Predicting population coverage of T-cell epitope-based diagnostics and vaccines

Prediction and analyses of HLA-II restricted Mycobacterium tuberculosis CD4+ T cell epitopes in the Chinese population

The Bacillus Calmette-Guérin (BCG) vaccine has been used to prevent tuberculosis (TB), but it cannot prevent adults against TB. The Mycobacterium tuberculosis Beijing strain is the most popular strain in China, but no vaccine is designed for the Beijing strain. It is vital to design a multiepitopes-based vaccine against the Beijing strain for the Chinese population. The bioinformatics tools were used to predict CD4+ T-cell epitopes in five protective antigens based on the Chinese population-specific alleles. The antigenicity, allergenicity, toxicity, IFN-γ level, population coverage, and three-dimensional structure were predicted using Vaxijen, AllerTOP, ToxinPred, IFN-γ epitope server, IEDB, and I-TASSER, respectively. One-hundred one promiscuous epitopes were obtained from Rv1813c, Rv2608, Rv3131, and Rv3628 proteins. After screening with antigenicity, allergenicity, toxicity, and IFN-γ level, seven epitopes from Rv2608 and Rv3131 proteins were selected to be vaccine candidates. Further study determined their three-dimensional structure and the coverage in the Chinese population as high as 99%. Our study predicted seven CD4+ T-cell dominant epitopes from the proteins Rv2608 and Rv3131 of M. tuberculosis Beijing strain for the first time, which may provide a basis for improving the design of multiepitopes-based vaccines for TB.

T cell and antibody kinetics delineate SARS-CoV-2 peptides mediating long-term immune responses in COVID-19 convalescent individuals

Long-term immunological memory to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is crucial for the development of population-level immunity, which is the aim of vaccination approaches. Reports on rapidly decreasing antibody titers have led to questions regarding the efficacy of humoral immunity alone. The relevance of T cell memory after coronavirus disease 2019 (COVID-19) remains unclear. Here, we investigated SARS-CoV-2 antibody and T cell responses in matched samples of COVID-19 convalescent individuals up to 6 months after infection. Longitudinal analysis revealed decreasing and stable spike- and nucleocapsid-specific antibody responses, respectively. In contrast, functional T cell responses remained robust, and even increased, in both frequency and intensity. Single peptide mapping of T cell diversity over time identified open reading frame-independent, dominant T cell epitopes mediating long-term SARS-CoV-2 T cell responses. Identification of these epitopes may be fundamental for COVID-19 vaccine design.

Prediction of Epitope based Peptides for Vaccine Development from Complete Proteome of Novel Corona Virus (SARS-COV-2) Using Immunoinformatics

COVID-19 is an infectious disease caused by a newly discovered corona virus SARS-COV-2. It is the most dangerous epidemic existing currently all over the world. To date, there is no licensed vaccine and not any particular efficient therapeutic agent available to prevent or cure the disease. So development of an effective vaccine is the urgent need of the time. The proposed study aims to identify potential vaccine candidates by screening the complete proteome of SARS-COV-2 using the computational approach. From 14 protein entries in UniProtKB, 4 proteins were screened for epitope prediction based on consensus antigenicity predictions and various physico-chemical criteria like transmembrane domain, allergenicity, GRAVY value, toxicity, stability index. Comprehensive analysis of these 4 antigens revealed that spike protein (P0DTC2) and nucleoprotein (P0DTC9) show the greatest potential for experimental immunogenicity analysis. These 2 proteins have several potential CD4+ and CD8+ T-cell epitopes, as well as high probability of B-cell epitope regions as compared to well-characterized antigen the matrix protein 1 [Influenza A virus (H5N1)]. In addition, the epitope SIIAYTMSL predicted from spike protein (P0DTC2) and epitope SPRWYFYYL predicted from nucleoprotein (P0DTC9) exhibited more than 60% population coverage in the target populations Europe, North America, South Asia, Northeast Asia taken in this study. These epitopes have also been found to exhibit highly significant TCR–pMHC interactions having a joint Z value of 4.51 and 4.37 respectively. Therefore, this analysis suggests that the predicted epitopes might be suitable vaccine candidates and should be subjected to further in-vivo and in-vitro studies.

Assessment of the population coverage of an HIV-1 vaccine targeting sequences surrounding the viral protease cleavage sites in Gag, Pol, or all 12 protease cleavage sites

Development of an effective HIV-1 vaccine has been a great challenge faced by the research community. Recently a novel strategy targeting the viral protease cleavage sites (PCSs) has been tested and shown promising results. This T cell-based vaccine strategy depends on individuals expressing certain HLA class I molecules and since each population has unique distributions of HLA class I alleles, population coverage analysis is required to assess feasibility. Utilizing the validated CD8 T cell epitope data from previous studies we conducted coverage analysis of an HIV-1 vaccine targeting the sequences surrounding all 12-PCSs, Gag-PCSs, and Pol-PCSs. The population coverage, average epitope hit, and minimum number of epitopes recognized by 90% of the population (PC90) was compiled for 66 countries and 16 geographical regions using the web tool provided by "Immune Epitope Database and Analysis Resource". Our analysis shows that the coverage for an HIV-1 vaccine targeting sequences surrounding all 12 PCSs, 5 PCSs in Gag or 6 PCSs in Pol can cover ~ 70% to ~ 100% of the populations analyzed. There was no statistical difference in population coverages for the majority of populations examined when comparing the CD8 T cell epitope sets (12-PCSs, Gag-PCSs, and Pol-PCSs). As expected, vaccines targeting more sequences will have more CD8 T cell epitopes, as the mean average epitope hit for the 12-PCSs, Gag-PCSs, and Pol-PCSs across all countries studied was 9.45, 4.76, and 4.74, respectively, and across all geographical regions was 9.76, 4.99, and 4.92, respectively. The average PC90 for the 12-PCSs, Gag-PCSs, and Pol-PCSs across all countries studied was 2.53, 1.31, and 1.41, respectively, and across all geographical regions was 2.24, 1.23, and 1.29, respectively. Thus, vaccines targeting sequences surrounding the HIV-1 PCSs can cover broad populations; however, whether targeting a subset of the PCSs is sufficient to prevent acquisition requires further preclinical investigation.

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

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

Cytotoxic T-lymphocyte elicited therapeutic vaccine candidate targeting cancer against MAGE-A11 carcinogenic protein

Immunotherapy is a breakthrough approach for cancer treatment and prevention. By exploiting the fact that cancer cells have overexpression of tumor antigens responsible for its growth and progression, which can be identified and removed by boosting the immune system. In silico techniques have provided efficient ways for developing preventive measures to ward off cancer. Herein, we have designed a potent cytotoxic T-lymphocyte epitope to elicit a desirable immune response against carcinogenic melanoma-associated antigen-A11. Potent epitope was predicted using reliable algorithms and characterized by advanced computational avenue CABS molecular dynamics simulation, for full flexible binding with HLA-A*0201 and androgen receptor to large-scale rearrangements of the complex system. Results showed the potent immunogenic construct (KIIDLVHLL), from top epitopes using five algorithms. Molecular docking analyses showed the strong binding of epitope with HLA-A*0201 and androgen receptor with docking score of -780.6 and -641.06 kcal/mol, respectively. Molecular dynamics simulation analysis revealed strong binding of lead epitope with androgen receptor by involvement of 127 elements through atomic-model study. Full flexibility study showed stable binding of epitope with an average root mean square deviation (RMSD) 2.21 Å and maximum RMSD value of 6.48 Å in optimal cluster density area. The epitope also showed remarkable results with radius of gyration 23.0777 Å, world population coverage of 39.08% by immune epitope database, and transporter associated with antigen processing (TAP) affinity IC50 value of 2039.65 nm. Moreover, in silico cloning approach confirmed the expression and translation capacity of the construct within a suitable expression vector. The present study paves way for a potential immunogenic construct for prevention of cancer.

Epitope-based universal vaccine for Human T-lymphotropic virus-1 (HTLV-1)

Human T-cell leukemia virus type 1 (HTLV-1) was the first oncogenic human retrovirus identified in humans which infects at least 10-15 million people worldwide. Large HTLV-1 endemic areas exist in Southern Japan, the Caribbean, Central and South America, the Middle East, Melanesia, and equatorial regions of Africa. HTLV-1 TAX viral protein is thought to play a critical role in HTLV-1 associated diseases. We have used numerous bio-informatics and immuno-informatics implements comprising sequence and construction tools for the construction of a 3D model and epitope prediction for HTLV-1 Tax viral protein. The conformational linear B-cell and T-cell epitopes for HTLV-1 TAX viral protein have been predicted for their possible collective use as vaccine candidates. Based on in silico investigation two B cell epitopes, KEADDNDHEPQISPGGLEPPSEKHFR and DGTPMISGPCPKDGQPS spanning from 324-349 and 252-268 respectively; and T cell epitopes, LLFGYPVYV, ITWPLLPHV and GLLPFHSTL ranging from 11-19, 163-171 and 233-241 were found most antigenic and immunogenic epitopes. Among different vaccine constructs generated by different combinations of these epitopes our predicted vaccine construct was found to be most antigenic with a score of 0.57. T cell epitopes interacted strongly with HLA-A*0201 suggesting a significant immune response evoked by these epitopes. Molecular docking study also showed a high binding affinity of the vaccine construct for TLR4. The study was carried out to predict antigenic determinants of the Tax protein along with the 3D protein modeling. The study revealed a potential multi epitope vaccine that can raise the desired immune response against HTLV-1 and be useful in developing effective vaccines against Human T-lymphotropic virus.

Identification of promiscuous T cell epitopes on Mayaro virus structural proteins using immunoinformatics, molecular modeling, and QM:MM approaches

The Mayaro virus (MAYV) belongs to genus Alphavirus (family Togaviridae) and has been reported in several countries, especially in tropical regions of America. Due to its outbreaks and potential lack of medication, an effective vaccine formulation is strongly required. This study aimed to predict promiscuous T cell epitopes from structural polyproteins of MAYV using an immunoinformatics approach. For this purpose, consensus sequences were used to identify short protein sequences capable of binding to MHC class I and class II alleles. Our analysis pointed out 4 MHC-I/TCD8+ and 21 MHC-II/TCD4+ epitopes on capside (1;3), E1 (2;5), E2 (1;10), E3 (0;2), and 6 K (0;1) proteins. These predicted epitopes were characterized by high antigenicity, immunogenicity, conservancy, non-allergenic, non-toxic, and good population coverage rate values for North and South American geographical areas. Afterwards, we used the crystal structure of human toll-like receptor 3 (TLR3) ectodomain as a template to predict, through docking essays, the placement of a vaccine prototype at the TLR3 receptor binding site. Finally, classical and quantum mechanics/molecular mechanics (QM:MM) computations were employed to improve the quality of docking calculations, with the QM part of the simulations being accomplished by using the density functional theory (DFT) formalism. These results provide important insights into the advancement of diagnostic platforms, the development of vaccines, and immunotherapeutic interventions.

Design of an epitope-based peptide vaccine against the SARS-CoV-2: a vaccine-informatics approach

The recurrent and recent global outbreak of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has turned into a global concern which has infected more than 42 million people all over the globe, and this number is increasing in hours. Unfortunately, no vaccine or specific treatment is available, which makes it more deadly. A vaccine-informatics approach has shown significant breakthrough in peptide-based epitope mapping and opens the new horizon in vaccine development. In this study, we have identified a total of 15 antigenic peptides [including thymus cells (T-cells) and bone marrow or bursa-derived cells] in the surface glycoprotein (SG) of SARS-CoV-2 which is nontoxic and nonallergenic in nature, nonallergenic, highly antigenic and non-mutated in other SARS-CoV-2 virus strains. The population coverage analysis has found that cluster of differentiation 4 (CD4+) T-cell peptides showed higher cumulative population coverage over cluster of differentiation 8 (CD8+) peptides in the 16 different geographical regions of the world. We identified 12 peptides ((LTDEMIAQY, WTAGAAAYY, WMESEFRVY, IRASANLAA, FGAISSVLN, VKQLSSNFG, FAMQMAYRF, FGAGAALQI, YGFQPTNGVGYQ, LPDPSKPSKR, QTQTNSPRRARS and VITPGTNTSN) that are $80\hbox{--} 90\%$ identical with experimentally determined epitopes of SARS-CoV, and this will likely be beneficial for a quick progression of the vaccine design. Moreover, docking analysis suggested that the identified peptides are tightly bound in the groove of human leukocyte antigen molecules which can induce the T-cell response. Overall, this study allows us to determine potent peptide antigen targets in the SG on intuitive grounds, which opens up a new horizon in the coronavirus disease (COVID-19) research. However, this study needs experimental validation by in vitro and in vivo.

Prediction of putative epitope-based vaccine against all corona virus strains for the Chinese population: Approach toward development of vaccine

Currently, the whole world is facing the coronavirus disease-19 pandemic. As of now, approximately 0.15 million people around the globe are infected with the novel coronavirus. In the last decade, two strains of the coronavirus family, severe acute respiratory syndrome-related coronavirus and Middle East respiratory syndrome coronavirus, also resulted in epidemics in south Asian and the Middle Eastern countries with high mortality rate. This scenario demands the development of a putative vaccine which may provide immunity against all current and new evolving coronavirus strains. In this study, we designed an epitope-based vaccine using an immunoinformatic approach. This vaccine may protect against all coronavirus strains. The vaccine is developed by considering the geographical distribution of coronavirus strains and host genetics (Chinese population). Nine experimentally validated epitopes sequences from coronavirus strains were used to derive the variants considering the conservancy in all strains. Further, the binding affinities of all derived variants were checked with most abundant human leukocyte antigen alleles in the Chinese population. Three major histocompatibility complex (MHC) Class I epitopes from spike glycoprotein and nucleoprotein showed sufficient binding while one MHC Class II epitope from spike glycoprotein was found to be an effective binder. A cocktail of these epitopes gave more than 95% population coverage in the Chinese population. Moreover, molecular dynamics simulation supported the aforementioned predictions. Further, in vivo studies are needed to confirm the immunogenic potential of these vaccines.

Vaccinomics approach for scheming potential epitope-based peptide vaccine by targeting l-protein of Marburg virus

Marburg virus is one of the world’s most threatening diseases, causing extreme hemorrhagic fever, with a death rate of up to 90%. The Food and Drug Administration (FDA) currently not authorized any treatments or vaccinations for the hindrance and post-exposure of the Marburg virus. In the present study, the vaccinomics methodology was adopted to design a potential novel peptide vaccine against the Marburg virus, targeting RNA-directed RNA polymerase (l). A total of 48 l-proteins from diverse variants of the Marburg virus were collected from the NCBI GenBank server and used to classify the best antigenic protein leading to predict equally T and B-cell epitopes. Initially, the top 26 epitopes were evaluated for the attraction with major histocompatibility complex (MHC) class I and II alleles. Finally, four prospective central epitopes NLSDLTFLI, FRYEFTRHF, YRLRNSTAL, and YRVRNVQTL were carefully chosen. Among these, FRYEFTRHF and YRVRNVQTL peptides showed 100% conservancy. Though YRLRNSTAL showed 95.74% conservancy, it demonstrated the highest combined score as T cell epitope (2.5461) and population coverage of 94.42% among the whole world population. The epitope was found non-allergenic, and docking interactions with human leukocyte antigens (HLAs) also verified. Finally, in vivo analysis of the recommended peptides might contribute to the advancement of an efficient and exclusively prevalent vaccine that would be an active route to impede the virus spreading.

Population-Predicted MHC Class II Epitope Presentation of SARS-CoV-2 Structural Proteins Correlates to the Case Fatality Rates of COVID-19 in Different Countries

We observed substantial differences in predicted Major Histocompatibility Complex II (MHCII) epitope presentation of SARS-CoV-2 proteins for different populations but only minor differences in predicted MHCI epitope presentation. A comparison of this predicted epitope MHC-coverage revealed for the early phase of infection spread (till day 15 after reaching 128 observed infection cases) highly significant negative correlations with the case fatality rate. Specifically, this was observed in different populations for MHC class II presentation of the viral spike protein (p-value: 0.0733 for linear regression), the envelope protein (p-value: 0.023), and the membrane protein (p-value: 0.00053), indicating that the high case fatality rates of COVID-19 observed in some countries seem to be related with poor MHC class II presentation and hence weak adaptive immune response against these viral envelope proteins. Our results highlight the general importance of the SARS-CoV-2 structural proteins in immunological control in early infection spread looking at a global census in various countries and taking case fatality rate into account. Other factors such as health system and control measures become more important after the early spread. Our study should encourage further studies on MHCII alleles as potential risk factors in COVID-19 including assessment of local populations and specific allele distributions.

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

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

Implementation of in silico methods to predict common epitopes for vaccine development against Chikungunya and Mayaro viruses

Being a Positive sense RNA virus the recent reemergence of Chikungunya and Mayaro virus has taken the concern of the leading scientific communities of the world. Though the outbreak of Mayaro virus is limited to Neotropical region only, Chikungunya is already identified in over 60 countries around the world. Besides, the lack of a strong protective treatment, misdiagnosis issue and co-circulation of both the viruses calls for a new strategy which could potentially prevent these infections from spreading. In this study, we therefore, identified the peptide based vaccine candidates e.g. epitopes for B cell and T cell from Chikungunya virus which also showed to be homologous to the Mayaro virus through immuno-informatics and computational approaches. Final epitopes identified from the most antigenic structural polyprotein of both the viruses were 5 for CD8+ T cell Epitopes (209KPGDSGRPI217, 219TGTMGHFIL227, 239ALSVVTWNK247, 98KPGRRERMC106 and 100GRRERMCMK108), 2 epitopes for CD4+ T cell (105MCMKIENDCIFEVKH119 and 502DRTLLSQQSGNVKIT516) and a single epitope for B cell (504GGRFTIPTGAGKPGDSGRPI518). Analysis of our predicted epitopes for population coverage showed prominent population coverage (92.43%) around the world. Finally, molecular docking simulation of the foreseen T cell epitopes with respondent HLA alleles secured good HLA-epitope interaction. This study was directed towards the discovery of potential antigenic epitopes which can open up a new skyline to design novel vaccines for combating both of the diseases at the same time.

A Proteome-Wide Immunoinformatics Tool to Accelerate T-Cell Epitope Discovery and Vaccine Design in the Context of Emerging Infectious Diseases: An Ethnicity-Oriented Approach

Emerging infectious diseases (EIDs) caused by viruses are increasing in frequency, causing a high disease burden and mortality world-wide. The COVID-19 pandemic caused by the novel SARS-like coronavirus (SARS-CoV-2) underscores the need to innovate and accelerate the development of effective vaccination strategies against EIDs. Human leukocyte antigen (HLA) molecules play a central role in the immune system by determining the peptide repertoire displayed to the T-cell compartment. Genetic polymorphisms of the HLA system thus confer a strong variability in vaccine-induced immune responses and may complicate the selection of vaccine candidates, because the distribution and frequencies of HLA alleles are highly variable among different ethnic groups. Herein, we build on the emerging paradigm of rational epitope-based vaccine design, by describing an immunoinformatics tool (Predivac-3.0) for proteome-wide T-cell epitope discovery that accounts for ethnic-level variations in immune responsiveness. Predivac-3.0 implements both CD8+ and CD4+ T-cell epitope predictions based on HLA allele frequencies retrieved from the Allele Frequency Net Database. The tool was thoroughly assessed, proving comparable performances (AUC ~0.9) against four state-of-the-art pan-specific immunoinformatics methods capable of population-level analysis (NetMHCPan-4.0, Pickpocket, PSSMHCPan and SMM), as well as a strong accuracy on proteome-wide T-cell epitope predictions for HIV-specific immune responses in the Japanese population. The utility of the method was investigated for the COVID-19 pandemic, by performing in silico T-cell epitope mapping of the SARS-CoV-2 spike glycoprotein according to the ethnic context of the countries where the ChAdOx1 vaccine is currently initiating phase III clinical trials. Potentially immunodominant CD8+ and CD4+ T-cell epitopes and population coverages were predicted for each population (the Epitope Discovery mode), along with optimized sets of broadly recognized (promiscuous) T-cell epitopes maximizing coverage in the target populations (the Epitope Optimization mode). Population-specific epitope-rich regions (T-cell epitope clusters) were further predicted in protein antigens based on combined criteria of epitope density and population coverage. Overall, we conclude that Predivac-3.0 holds potential to contribute in the understanding of ethnic-level variations of vaccine-induced immune responsiveness and to guide the development of epitope-based next-generation vaccines against emerging pathogens, whose geographic distributions and populations in need of vaccinations are often well-defined for regional epidemics.

Identification of SARS-CoV-2 Nucleocapsid and Spike T-Cell Epitopes for Assessing T-Cell Immunity

Developing optimal T-cell response assays to severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) is critical for measuring the duration of immunity to this disease and assessing the efficacy of vaccine candidates. These assays need to target conserved regions of SARS-CoV-2 global variants and avoid cross-reactivity to seasonal human coronaviruses. To contribute to this effort, we employed an in silico immunoinformatics analysis pipeline to identify immunogenic peptides resulting from conserved and highly networked regions with topological importance from the SARS-CoV-2 nucleocapsid and spike proteins. A total of 57 highly networked T-cell epitopes that are conserved across geographic viral variants were identified from these viral proteins, with a binding potential to diverse HLA alleles and 80 to 100% global population coverage. Importantly, 18 of these T-cell epitope derived peptides had limited homology to seasonal human coronaviruses making them promising candidates for SARS-CoV-2-specific T-cell immunity assays. Moreover, two of the NC-derived peptides elicited effector/polyfunctional responses of CD8+ T cells derived from SARS-CoV-2 convalescent patients.IMPORTANCE The development of specific and validated immunologic tools is critical for understanding the level and duration of the cellular response induced by SARS-CoV-2 infection and/or vaccines against this novel coronavirus disease. To contribute to this effort, we employed an immunoinformatics analysis pipeline to define 57 SARS-CoV-2 immunogenic peptides within topologically important regions of the nucleocapsid (NC) and spike (S) proteins that will be effective for detecting cellular immune responses in 80 to 100% of the global population. Our immunoinformatics analysis revealed that 18 of these peptides had limited homology to circulating seasonal human coronaviruses and therefore are promising candidates for distinguishing SARS-CoV-2-specific immune responses from pre-existing coronavirus immunity. Importantly, CD8+ T cells derived from SARS-CoV-2 survivors exhibited polyfunctional effector responses to two novel NC-derived peptides identified as HLA-binders. These studies provide a proof of concept that our immunoinformatics analysis pipeline identifies novel immunogens which can elicit polyfunctional SARS-CoV-2-specific T-cell responses.

An integrative docking and simulation-based approach towards the development of epitope-based vaccine against enterotoxigenic Escherichia coli

Enterotoxigenic E.coli is causing diarrheal illness in children as well as adults with the majority of the cases occurring in developing countries. To reduce the number of cases occurring worldwide, the development of an effectual vaccine against these bacteria can be the only prevention. This conjectural work was performed using modern bioinformatics tools for investigation of proteome of ETEC strain E24377A. Different computational vaccinology approaches were deployed to assess several parameters including antigenicity, allergenicity, stability, localization, molecular weight and toxicity of the predicted epitopes required for good vaccine candidate to elicit immune response against diarrhea. We estimated two known control antigens, epitope ¹⁴¹STLPETTVV¹⁴⁹ of Hepatitis B virus and epitope ²⁶⁵ILRGSVAHK²⁷³ of H1N1 Nucleoprotein in an attempt to corroborate our research work. Furthermore molecular docking was performed to evaluate the interaction between HLA allele and peptide, the peptide QYGGGNSAL and peptide LPYFELRWL were considered to be the most promiscuous T cell epitopes with the highest binding energy value of −2.09 kcal/mol and −1.84 kcal/mol, respectively. In addition, dynamic simulation revealed good stability of the vaccine construct as well as population coverage analysis exhibits the highest population coverage in the regions of East Asia, India, Northeast Asia, South Asia and North America. Therefore, these two epitopes can be further synthesized for wet lab analysis and could be considered as a promising vaccine against diarrhea.

An immunoprophylactic evaluation of Ld-ODC derived HLA-A0201 restricted peptides against visceral leishmaniasis

Five (5) HLA-A 0201 restricted epitopes of ornithine decarboxylase derived from Leishmania donovani (Ld-ODC) were examined by reverse vaccinology to develop prophylactics against visceral leishmaniasis (VL). These consensus epitopes comprising (P1: RLMPSAHAI, P2: LLDQYQIHL, P3: GLYHSFNCI, P4: AVLEVLSAL and P5: RLPASPAAL) were observed and presented by diverse HLA alleles screened by immune-informatics tools. These epitopes were also observed for strong stability for appropriate immune response in in silico screening and molecular dynamics. Top five selected epitopes filtered from population coverage analysis and TAP binding affinity were identified and evaluated against treated cases of VL subjects. Experiments were run individually with synthetic peptides or as the cocktail of peptides. A major population of CD8+ T cells were predominantly IFN-γ producers but not the IL-10 cytokines and shown with granzyme-B activity. Therefore, it can be concluded that the screened HLA-A0201 restricted epitope hotspots derived from Leishmania ODC can trigger CD8+ T cells, which can skew other immune cells functions toward protection. However, a detailed analysis can explore its potentiality as a vaccine candidate.Communicated by Ramaswamy H. Sarma.

A computational study to disclose potential drugs and vaccine ensemble for COVID-19 conundrum

The nucleocapsid (N) protein of SARS-COV-2, a virus responsible for the current COVID-19 pandemic, is considered a potential candidate for the design of new drugs and vaccines. The protein is central to several critical events in virus production, with its highly druggable nature and rich antigenic determinants making it an excellent anti-viral biomolecule. Docking-based virtual screening using the Asinex anti-viral library identified binding of drug molecules at three specific positions: loop 1 region, loop 2 region and β-sheet core pockets, the loop 2 region being the most common binding and stable site for the bulk of the molecules. In parallel, the protein was characterized by vaccine design perspective and harboured three potential B cell-derived T cell epitopes: PINTNSSPD, GVPINTNSS, and DHIGTRNPA. The epitopes are highly antigenic, virulent, non-allergic, non-toxic, bind with good affinity to the highly prevalent DRB*0101 allele and show an average population coverage of 95.04%. A multi-epitope vaccine ensemble which was 83 amino acids long was created. This was highly immunogenic, robust in generating both humoral and cellular immune responses, thermally stable, and had good physicochemical properties that could be easily analyzed in in vivo and in vitro studies. Conformational dynamics of both drug and vaccine ensemble with respect to the receptors are energetically stable, shedding light on favourable conformation and chemical interactions. These facts were validated by subjecting the complexes to relative and absolute binding free energy methods of MMGB/PBSA and WaterSwap. A strong agreement on the system stability was disclosed that supported ligand high affinity potential for the receptors. Collectively, this work sought to provide preliminary experimental data of existing anti-viral drugs as a possible therapy for COVID-19 infections and a new peptide-based vaccine for protection against this pandemic virus.

The Peptide Vaccine of the Future

The approach of peptide-based anticancer vaccination has proven the ability to induce cancer-specific immune responses in multiple studies for various cancer entities. However, clinical responses remain so far limited to single patients and broad clinical applicability was not achieved. Therefore, further efforts are required to improve peptide vaccination in order to integrate this low-side-effect therapy into the clinical routine of cancer therapy. To design clinically effective peptide vaccines in the future, different issues have to be addressed and optimized comprising antigen target selection as well as choice of optimal adjuvants and vaccination schedules. Furthermore, the combination of peptide-based vaccines with other immuno- and molecular targeted therapies as well as the development of predictive biomarkers could further improve efficacy. In this review, current approaches in the development of peptide-based vaccines and critical implications for optimal vaccine design are discussed.

An in silico deep learning approach to multi-epitope vaccine design: a SARS-CoV-2 case study

The rampant spread of COVID-19, an infectious disease caused by SARS-CoV-2, all over the world has led to over millions of deaths, and devastated the social, financial and political entities around the world. Without an existing effective medical therapy, vaccines are urgently needed to avoid the spread of this disease. In this study, we propose an in silico deep learning approach for prediction and design of a multi-epitope vaccine (DeepVacPred). By combining the in silico immunoinformatics and deep neural network strategies, the DeepVacPred computational framework directly predicts 26 potential vaccine subunits from the available SARS-CoV-2 spike protein sequence. We further use in silico methods to investigate the linear B-cell epitopes, Cytotoxic T Lymphocytes (CTL) epitopes, Helper T Lymphocytes (HTL) epitopes in the 26 subunit candidates and identify the best 11 of them to construct a multi-epitope vaccine for SARS-CoV-2 virus. The human population coverage, antigenicity, allergenicity, toxicity, physicochemical properties and secondary structure of the designed vaccine are evaluated via state-of-the-art bioinformatic approaches, showing good quality of the designed vaccine. The 3D structure of the designed vaccine is predicted, refined and validated by in silico tools. Finally, we optimize and insert the codon sequence into a plasmid to ensure the cloning and expression efficiency. In conclusion, this proposed artificial intelligence (AI) based vaccine discovery framework accelerates the vaccine design process and constructs a 694aa multi-epitope vaccine containing 16 B-cell epitopes, 82 CTL epitopes and 89 HTL epitopes, which is promising to fight the SARS-CoV-2 viral infection and can be further evaluated in clinical studies. Moreover, we trace the RNA mutations of the SARS-CoV-2 and ensure that the designed vaccine can tackle the recent RNA mutations of the virus.

Comprehensive analysis of T cell immunodominance and immunoprevalence of SARS-CoV-2 epitopes in COVID-19 cases

T cells are involved in control of SARS-CoV-2 infection. To establish the patterns of immunodominance of different SARS-CoV-2 antigens and precisely measure virus-specific CD4⁺ and CD8⁺ T cells, we study epitope-specific T cell responses of 99 convalescent coronavirus disease 2019 (COVID-19) cases. The SARS-CoV-2 proteome is probed using 1,925 peptides spanning the entire genome, ensuring an unbiased coverage of human leukocyte antigen (HLA) alleles for class II responses. For HLA class I, we study an additional 5,600 predicted binding epitopes for 28 prominent HLA class I alleles, accounting for wide global coverage. We identify several hundred HLA-restricted SARS-CoV-2-derived epitopes. Distinct patterns of immunodominance are observed, which differ for CD4⁺ T cells, CD8⁺ T cells, and antibodies. The class I and class II epitopes are combined into epitope megapools to facilitate identification and quantification of SARS-CoV-2-specific CD4⁺ and CD8⁺ T cells.

Immunoinformatics approach for a novel multi-epitope subunit vaccine design against various subtypes of Influenza A virus

Vaccination is the best strategy for the control and prevention of contagious diseases caused by Influenza A viruses. Extraordinary genetic variability and continual evolvability are responsible for the virus having survival and adaptation to host cell immune response, thus rendering the current influenza vaccines with suboptimal effectiveness.Therefore, in the present study, using a novel immunoinformatics approach, we have designed a universal influenza subunit vaccine based on the highly conserved epitopic sequences of rapidly evolving (HA), a moderately evolving (NP) and slow evolving (M1) proteins of the virus. The vaccine design includes 2 peptide adjuvants, 26 CTL epitopes, 9 HTL epitopes, and 7 linear BCL epitopes to induce innate, cellular, and humoral immune responses against Influenza A viruses. We also analyzed the physicochemical properties of the designed construct to validate its thermodynamic stability, hydrophilicity, PI, antigenicity, and allergenicity. Furthermore, we predicted a highly stable tertiary model of the designed subunit vaccine, wherein additional disulfide bonds were incorporated to enhance its stability. The molecular docking and molecular dynamics simulations of the refined vaccine model with TLR3, TLR7, TLR8, MHC-I and MHC-II showed stable vaccine and receptors complexes, thus confirming the immunogenicity of the designed vaccine. Collectively, these findings suggest that our multi-epitope vaccine construct may confer protection against various strains of influenza A virus subtypes, which could prevent the need for annual reformulation of vaccine and alleviate disease burden.

Mining of Ebola virus genome for the construction of multi-epitope vaccine to combat its infection

Ebola virus is the primary causative agent of viral hemorrhagic fever that is an epidemic disease and responsible for the massive premature deaths in humans. Despite knowing the molecular mechanism of its pathogenesis, to date, no commercial or FDA approved multiepitope vaccine is available against Ebola infection. The current study focuses on designing a multi-epitope subunit vaccine for Ebola using a novel immunoinformatic approach. The best predicted antigenic epitopes of Cytotoxic-T cell (CTL), Helper-T cells (HTL), and B-cell epitopes (BCL) joined by various linkers were selected for the multi-epitope vaccine designing. For the enhanced immune response, two adjuvants were also added to the construct. Further analysis showed the vaccine to be immunogenic and non-allergenic, forming a stable and energetically favorable structure. The stability of the unbound vaccine construct and vaccine/TLR4 was elucidated via atomistic molecular dynamics simulations. The binding free energy analysis (ΔG_Bind = -194.2 ± 0.5 kcal/mol) via the molecular mechanics Poisson-Boltzmann docking scheme revealed a strong association and thus can initiate the maximal immune response. Next, for the optimal expression of the vaccine construct, its gene construct was cloned in the pET28a + vector system. In summary, the Ebola viral proteome was screened to identify the most potential HTLs, CTLs, and BCL epitopes. Along with various linkers and adjuvants, a multi-epitope vaccine is constructed that showed a high binding affinity with the immune receptor, TLR4. Thus, the current study provides a highly immunogenic multi-epitope subunit vaccine construct that may induce humoral and cellular immune responses against the Ebola infection.Communicated by Ramaswamy H. Sarma.

Immunoinformatics prediction of overlapping CD8+ T-cell, IFN-γ and IL-4 inducer CD4+ T-cell and linear B-cell epitopes based vaccines against COVID-19 (SARS-CoV-2)

At the beginning of the year 2020, the world was struck with a global pandemic virus referred to as SARS-CoV-2 (COVID-19) which has left hundreds of thousands of people dead. To control this virus, vaccine design becomes imperative. In this study, potential epitopes-based vaccine candidates were explored. Six hundred (600) genomes of SARS-CoV-2 were retrieved from the viPR database to generate CD8⁺ T-cell, CD4+ T-cell and linear B-cell epitopes which were screened for antigenicity, immunogenicity and non-allergenicity. The results of this study provide 19 promising candidate CD8⁺ T-cell epitopes that strongly overlap with 8 promising B-cells epitopes. Another 19 CD4⁺ T-cell epitopes were also identified that can induce IFN-γ and IL-4 cytokines. The most conserved MHC-I and MHC-II for both CD8⁺ and CD4⁺ T-cell epitopes are HLA-A*02:06 and HLA-DRB1*01:01 respectively. These epitopes also bound to Toll-like receptor 3 (TLR3). The population coverage of the conserved Major Histocompatibility Complex Human Leukocyte Antigen (HLA) for both CD8⁺ T-cell and CD4⁺ T-cell ranged from 65.6% to 100%. The detailed analysis of the potential epitope-based vaccine and their mapping to the complete COVID-19 genome reveals that they are predominantly found in the location of the surface (S) and membrane (M) glycoproteins suggesting the potential involvement of these structural proteins in the immunogenic response and antigenicity of the virus. Since the majority of the potential epitopes are located on M protein, the design of multi-epitope vaccine with the structural protein is highly promising though the whole M protein could also serve as a viable epitope for the development of an attenuated vaccine. Our findings provide a baseline for the experimental design of a suitable vaccine against SARS-CoV-2.

Immuno-informatics approach for B-cell and T-cell epitope based peptide vaccine design against novel COVID-19 virus

COVID-19 has brought the world to a standstill with a wave of destruction in country after country with tremendous loss of lives and livelihood in advanced to developing nations. Whole world is staring at the prospect of repeated lockdowns with another wave of COVID-19 predicted to hit the world in September of 2020. The second wave is assumed to be even more destructive with severe impact across much of the world. The only way to defeat this pandemic is to quickly develop a safe and effective vaccine against this raging menace and initiate a global vaccination drive. Our study is an attempt to deploy various computational methods to identify B-cell and T-cell epitopes from the spike surface glycoprotein of SARS-COV-2 which have the novel potential for vaccine development against COVID-19. For this we have taken 8 unique strains with one each from India, China, France, USA, Italy, Australia, Iran and Pakistan. The strain data was extracted from NCBI Database. By analyzing the immune parameters like surface accessibility, antigenicity, variability, conservancy, flexibility, hydrophilicity, allergenicity and toxicity of the conserved sequences of spike glycoprotein using various databases and bioinformatics tools, we identified two potential novel linear (SGTNGTKRFDN and ASVYAWNRK) and one structural B-cell epitope as well as two T-cell epitopes (RLFRKSNLK and IPTNFTISV) which can be used as epitope-based peptide vaccines. Docking simulation assay revealed that above T-cell epitopes have minimum free binding energy and showed strong hydrogen bond interaction which strengthened its potential as being a T-cell epitope for the epitope-based novel vaccine against SARS-CoV-2. This study allows us to claim that B-cell and T-cell epitopes mentioned above provide potential pathways for developing an exploratory vaccine against spike surface glycoprotein of SARS-CoV-2 with high confidence for the identified strains. We will need to confirm our findings with biological assays.

Immunoinformatics designed T cell multi epitope dengue peptide vaccine derived from non structural proteome

Dengue viral disease has been reported as an Aedes aegypti mosquito-borne human disease and causing a severe global public health concern. In this study, immunoinformatics methods was deployed for crafting CTL T-cell epitopes as dengue vaccine candidates. The NS1 protein sequence of dengue serotype 1 strain retrieved from the protein database and T-cell epitopes (n = 85) were predicted by the artificial neural network. The conserved epitopes (n = 10) were predicted and selected for intensive computational analysis. The machine learning technique and quantitative matrix-based toxicity analysis assured nontoxic peptide selection. Hidden Markov Model derived Structural Alphabet (SA) based algorithm predicted the 3D molecular structure and all-atom structure of peptide ligand validated by Ramachandran-plot. Three-tier molecular docking approaches were used to predictthe peptide - HLA docking complex. Molecular dynamics (MD) simulation study confirmed the docking complex was stable in the time frame of 100ns. Population coverage analysis predicted the interaction epitope interaction with a particular population of HLA. These results concluded that the computationally designed HTLWSNGVL and FTTNIWLKL epitope peptides could be used as putative agents for the multi CTL T cell epitope vaccine. The vaccine protein sequence expression and translation were analyzed in the prokaryotic vector adapted by codon usage. Such in silico formulated CTL T-cell-based prophylactic vaccines could encourage the commercial development of dengue vaccines.

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.

Class I HLA Allele Predicted Restricted Antigenic Coverages for Spike and Nucleocapsid Proteins Are Associated With Deaths Related to COVID-19

The world is dealing with one of the worst pandemics ever. SARS-CoV-2 is the etiological agent of COVID-19 that has already spread to more than 200 countries. However, infectivity, severity, and mortality rates do not affect all countries equally. Here we consider 140 HLA alleles and extensively investigate the landscape of 3,723 potential HLA-I A and B restricted SARS-CoV-2-derived antigens and how 37 countries in the world are predicted to respond to those peptides considering their HLA-I distribution frequencies. The clustering of HLA-A and HLA-B allele frequencies partially separates most countries with the lowest number of deaths per million inhabitants from the other countries. We further correlated the patterns of in silico predicted population coverage and epidemiological data. The number of deaths per million inhabitants correlates to the predicted antigen coverage of S and N derived peptides and its module is influenced if a given set of frequent or rare HLA alleles are analyzed in a given population. Moreover, we highlighted a potential risk group carrying HLAs associated with an elevated number of deaths per million inhabitants. In addition, we identified three potential antigens bearing at least one amino acid of the four-length insertion that differentiates SARS-CoV-2 from previous coronavirus strains. We believe these data can contribute to the search for peptides with the potential to be used in vaccine strategies considering the role of herd immunity to hamper the spread of the disease. Importantly, to the best of our knowledge, this work is the first to use a populational approach in association with COVID-19 outcome.

Comprehensive analysis of T cell immunodominance and immunoprevalence of SARS-CoV-2 epitopes in COVID-19 cases

T cells are involved in control of SARS-CoV-2 infection. To establish the patterns of immunodominance of different SARS-CoV-2 antigens, and precisely measure virus-specific CD4 ⁺ and CD8 ⁺ T cells, we studied epitope-specific T cell responses of approximately 100 convalescent COVID-19 cases. The SARS-CoV-2 proteome was probed using 1,925 peptides spanning the entire genome, ensuring an unbiased coverage of HLA alleles for class II responses. For HLA class I, we studied an additional 5,600 predicted binding epitopes for 28 prominent HLA class I alleles, accounting for wide global coverage. We identified several hundred HLA-restricted SARS-CoV-2-derived epitopes. Distinct patterns of immunodominance were observed, which differed for CD4 ⁺ T cells, CD8 ⁺ T cells, and antibodies. The class I and class II epitopes were combined into new epitope megapools to facilitate identification and quantification of SARS-CoV-2-specific CD4 ⁺ and CD8 ⁺ T cells.

Sub-genomic analysis of Chikungunya virus E2 mutations in Pakistani isolates potentially modulating B-cell & T-Cell immune response

Background & Objectives:

The Chikungunya virus (CHIKV) transmitted to the humans through Aedes species of the mosquitoes. In December 2016, a severe outbreak reported from Pakistan. However, there is no vaccine or anti-viral treatment currently available so host immune response against CHIKV gained significant interest. Therefore, this study was conducted to identify the mutations in CHIKV E2 region of currently circulating Pakistani strains & determine their potential immunogenicity in Pakistani population.

Methods:

It was a cross sectional study in which a total of 60 CHIKV PCR positive samples were collected from Molecular Department of Pathology, Dow University of Health Sciences (DUHS), Karachi during November 2017 to February 2018. CHIKV E2 gene was amplified by PCR & sequenced. Sequences were analyzed by using bioinformatic tools followed by epitope prediction in E2 sequences by In-silico immunoinformatic approach.

Results:

Several single nucleotide variations (SNVs) were identified in Pakistani isolates with six novel mutations in E2 sequences. Immunoinformatic analyses showed more proteasomal sites, CTL & B-Cell epitopes in Pakistani strains with respect to S27 prototype with 69.4% population coverage against these epitopes in Pakistan. The study also identified key mutations responsible for generation of unique epitopes and HLA restriction in Pakistani isolates. The strain specific mutations revealed the current outbreak was caused by ESCA.IOL lineage of CHIKV.

Conclusion:

The evolution of E2 protein in Pakistani strains has increased its immunogenicity in comparison to ancestral s27 strain. The identification of most immunogenic and conserved epitopes with high population coverage has high potential to be used in vaccine development against these local strains.

A conserved multi-epitope-based vaccine designed by targeting hemagglutinin protein of highly pathogenic avian H5 influenza viruses

The highly pathogenic avian H5N1 influenza viruses have been recognized as a potential pandemic threat to humans, and to the poultry industry since 1997. H5 viruses consist of a high mutation rate, so universal vaccine designing is very challenging. Here, we describe a vaccinomics approach to design a novel multi-epitope influenza vaccine, based on the highly conserved regions of surface glycoprotein, Hemagglutinin (HA). Initially, the HA protein sequences from Bangladeshi origin were retrieved and aligned by ClustalW. The sequences of 100% conserved regions extracted and analyzed to select the highest potential T-cell and B-cell epitope. The HTL and CTL analyses using IEDB tools showed that DVWTYNAELLVLMEN possesses the highest affinity with MHC class I and II alleles, and it has the highest population coverage. The docking simulation study suggests that this epitope has the potential to interact with both MHC class I and MHC class II. The B-cell epitope prediction provides a potential peptide, GAIAGFIEGGWQGM. We further retrieved HA sequences of 3950 avian and 250 human H5 isolates from several populations of the world, where H5 was an epidemic. Surprisingly, these epitopes are more than 98% conserved in those regions which indicate their potentiality as a conserved vaccine. We have proposed a multi-epitope vaccine using these sequences and assess its stability and potentiality to induce B-cell immunity. In vivo study is necessary to corroborate this epitope as a vaccine, however, setting forth groundwork for wet-lab studies essential to mitigate pandemic threats and provide cross-protection of both avian and humans against H5 influenza viruses.

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

In the present study, one of the targets present on the envelopes of coronaviruses, membrane glycoprotein (M) was chosen for the design of a multi-epitope vaccine by Immunoinformatics approach. The B-cell and T-cell epitopes used for the construction of vaccine were antigenic, nonallergic and nontoxic. An adjuvant, β-defensin and PADRE sequence were included at the N-terminal end of the vaccine. All the epitopes were joined by linkers for decreasing the junctional immunogenicity. Various physicochemical parameters of the vaccine were evaluated. Secondary and tertiary structures were predicted for the vaccine construct. The tertiary structure was further refined, and various parameters related to the refinement of the protein structure were validated by using different tools. Humoral immunity induced by B-cells relies upon the identification of antigenic determinants on the surface of the vaccine construct. In this regard, the vaccine construct was found to consist of several B-cell epitopes in its three-dimensional conformation. Molecular docking of the vaccine was carried out with TLR-3 receptor to study their binding and its strength. Further, protein-protein interactions in the docked complex were visualized using LigPlot+. Population coverage analysis had shown that the multi-epitope vaccine covers 94.06% of the global population. The vaccine construct was successfully cloned in silico into pET-28a (+). Immune simulation studies showed the induction of primary, secondary and tertiary immune responses marked by the increased levels of antibodies, INF-γ, IL-2, TGF-β, B- cells, CD4+ and CD8+ cells. Finally, the vaccine construct was able to elicit immune response as desired.Communicated by Ramaswamy H. Sarma.

An Immunoinformatics Study to Predict Epitopes in the Envelope Protein of SARS-CoV-2

COVID-19 is a new viral emergent disease caused by a novel strain of coronavirus. This virus has caused a huge problem in the world as millions of people are affected by this disease. We aimed at designing a peptide vaccine for COVID-19 particularly for the envelope protein using computational methods to predict epitopes inducing the immune system. The envelope protein sequence of SARS-CoV-2 has been retrieved from the NCBI database. The bioinformatics analysis was carried out by using the Immune Epitope Database (IEDB) to predict B- and T-cell epitopes. The predicted HTL and CTL epitopes were docked with HLA alleles and binding energies were evaluated. The allergenicity of predicted epitopes was analyzed, the conservancy analysis was performed, and the population coverage was determined throughout the world. Some overlapped CTL, HTL, and B-cell epitopes were suggested to become a universal candidate for peptide-based vaccine against COVID-19. This vaccine peptide could simultaneously elicit humoral and cell-mediated immune responses. We hope to confirm our findings by adding complementary steps of both in vitro and in vivo studies to support this new universal predicted candidate.

Design of Epitope-Based Peptide Vaccine against Pseudomonas aeruginosa Fructose Bisphosphate Aldolase Protein Using Immunoinformatics

Pseudomonas aeruginosa is a common pathogen that is responsible for serious hospital-acquired infections, ventilator-associated pneumonia, and various sepsis syndromes. Also, it is a multidrug-resistant pathogen recognized for its ubiquity and its intrinsically advanced antibiotic-resistant mechanisms. It usually affects immunocompromised individuals but can also infect immunocompetent individuals. There is no vaccine against it available till now. This study predicts an effective epitope-based vaccine against fructose bisphosphate aldolase (FBA) of Pseudomonas aeruginosa using immunoinformatics tools. The protein sequences were obtained from NCBI, and prediction tests were undertaken to analyze possible epitopes for B and T cells. Three B cell epitopes passed the antigenicity, accessibility, and hydrophilicity tests. Six MHC I epitopes were found to be promising, while four MHC II epitopes were found promising from the result set. Nineteen epitopes were shared between MHC I and II results. For the population coverage, the epitopes covered 95.62% worldwide excluding certain MHC II alleles. We recommend in vivo and in vitro studies to prove its effectiveness.

Designing a novel mRNA vaccine against SARS-CoV-2: An immunoinformatics approach

SARS-CoV-2 is the deadly virus behind COVID-19, the disease that went on to ravage the world and caused the biggest pandemic 21st century has witnessed so far. On the face of ongoing death and destruction, the urgent need for the discovery of a vaccine against the virus is paramount. This study resorted to the emerging discipline of immunoinformatics in order to design a multi-epitope mRNA vaccine against the spike glycoprotein of SARS-CoV-2. Various immunoinformatics tools were utilized to predict T and B lymphocyte epitopes. The epitopes were channeled through a filtering pipeline comprised of antigenicity, toxicity, allergenicity, and cytokine inducibility evaluation with the goal of selecting epitopes capable of generating both T and B cell-mediated immune responses. Molecular docking simulation between the epitopes and their corresponding MHC molecules was carried out. 13 epitopes, a highly immunogenic adjuvant, elements for proper sub-cellular trafficking, a secretion booster, and appropriate linkers were combined for constructing the vaccine. The vaccine was found to be antigenic, almost neutral at physiological pH, non-toxic, non-allergenic, capable of generating a robust immune response and had a decent worldwide population coverage. Based on these parameters, this design can be considered a promising choice for a vaccine against SARS-CoV-2.

Vaccine design based on 16 epitopes of SARS-CoV-2 spike protein

The global outbreak of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) urgently requires an effective vaccine for prevention. In this study, 66 epitopes containing pentapeptides of SARS‐CoV‐2 spike protein in the IEDB database were compared with the amino acid sequence of SARS‐CoV‐2 spike protein, and 66 potentially immune‐related peptides of SARS‐CoV‐2 spike protein were obtained. Based on the single‐nucleotide polymorphisms analysis of spike protein of 1218 SARS‐CoV‐2 isolates, 52 easily mutated sites were identified and used for vaccine epitope screening. The best vaccine candidate epitopes in the 66 peptides of SARS‐CoV‐2 spike protein were screened out through mutation and immunoinformatics analysis. The best candidate epitopes were connected by different linkers in silico to obtain vaccine candidate sequences. The results showed that 16 epitopes were relatively conservative, immunological, nontoxic, and nonallergenic, could induce the secretion of cytokines, and were more likely to be exposed on the surface of the spike protein. They were both B‐ and T‐cell epitopes, and could recognize a certain number of HLA molecules and had high coverage rates in different populations. Moreover, epitopes 897‐913 were predicted to have possible cross‐immunoprotection for SARS‐CoV and SARS‐CoV‐2. The results of vaccine candidate sequences screening suggested that sequences (without linker, with linker GGGSGGG, EAAAK, GPGPG, and KK, respectively) were the best. The proteins translated by these sequences were relatively stable, with a high antigenic index and good biological activity. Our study provided vaccine candidate epitopes and sequences for the research of the SARS‐CoV‐2 vaccine.

Epitope prediction and identification- adaptive T cell responses in humans

Epitopes, in the context of T cell recognition, are short peptides typically derived by antigen processing, and presented on the cell surface bound to MHC molecules (HLA molecules in humans) for TCR scrutiny. The identification of epitopes is a context-dependent process, with consideration given to, for example, the source pathogen and protein, the host organism, and state of the immune reaction (e.g., following natural infection, vaccination, etc.). In the following review, we consider the various approaches used to define T cell epitopes, including both bioinformatic and experimental approaches, and discuss the concepts of immunodominance and immunoprevalence. We also discuss HLA polymorphism and epitope restriction, and the resulting impact on the identification of, and potential population coverage afforded by, epitopes or epitope-based vaccines. Finally, some examples of the practical application of T cell epitope identification are provided, showing how epitopes have been valuable for deriving novel immunological insights in the context of the immune response to various pathogens and allergens.

Proteomic Exploration of Listeria monocytogenes for the Purpose of Vaccine Designing Using a Reverse Vaccinology Approach

Listeriosis is a major foodborne infection provoked by a bacterium known as Listeria monocytogenes. It is one of the predominant causes of death in pregnant women, infants, and immunocompromised persons. Despite such fatal effects, until now there is no proper medication or drug available for such a serious foodborne infection. One of the most promising ways to deal with this challenge is vaccination. This present study aims at the prediction of B cell epitopes for subunit vaccine designing against Listeria monocytogenes using a reverse vaccinology approach. Among screened out 299 epitopes of strain F2365 of Listeria monocytogenes, based on the VaxiJen score, the top 20 epitopes were selected. 3D modeling of epitopes and alleles was generated by PEPstrMOD and Swiss Model respectively. Molecular docking reveals 4 epitopes viz., MKFLFPLKL, CEETFGIRL, FLKIDPPIL, and VRHHGGGHK based on binding energy. All 4 epitopes were investigated for non-toxicity, binding affinity, and population coverage. After vigorous investigation, epitope FLKIDPPIL was anticipated as the best vaccine contender. The stability of the FLKIDPPIL-HLA DRB1 _0101 complex was proved by performing the simulation. Here, predicted peptide through the Insilico approach may become a potential remedy against listeriosis, after the wet-lab approach and clinical trials.

Potential Cross-Reactive Immunity to SARS-CoV-2 From Common Human Pathogens and Vaccines

The recently emerged SARS-CoV-2 causing the ongoing COVID-19 pandemic is particularly virulent in the elderly while children are largely spared. Here, we explored the potential role of cross-reactive immunity acquired from pediatric vaccinations and exposure to common human pathogens in the protection and pathology of COVID-19. To that end, we sought for peptide matches to SARS-CoV-2 (identity ≥ 80%, in at least eight residues) in the proteomes of 25 human pathogens and in vaccine antigens, and subsequently predicted their T and B cell reactivity to identify potential cross-reactive epitopes. We found that viruses subject to pediatric vaccinations do not contain cross-reactive epitopes with SARS-CoV-2, precluding that they can provide any general protection against COVID-19. Likewise, common viruses including rhinovirus, respiratory syncytial virus, influenza virus, and several herpesviruses are also poor or null sources of cross-reactive immunity to SARS-CoV-2, discarding that immunological memory against these viruses can have any general protective or pathological role in COVID-19. In contrast, we found combination vaccines for treating diphtheria, tetanus, and pertussis infectious diseases (DTP vaccine) to be significant sources of potential cross-reactive immunity to SARS-CoV-2. DTP cross-reactive epitopes with SARS-CoV-2 include numerous CD8 and CD4 T cell epitopes with broad population protection coverage and potentially neutralizing B cell epitopes in SARS-CoV-2 Spike protein. Worldwide, children receive several DTP vaccinations, including three-four doses the first year of life and one at 4-6 years of age. Moreover, a low antigenic Tdap dose is also given at ages 9-14. Thereby, children may well be protected from SARS-CoV-2 through cross-reactive immunity elicited by DTP vaccinations, supporting testing in the general population to prevent COVID-19.

Design of novel multiepitope constructs-based peptide vaccine against the structural S, N and M proteins of human COVID-19 using immunoinformatics analysis

The causative agent of severe acute respiratory syndrome (SARS) reported by the Chinese Center for Disease Control (China CDC) has been identified as a novel Betacoronavirus (SARS-CoV-2). A computational approach was adopted to identify multiepitope vaccine candidates against SARS-CoV-2 based on S, N and M proteins being able to elicit both humoral and cellular immune responses. In this study, the sequence of the virus was obtained from NCBI database and analyzed with in silico tools such as NetMHCpan, IEDB, BepiPred, NetCTL, Tap transport/proteasomal cleavage, Pa3P, GalexyPepDock, I-TASSER, Ellipro and ClusPro. To identify the most immunodominant regions, after analysis of population coverage and epitope conservancy, we proposed three different constructs based on linear B-cell, CTL and HTL epitopes. The 3D structure of constructs was assessed to find discontinuous B-cell epitopes. Among CTL predicted epitopes, S257-265, S603-611 and S360-368, and among HTL predicted epitopes, N167-181, S313-330 and S1110-1126 had better MHC binding rank. We found one putative CTL epitope, S360-368 related to receptor-binding domain (RBD) region for S protein. The predicted epitopes were non-allergen and showed a high quality of proteasomal cleavage and Tap transport efficiency and 100% conservancy within four different clades of SARS-CoV-2. For CTL and HTL epitopes, the highest population coverage of the world's population was calculated for S27-37 with 86.27% and for S196-231, S303-323, S313-330, S1009-1030 and N328-349 with 90.33%, respectively. We identified overall 10 discontinuous B-cell epitopes for three multiepitope constructs. All three constructs showed strong interactions with TLRs 2, 3 and 4 supporting the hypothesis of SARS-CoV-2 susceptibility to TLRs 2, 3 and 4 like other Coronaviridae families. These data demonstrated that the novel designed multiepitope constructs can contribute to develop SARS-CoV-2 peptide vaccine candidates. The in vivo studies are underway using several vaccination strategies.

Designing a multi-epitope peptide based vaccine against SARS-CoV-2

COVID-19 pandemic has resulted in 16,114,449 cases with 646,641 deaths from the 217 countries, or territories as on July 27th 2020. Due to multifaceted issues and challenges in the implementation of the safety and preventive measures, inconsistent coordination between societies-governments and most importantly lack of specific vaccine to SARS-CoV-2, the spread of the virus that initially emerged at Wuhan is still uprising after taking a heavy toll on human life. In the present study, we mapped immunogenic epitopes present on the four structural proteins of SARS-CoV-2 and we designed a multi-epitope peptide based vaccine that, demonstrated a high immunogenic response with a vast application on world’s human population. On codon optimization and in-silico cloning, we found that candidate vaccine showed high expression in E. coli and immune simulation resulted in inducing a high level of both B-cell and T-cell mediated immunity. The results predicted that exposure of vaccine by administrating three injections significantly subsidized the antigen growth in the system. The proposed candidate vaccine found promising by yielding desired results and hence, should be validated by practical experimentations for its functioning and efficacy to neutralize SARS-CoV-2.

SARS-CoV-2-derived peptides define heterologous and COVID-19-induced T cell recognition

T cell immunity is central for the control of viral infections. To characterize T cell immunity, but also for the development of vaccines, identification of exact viral T cell epitopes is fundamental. Here we identify and characterize multiple dominant and subdominant SARS-CoV-2 HLA class I and HLA-DR peptides as potential T cell epitopes in COVID-19 convalescent and unexposed individuals. SARS-CoV-2-specific peptides enabled detection of post-infectious T cell immunity, even in seronegative convalescent individuals. Cross-reactive SARS-CoV-2 peptides revealed pre-existing T cell responses in 81% of unexposed individuals and validated similarity with common cold coronaviruses, providing a functional basis for heterologous immunity in SARS-CoV-2 infection. Diversity of SARS-CoV-2 T cell responses was associated with mild symptoms of COVID-19, providing evidence that immunity requires recognition of multiple epitopes. Together, the proposed SARS-CoV-2 T cell epitopes enable identification of heterologous and post-infectious T cell immunity and facilitate development of diagnostic, preventive and therapeutic measures for COVID-19.

Genome-Wide Asymptomatic B-Cell, CD4 + and CD8 + T-Cell Epitopes, that are Highly Conserved Between Human and Animal Coronaviruses, Identified from SARS-CoV-2 as Immune Targets for Pre-Emptive Pan-Coronavirus Vaccines

Over the last two decades, there have been three deadly human outbreaks of Coronaviruses (CoVs) caused by emerging zoonotic CoVs: SARS-CoV, MERS-CoV, and the latest highly transmissible and deadly SARS-CoV-2, which has caused the current COVID-19 global pandemic. All three deadly CoVs originated from bats, the natural hosts, and transmitted to humans via various intermediate animal reservoirs. Because there is currently no universal pan-Coronavirus vaccine available, two worst-case scenarios remain highly possible: (1) SARS-CoV-2 mutates and transforms into a seasonal "flu-like" global pandemic; and/or (2) Other global COVID-like pandemics will emerge in the coming years, caused by yet another spillover of an unknown zoonotic bat-derived SARS-like Coronavirus (SL-CoV) into an unvaccinated human population. Determining the antigen and epitope landscapes that are conserved among human and animal Coronaviruses as well as the repertoire, phenotype and function of B cells and CD4 ⁺ and CD8 ⁺ T cells that correlate with resistance seen in asymptomatic COVID-19 patients should inform in the development of pan-Coronavirus vaccines ¹ . In the present study, using several immuno-informatics and sequence alignment approaches, we identified several human B-cell, CD4 ⁺ and CD8 ⁺ T cell epitopes that are highly conserved in: ( i ) greater than 81,000 SARS-CoV-2 human strains identified to date in 190 countries on six continents; ( ii ) six circulating CoVs that caused previous human outbreaks of the "Common Cold"; ( iii ) five SL-CoVs isolated from bats; ( iv ) five SL-CoV isolated from pangolins; ( v ) three SL-CoVs isolated from Civet Cats; and ( vi ) four MERS strains isolated from camels. Furthermore, we identified cross-reactive asymptomatic epitopes that: ( i ) recalled B cell, CD4 ⁺ and CD8 ⁺ T cell responses from both asymptomatic COVID-19 patients and healthy individuals who were never exposed to SARS-CoV-2; and ( ii ) induced strong B cell and T cell responses in "humanized" Human Leukocyte Antigen (HLA)-DR/HLA-A*02:01 double transgenic mice. The findings herein pave the way to develop a pre-emptive multi-epitope pan-Coronavirus vaccine to protect against past, current, and potential future outbreaks.

Designing an efficient multi-epitope vaccine displaying interactions with diverse HLA molecules for an efficient humoral and cellular immune response to prevent COVID-19 infection

Background

The novel SARS-CoV-2 coronavirus, the causative agent of the ongoing pandemic COVID-19 disease continues to infect people globally and has infected millions of humans worldwide. However, no effective vaccine against this virus exists.

Method

Using Immunoinformatics, epitopic sequences from multiple glycoproteins that play crucial role in pathogenesis were identified. Particularly, epitopes were mapped from conserved receptor-binding domain of spike protein which have been experimentally validated in SARS-CoV-1 as a promising target for vaccine development.

Results

A multi-epitopic vaccine construct comprising of B-cell, CTL, HTL epitopes was developed along with fusion of adjuvant and linkers. The epitopes identified herein are reported for the first time and were predicted to be highly antigenic, stable, nonallergen, nontoxic and displayed conservation across several SARS-CoV-2 isolates from different countries. Additionally, the epitopes associated with maximum HLA alleles and population coverage analysis shows the proposed epitopes would be a relevant representative of large proportion of the world population. A reliable three-dimensional structure of the vaccine construct was developed. Consequently, docking and molecular-dynamics simulation ensured the stable interaction between vaccine and innate-immune receptor.

Immuno-Informatics Quest against COVID-19/SARS-COV-2: Determining Putative T-Cell Epitopes for Vaccine Prediction

BACKGROUND

Since, December 2019 a novel coronavirus, SARS-CoV-2 has caused global public health issue after being reported for the first time in Wuhan province of China. So far, there have been approximately 14.8 million confirmed cases and 0.614 million deaths due to the SARS-CoV-2 infection globally, and still numbers are increasing. Although, the virus has caused a global public health concern, no effective treatment has been developed.

OBJECTIVE

One of the strategies to combat the COVID-19 disease caused by SARS-CoV-2 is development of vaccines that can make humans immune to these infections. Considering this approach, in this study an attempt has been made to design epitope based vaccine for combatting COVID-19 disease by analyzing the complete proteome of the virus by using immuno-informatics tools.

METHODS

The protein sequence of the SARS-CoV-2 was retrieved and the individual proteins were checked for their allergic potential. Then, from non-allergen proteins antigenic epitopes were identified that could bind with MHCII molecules. The epitopes were modeled and docked to predict the interaction with MHCII molecules. The stability of the epitopeMHCII complex was further analyzed by performing molecular dynamic simulation study. The selected vaccine candidates were also analyzed for their global population coverage and conservancy among SARS related coronavirus species.

RESULTS

The study has predicted 5 peptide molecules that can act as potential candidate for epitope based vaccine development. Among the 5 selected epitopes, the peptide LRARSVSPK can be the most potent epitope because of its high geometric shape complementarity score, low ACE and very high response to it by the world population (81.81% global population coverage). Further, molecular dynamic simulation analysis indicated the formation of stable epitope-MHCII complex. The epitope LRARSVSPK was also found to be highly conserved among the SARS-CoV-2 isolated from different countries.

CONCLUSION

The study has predicted T-cell epitopes that can elicit robust immune response in global human population and act as potential vaccine candidates. However, the ability of these epitopes to act as vaccine candidate needs to be validated in wet lab studies.

Reverse vaccinology assisted designing of multiepitope-based subunit vaccine against SARS-CoV-2

BACKGROUND

Coronavirus disease 2019 (COVID-19) linked with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cause severe illness and life-threatening pneumonia in humans. The current COVID-19 pandemic demands an effective vaccine to acquire protection against the infection. Therefore, the present study was aimed to design a multiepitope-based subunit vaccine (MESV) against COVID-19.

METHODS

Structural proteins (Surface glycoprotein, Envelope protein, and Membrane glycoprotein) of SARS-CoV-2 are responsible for its prime functions. Sequences of proteins were downloaded from GenBank and several immunoinformatics coupled with computational approaches were employed to forecast B- and T- cell epitopes from the SARS-CoV-2 highly antigenic structural proteins to design an effective MESV.

RESULTS

Predicted epitopes suggested high antigenicity, conserveness, substantial interactions with the human leukocyte antigen (HLA) binding alleles, and collective global population coverage of 88.40%. Taken together, 276 amino acids long MESV was designed by connecting 3 cytotoxic T lymphocytes (CTL), 6 helper T lymphocyte (HTL) and 4 B-cell epitopes with suitable adjuvant and linkers. The MESV construct was non-allergenic, stable, and highly antigenic. Molecular docking showed a stable and high binding affinity of MESV with human pathogenic toll-like receptors-3 (TLR3). Furthermore, in silico immune simulation revealed significant immunogenic response of MESV. Finally, MEV codons were optimized for its in silico cloning into the Escherichia coli K-12 system, to ensure its increased expression.

CONCLUSION

The MESV developed in this study is capable of generating immune response against COVID-19. Therefore, if designed MESV further investigated experimentally, it would be an effective vaccine candidate against SARS-CoV-2 to control and prevent COVID-19.

SARS-CoV-2 transcriptome analysis and molecular cataloguing of immunodominant epitopes for multi-epitope based vaccine design

Genomics-led researches are engaged in tracing virus expression pattern, and induced immune responses in human to develop effective vaccine against COVID-19. In this study, targeted expression profiling and differential gene expression analysis of major histocompatibility complexes and innate immune system genes were performed through SARS-CoV-2 infected RNA-seq data of human cell line, and virus transcriptome was generated for T-and B-cell epitope prediction. Docking studies of epitopes with MHC and B-cell receptors were performed to identify potential T-and B-cell epitopes. Transcriptome analysis revealed the specific multiple allele expressions in cell line, genes for elicited induce immune response, and virus gene expression. Proposed T- and B-cell epitopes have high potential to elicit equivalent immune responses caused by SARS-CoV-2 infection which can be useful to provide links between elicited immune response and virus gene expression. This study will facilitate in vitro and in vivo vaccine related research studies in disease control.

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SARS-CoV-2 transcriptome construction from RNA-seq data of infected human cell-lines.

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T- and B-cell epitopes from SARS-CoV-2 transcriptome

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Gene expression profiling of MHC alleles and innate immune system genes