPhave displayed the most promising B cell epitopes. While theYMAADQFCL, VSYEEWMNYandFQQRYTGTFthey represent the best candidates T-cell conserved epitopes, the 9-mer epitopeYMAADQFCLdisplay the greater interact with 9 MHC-I alleles and HLA-A*02:01 alleles have the best interaction with an epitope. TheVSYEEWMNYandFQQRYTGTFthey are non-allergen whileYMAADQFCLwas an allergen. For MHC class II peptide binding prediction, theYARLLSLNA, ISYGTAMAVandINQTSYARLrepresent the most Three highly binding affinity core epitopes. The core epitopeINQTSYARLwas found to interact with 14 MHC-II. The allergenicity prediction revealsISYGTAMAV, INQTSYARLwere non-allergen andYARLLSLNAwas an allergen. Regarding population coverage theYMAADQFCLexhibit, a higher percentage among the world (69.75%) and the average population coverage was93.01%.In MHC-II,ISYGTAMAVepitope reveal a higher percentage (74.39%) and the average population coverage was (81.94%). This successfully designed a peptide vaccine against Cryptococcus neoformans open up a new horizon in Cryptococcus neoformans research; the results require validation by in vitro and in vivo experiments.

Identification of broadly reactive epitopes targeting major glycoproteins of Herpes simplex virus (HSV) 1 and 2 - An immunoinformatics analysis

Infections due to both HSV-1 and HSV-2 constitute an enormous health burden worldwide. Development of vaccine against herpes infections is a WHO supported public health priority. The viral glycoproteins have always been the major hotspots for vaccine designing. The present study was aimed to identify the conserved T and B cell epitopes in the major glycoproteins of both HSV-1 and HSV-2 via rigorous computational approaches. Identification of promiscuous T cell epitopes is of utmost importance in vaccine designing as such epitopes are capable of binding to several allelic forms of HLA and could generate effective immune response in the host. The criteria designed for identification of T and B cell epitopes was that it should be conserved in both HSV-1 and 2, promiscuous, have high affinity towards HLA alleles, should be located on the surface of glycoproteins and not be present in the glycosylation sites. This study led to the identification of 17 HLA Class II and 26 HLA Class I T cell epitopes, 9 linear and some conformational B cell epitopes. The identified T cell epitopes were further subjected to molecular docking analysis to analyze their binding patterns. Altogether we have identified 4 most promising regions in glycoproteins (2-gB, 1-gD, 1-gH) of HSV-1 and 2 which are promiscuous to HLA Class II alleles and have overlapping HLA Class I and B cell epitopes, which could be very useful in generating both arms of immune response in the host i.e. adaptive as well as humoral immunity. Further the authors propose the cross-validation of the identified epitopes in experimental settings for confirming their immunogenicity to support the present findings.

Identification of T cell and B cell epitopes against Indian HCV-genotype-3a for vaccine development- An in silico analysis

Hepatitis C virus (HCV) infects almost 150 million people and is a leading cause of liver disease worldwide. It has been classified into seven genotypes; the most common genotype affecting Indian population is genotype 3 (60-70%). Currently there is no vaccine for any genotype of HCV. In order to develop peptide based vaccine against HCV, it is important to identify the conservancy in the circulating genotypes, along with the Human Leucocyte Antigen (HLA) alleles in the target population. The present study aims to identify conserved CD4 and CD8 T cells and B cell epitopes against Indian HCV-genotype-3a using an in silico analysis. In the present study, 28 promiscuous CD4 T cell epitopes and some CD8 epitopes were identified. The NS4 region was predicted to be the most antigenic with maximum number of conserved and promiscuous CD4 T cell epitopes and CD8 T cell epitopes having strong and intermediate affinity towards a number of HLA alleles prevalent in Indian population. Additionally, some linear B cell epitopes were also identified, which could generate neutralizing antibodies. In order to ascertain the binding pattern of the identified epitopes with HLA alleles, molecular docking analysis was carried out. The authors suggest further experimental validation to investigate the immunogenicity of the identified epitopes.

From ZikV genome to vaccine: in silico approach for the epitope-based peptide vaccine against Zika virus envelope glycoprotein

Zika virus (ZikV) has emerged as a potential threat to human health worldwide. A member of the Flaviviridae, ZikV is transmitted to humans by mosquitoes. It is related to other pathogenic vector-borne flaviviruses including dengue, West Nile and Japanese encephalitis viruses, but produces a comparatively mild disease in humans. As a result of its epidemic outbreak and the lack of potential medication, there is a need for improved vaccine/drugs. Computational techniques will provide further information about this virus. Comparative analysis of ZikV genomes should lead to the identification of the core characteristics that define a virus family, as well as its unique properties, while phylogenetic analysis will show the evolutionary relationships and provide clues about the protein's ancestry. Envelope glycoprotein of ZikV was obtained from a protein database and the most immunogenic epitope for T cells and B cells involved in cell-mediated immunity, whereas B cells are primarily responsible for humoral immunity. We mainly focused on MHC class I potential peptides. YRIMLSVHG, VLIFLSTAV and MMLELDPPF, GLDFSDLYY are the most potent peptides predicted as epitopes for CD4⁺ and CD8⁺ T cells, respectively, whereas MMLELDPPF and GLDFSDLYY had the highest pMHC-I immunogenicity score and these are further tested for interaction against the HLA molecules, using in silico docking techniques to verify the binding cleft epitope. However, this is an introductory approach to design an epitope-based peptide vaccine against ZikV; we hope that this model will be helpful in designing and predicting novel vaccine candidates.

Therapeutics Insight with Inclusive Immunopharmacology Explication of Human Rotavirus A for the Treatment of Diarrhea

Rotavirus is the most common cause of severe infant and childhood diarrhea worldwide, and the morbidity and mortality rate is going to be outnumbered in developing countries like Bangladesh. To mitigate this substantial burden of disease, new therapeutics such as vaccine and drug are swiftly required against rotavirus. The present therapeutics insight study was performed with comprehensive immunoinformatics and pharmacoinformatics approach. T and B-cell epitopes were assessed in the conserved region of outer capsid protein VP4 among the highly reviewed strains from different countries including Bangladesh. The results suggest that epitope SU1 (TLKNLNDNY) could be an ideal candidate among the predicted five epitopes for both T and B-cell epitopes for the development of universal vaccine against rotavirus. This research also suggests five novel drug compounds from medicinal plant Rhizophora mucronata Lamk. for better therapeutics strategies against rotavirus diarrhea based on 3D structure building, pharmacophore, ADMET, and QSAR properties. The exact mode of action between drug compounds and target protein VP4 were revealed by molecular docking analysis. Drug likeness and oral bioavailability further confirmed the effectiveness of the proposed drugs against rotavirus diarrhea. This study might be implemented for experimental validation to facilitate the novel vaccine and drug design.

Identification of Conserved Peptides Comprising Multiple T Cell Epitopes of Matrix 1 Protein in H1N1 Influenza Virus

Cell mediated immune response plays a key role in combating viral infection and thus identification of new vaccine targets manifesting T cell mediated response may serve as an ideal approach for influenza vaccine. The present study involves the application of an immunoinformatics-based consensus approach for epitope prediction (three epitope prediction tools each for CD4+ and CD8+ T cell epitopes) and molecular docking to identify peptide sequences containing T cell epitopes using the conserved sequences from all the Matrix 1 protein sequences of H1N1 virus available until April 2015. Three peptides comprising CD4+ and CD8+ T cell epitopes were obtained, which were not exactly reported in earlier studies. Population coverage study of these multi-epitope peptides revealed that they are capable of inducing a potent immune response belonging to individuals from different populations and ethnicity distributed around the globe. Conservation study with other subtypes of influenza virus infecting humans (H2N2, H5N1, H7N9, and H3N2) revealed that these three peptides were conserved (>90%), with 100% identity in most of these strains. Hence, these peptides can impart immunity against H1N1 as well as other subtypes of influenza virus. A molecular docking study of the predicted peptides with class I and II human leukocyte antigen (HLA) molecules has shown that the majority of them have comparable binding energies to that of native peptides. Hence, these peptides from Matrix 1 protein of H1N1 appear to be promising candidates for universal vaccine design.

Highly conserved regions in Ebola virus RNA dependent RNA polymerase may be act as a universal novel peptide vaccine target: a computational approach

Purpose

Ebola virus (EBOV) is such kind of virus which is responsible for 23,825 cases and 9675 deaths worldwide only in 2014 and with an average diseases fatality rate between 25 % and 90 %. Although, medical technology has tried to handle the problems, there is no Food and Drug Administration (FDA)-approved therapeutics or vaccines available for the prevention, post exposure, or treatment of Ebola virus disease (EVD).

Methods

In the present study, we used the immunoinformatics approach to design a potential epitope-based vaccine against the RNA-dependent RNA polymerase-L of EBOV. BioEdit v7.2.3 sequence alignment editor, Jalview v2 and CLC Sequence Viewer v7.0.2 were used for the initial sequence analysis for securing the conservancy from the sequences. Later the Immune Epitope Database and Analysis Resource (IEDB-AR) was used for the identification of T-cell and B-cellepitopes associated with type I and II major histocompatibility complex molecules analysis. Finally, the population coverage analysis was employed.

Results

The core epitope “FRYEFTAPF” was found to be the most potential one, with 100 % conservancy among all the strains of EBOV. It also interacted with both type I and II major histocompatibility complex molecules and is considered as nonallergenic in nature. Finally, with impressive cumulative population coverage of 99.87 % for the both MHC-I and MHC-II class throughout the world population was found for the proposed epitope.

Conclusion

To end, the projected peptide gave us a solid stand to propose for vaccine consideration and that might be experimented for its potency in eliciting immunity through humoral and cell mediated immune responses in vitro and in vivo.

Electronic supplementary material

The online version of this article (doi:10.1186/s40203-015-0011-4) contains supplementary material, which is available to authorized users.

Identification of highly conserved regions in L-segment of Crimean-Congo hemorrhagic fever virus and immunoinformatic prediction about potential novel vaccine

Crimean-Congo hemorrhagic fever (CCHF) is a tick-borne zoonotic viral disease with a disease fatality rate between 15% and 70%. Despite the wide range of distribution, the virus (CCHFV) is basically endemic in Africa, Asia, eastern Europe, and the Middle East. Acute febrile illness associated with petechiae, disseminated intravascular coagulation, and multiple-organ failure are the main symptoms of the disease. With all these fatal effects, CCHFV is considered a huge threat as no successful therapeutic approach is currently available for the treatment of this disease. In the present study, we have used the immunoinformatics approach to design a potential epitope-based vaccine against the RNA-dependent RNA polymerase-L of CCHFV. Both the T-cell and B-cell epitopes were assessed, and the epitope "DCSSTPPDR" was found to be the most potential one, with 100% conservancy among all the strains of CCHFV. The epitope was also found to interact with both type I and II major histocompatibility complex molecules and is considered nonallergenic as well. In vivo study of our proposed peptide is advised for novel universal vaccine production, which might be an effective path to prevent CCHF disease.

Design of an epitope-based peptide vaccine against spike protein of human coronavirus: an in silico approach

Human coronavirus (HCoV), a member of Coronaviridae family, is the causative agent of upper respiratory tract infections and “atypical pneumonia”. Despite severe epidemic outbreaks on several occasions and lack of antiviral drug, not much progress has been made with regard to an epitope-based vaccine designed for HCoV. In this study, a computational approach was adopted to identify a multiepitope vaccine candidate against this virus that could be suitable to trigger a significant immune response. Sequences of the spike proteins were collected from a protein database and analyzed with an in silico tool, to identify the most immunogenic protein. Both T cell immunity and B cell immunity were checked for the peptides to ensure that they had the capacity to induce both humoral and cell-mediated immunity. The peptide sequence from 88–94 amino acids and the sequence KSSTGFVYF were found as the most potential B cell and T cell epitopes, respectively. Furthermore, conservancy analysis was also done using in silico tools and showed a conservancy of 64.29% for all epitopes. The peptide sequence could interact with as many as 16 human leukocyte antigens (HLAs) and showed high cumulative population coverage, ranging from 75.68% to 90.73%. The epitope was further tested for binding against the HLA molecules, using in silico docking techniques, to verify the binding cleft epitope interaction. The allergenicity of the epitopes was also evaluated. This computational study of design of an epitope-based peptide vaccine against HCoVs allows us to determine novel peptide antigen targets in spike proteins on intuitive grounds, albeit the preliminary results thereof require validation by in vitro and in vivo experiments.