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

Designing of an innovative conserved multiepitope subunit vaccine targeting SARS-CoV-2 glycoprotein and nucleoprotein through immunoinformatic

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has imposed substantial challenges on our society due to the COVID-19 pandemic. This virus relies heavily on its surface glycoprotein (S-glycoprotein) to facilitate attachment, fusion, and entry into host cells. While the nucleoprotein (N) in the ribonucleoprotein core binds to the viral RNA genome. Therefore, our objective is to develop a novel vaccine candidate targeting the dominant T-cell and B-cell epitopes of the immune system. On the S-glycoprotein and nucleoprotein. Employing an immunoinformatic approach, we constructed a vaccine candidate with 13 highly antigenic B-cell epitopes, 19 HTL antigenic epitopes, and 18 CTL epitopes following a rigorous assessment. The multi-epitope construct successfully passed three-fold toxicity, allergenicity, and antigenicity tests, affirming its non-toxic, non-allergenic, and antigenic nature. This demonstrates the potentiality of the vaccine design to trigger an immunological response. Furthermore, the vaccine-ACE-2 receptor complex was tested, confirming its ability to interact with ACE-2's core pocket and induce an immunological response. Additionally, the vaccine's binding prowess for human toll-like receptors (TLR) (1, 3, 4, and 8) was investigated. According to the Ramachandran plot, 77.46% of the construct's amino acid residues fall within a favorable zone, establishing it as a viable vaccine candidate.

Non-RBD peptides of SARS-CoV-2 spike protein exhibit immunodominance as they elicit both innate and adaptive immune responses

Severe acute respiratory coronavirus-2 (SARS-CoV-2) emerged in 2019 as a new virus and caused worldwide outbreaks, quickly turning into a pandemic disease called coronavirus disease-19 (COVID-19). All the existing methodologies were used for developing vaccines for this virus. But sporadic infections of this virus and the emergence of new strains to date suggest the incomplete protection offered by the developed vaccines and the need for new research. In this direction, we identified five epitopes present in the non-RBD region and on the surface of the spike protein by in silico analysis. They are epitope I (aa 80-90), epitope II (aa 262-270), and a small protein with three epitopes (aa 1059-1124). Antigenicity scores of these epitopes were found to be higher than the full length spike protein and its RBD region. These epitopes showed high conserveness across the emerging strains, high immunogenicity, non-toxicity, no homology with human sequences and high affinity for MHC class I & II molecules. Antibodies raised against these epitopes interacted with the bacterially expressed spike protein in western blotting. The antiserum of COVID-19 recovered participants reacted with the developed epitopes (small protein). Furthermore, in the presence of the respective antiserum and COVID-19 convalescent serum, these epitopes successfully fixed the complement, implying a possible role in innate immunity. The epitopes were also found to activate the peripheral blood mononuclear cells (PBMCs) isolated from the blood samples of COVID-19 recovered/vaccinated participants, suggesting a possible role in adaptive immunity. The need for the new SARS-CoV-2 vaccines is further highlighted in light of current reports about the side effects of a developed vaccine (AstraZeneca) and the circulating new strains. The epitopes presented in this study represent the potential immunogens and expect certain pitfalls of the existing vaccines would be sealed.

Insights into structural vaccinology harnessed for universal coronavirus vaccine development

Structural vaccinology is pivotal in expediting vaccine design through high-throughput screening of immunogenic antigens. Leveraging the structural and functional characteristics of antigens and immune cell receptors, this approach employs protein structural comparison to identify conserved patterns in key pathogenic components. Molecular modeling techniques, including homology modeling and molecular docking, analyze specific three-dimensional (3D) structures and protein interactions and offer valuable insights into the 3D interactions and binding affinity between vaccine candidates and target proteins. In this review, we delve into the utilization of various immunoinformatics and molecular modeling tools to streamline the development of broad-protective vaccines against coronavirus disease 2019 variants. Structural vaccinology significantly enhances our understanding of molecular interactions between hosts and pathogens. By accelerating the pace of developing effective and targeted vaccines, particularly against the rapidly mutating severe acute respiratory syndrome coronavirus 2 and other prevalent infectious diseases, this approach stands at the forefront of advancing immunization strategies. The combination of computational techniques and structural insights not only facilitates the identification of potential vaccine candidates but also contributes to the rational design of vaccines, fostering a more efficient and targeted approach to combatting infectious diseases.

Plausible Influence of HLA Class I and Class II Diversity on SARS-CoV-2 Vulnerability

Severe acute respiratory syndrome CoV-2 (SARS-CoV-2) caused the global coronavirus disease 2019 (COVID-19) pandemic, which adversely affected almost all aspects of human life and resulted in the loss of millions of lives, while affecting nearly 0.67 billion people worldwide. SARS-CoV-2 still poses a challenge to the healthcare system as there are more than 200,000 active cases of COVID-19 around the globe. Epidemiological data suggests that the magnitude of morbidity and mortality due to COVID-19 was low in a few geographical regions and was unpredictably higher in a few regions. The genetic diversity of different geographical regions might explain the sporadic prevalence of the disease. In this context, human leukocyte antigens (HLA) represent the most polymorphic gene-dense region of the human genome and serve as an excellent mini-genome model for evaluating population genetic diversity in the context of susceptibility and progression of various diseases. In this review, we highlight the plausible influence of HLA in susceptibility, severity, immune response, and designing of epitope-based vaccines for COVID-19. Further, there is a need for extensive investigations for illustration and clarification of the functional impact of HLA class I and II alleles in the pathogenesis and progression of SARS-CoV-2.

Use of Immunoglobulin Y Antibodies: Biosensor-based Diagnostic Systems and Prophylactic and Therapeutic Drug Delivery Systems for Viral Respiratory Diseases

Respiratory viruses have caused many pandemics from past to present and are among the top global public health problems due to their rate of spread. The recently experienced COVID-19 pandemic has led to an understanding of the importance of rapid diagnostic tests to prevent epidemics and the difficulties of developing new vaccines. On the other hand, the emergence of resistance to existing antiviral drugs during the treatment process poses a major problem for society and global health systems. Therefore, there is a need for new approaches for the diagnosis, prophylaxis, and treatment of existing or new types of respiratory viruses. Immunoglobulin Y antibodies (IgYs) obtained from the yolk of poultry eggs have significant advantages, such as high production volumes, low production costs, and high selectivity, which enable the development of innovative and strategic products. Especially in diagnosing respiratory viruses, antibody-based biosensors in which these antibodies are integrated have the potential to provide superiority in making rapid and accurate diagnosis as a practical diagnostic tool. This review article aims to provide information on using IgY antibodies in diagnostic, prophylactic, and therapeutic applications for respiratory viruses and to provide a perspective for future innovative applications.

Coarse-grained molecular dynamics-guided immunoinformatics to explain the binder and non-binder classification of Cytotoxic T-cell epitope for SARS-CoV-2 peptide-based vaccine discovery

Epitope-based peptide vaccine can elicit T-cell immunity against SARS-CoV-2 to clear the infection. However, finding the best epitope from the whole antigen is challenging. A peptide screening using immunoinformatics usually starts from MHC-binding peptide, immunogenicity, cross-reactivity with the human proteome, to toxicity analysis. This pipeline classified the peptides into three categories, i.e., strong-, weak-, and non-binder, without incorporating the structural aspect. For this reason, the molecular detail that discriminates the binders from non-binder is interesting to be investigated. In this study, five CTL epitopes against HLA-A*02:01 were identified from the coarse-grained molecular dynamics-guided immunoinformatics screening. The strong binder showed distinctive activities from the non-binder in terms of structural and energetic properties. Furthermore, the second residue from the nonameric peptide was most important in the interaction with HLA-A*02:01. By understanding the nature of MHC-peptide interaction, we hoped to improve the chance of finding the best epitope for a peptide vaccine candidate.

Epitopes screening and vaccine molecular design of SADS-CoV based on immunoinformatics

The regional outbreak of the Swine acute diarrhea syndrome coronavirus (SADS-CoV) has seriously threatened the swine industry. There is an urgent need to discover safe and effective vaccines to contain them quickly. The coronavirus spike protein mediates virus entry into host cells, one of the most important antigenic determinants and a potential vaccine target. Therefore, this study aims to conduct a predictive analysis of the epitope of S protein B cells and T cells (MHC class I and class II) by immunoinformatics methods by screening and identifying protective antigenic epitopes that induce major neutralized antibodies and activate immune responses to construct epitope vaccines. The study explored primary, secondary, and tertiary structures, disulfide bonds, protein docking, immune response simulation, and seamless cloning of epitope vaccines. The results show that the spike protein dominant epitope of the screening has a high conservativeness and coverage of IFN-γ, IL-4-positive Th epitope, and CTL epitope. The constructed epitope vaccine interacts stably with TLR-3 receptors, and the immune response simulation shows good immunogenicity, which could effectively activate humoral and cellular immunity. After codon optimization, it was highly likely to be efficiently and stably expressed in the Escherichia coli K12 expression system. Therefore, the constructed epitope vaccine will provide a new theoretical basis for the design of SADS-CoV antiviral drugs and related research on coronaviruses such as SARS-CoV-2.

Design, construction and in vivo functional assessment of a hinge truncated sFLT01

Gene therapy for the treatment of ocular neovascularization has reached clinical trial phases. The AAV2-sFLT01 construct was already evaluated in a phase 1 open-label trial administered intravitreally to patients with advanced neovascular age-related macular degeneration. SFLT01 protein functions by binding to VEGF and PlGF molecules and inhibiting their activities simultaneously. It consists of human VEGFR1/Flt-1 (hVEGFR1), a polyglycine linker, and the Fc region of human IgG1. The IgG1 upper hinge region of the sFLT01 molecule makes it vulnerable to radical attacks and prone to causing immune reactions. This study pursued two goals: (i) minimizing the immunogenicity and vulnerability of the molecule by designing a truncated molecule called htsFLT01 (hinge truncated sFLT01) that lacked the IgG1 upper hinge and lacked 2 amino acids from the core hinge region; and (ii) investigating the structural and functional properties of the aforesaid chimeric molecule at different levels (in silico, in vitro, and in vivo). Molecular dynamics simulations and molecular mechanics energies combined with Poisson-Boltzmann and surface area continuum solvation calculations revealed comparable free energy of binding and binding affinity for sFLT01 and htsFLT01 to their cognate ligands. Conditioned media from human retinal pigment epithelial (hRPE) cells that expressed htsFLT01 significantly reduced tube formation in HUVECs. The AAV2-htsFLT01 virus suppressed vascular development in the eyes of newborn mice. The htsFLT01 gene construct is a novel anti-angiogenic tool with promising improvements compared to existing treatments.

Computer-Based Immunoinformatic Analysis to Predict Candidate T-Cell Epitopes for SARS-CoV-2 Vaccine Design

Since the first outbreak of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 2019, its high infectivity led to its prevalence around the world in an exceptionally short time. Efforts have been made to control the ongoing outbreak, and among them, vaccine developments are going on high priority. New clinical trials add to growing evidence that vaccines from many countries were highly effective at preventing SARS-CoV-2 virus infection. One of them is B cell-based vaccines, which were common during a pandemic. However, neutralizing antibody therapy becomes less effective when viruses mutate. In order to tackle the problem, we focused on T-cell immune mechanism. In this study, the mutated strains of the virus were selected globally from India (B.1.617.1 and B.1.617.2), United Kingdom (B.1.1.7), South Africa (B.1.351), and Brazil (P.1), and the overlapping peptides were collected based on mutation sites of S-protein. After that, residue scanning was used to predict the affinity between overlapping peptide and HLA-A*11:01, the most frequent human leukocyte antigen (HLA) allele among the Chinese population. Then, the binding free energy was evaluated with molecular docking to further verify the affinity changes after the mutations happen in the virus genomes. The affinity test results of three epitopes on spike protein from experimental validation were consistent with our predicted results, thereby supporting the inclusion of the epitope ₃₇₄FSTFKCYGL₃₈₂ in future vaccine design and providing a useful reference route to improve vaccine development.

Large-Scale Structure-Based Screening of Potential T Cell Cross-Reactivities Involving Peptide-Targets From BCG Vaccine and SARS-CoV-2

Although not being the first viral pandemic to affect humankind, we are now for the first time faced with a pandemic caused by a coronavirus. The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has been responsible for the COVID-19 pandemic, which caused more than 4.5 million deaths worldwide. Despite unprecedented efforts, with vaccines being developed in a record time, SARS-CoV-2 continues to spread worldwide with new variants arising in different countries. Such persistent spread is in part enabled by public resistance to vaccination in some countries, and limited access to vaccines in other countries. The limited vaccination coverage, the continued risk for resistant variants, and the existence of natural reservoirs for coronaviruses, highlight the importance of developing additional therapeutic strategies against SARS-CoV-2 and other coronaviruses. At the beginning of the pandemic it was suggested that countries with Bacillus Calmette-Guérin (BCG) vaccination programs could be associated with a reduced number and/or severity of COVID-19 cases. Preliminary studies have provided evidence for this relationship and further investigation is being conducted in ongoing clinical trials. The protection against SARS-CoV-2 induced by BCG vaccination may be mediated by cross-reactive T cell lymphocytes, which recognize peptides displayed by class I Human Leukocyte Antigens (HLA-I) on the surface of infected cells. In order to identify potential targets of T cell cross-reactivity, we implemented an in silico strategy combining sequence-based and structure-based methods to screen over 13,5 million possible cross-reactive peptide pairs from BCG and SARS-CoV-2. Our study produced (i) a list of immunogenic BCG-derived peptides that may prime T cell cross-reactivity against SARS-CoV-2, (ii) a large dataset of modeled peptide-HLA structures for the screened targets, and (iii) new computational methods for structure-based screenings that can be used by others in future studies. Our study expands the list of BCG peptides potentially involved in T cell cross-reactivity with SARS-CoV-2-derived peptides, and identifies multiple high-density "neighborhoods" of cross-reactive peptides which could be driving heterologous immunity induced by BCG vaccination, therefore providing insights for future vaccine development efforts.

Lessons Learned from Cutting-Edge Immunoinformatics on Next-Generation COVID-19 Vaccine Research

Presently, immunoinformatics and bioinformatics approaches are contributing actively to COVID-19 vaccine research. The first immunoinformatics-based vaccine construct against SARS-CoV-2 was published in February 2020. Following this, immunoinformatics and bioinformatics approaches have created a new direction in COVID-19 vaccine research. Several researchers have designed the next-generation COVID-19 vaccines using these approaches. Presently, immunoinformatics has accelerated immunology research immensely in the area of COVID-19. Hence, we have tried to depict the current scenario of immunoinformatics and bioinformatics in COVID-19 vaccine research.

Current and prospective computational approaches and challenges for developing COVID-19 vaccines

SARS-CoV-2, which causes COVID-19, was first identified in humans in late 2019 and is a coronavirus which is zoonotic in origin. As it spread around the world there has been an unprecedented effort in developing effective vaccines. Computational methods can be used to speed up the long and costly process of vaccine development. Antigen selection, epitope prediction, and toxicity and allergenicity prediction are areas in which computational tools have already been applied as part of reverse vaccinology for SARS-CoV-2 vaccine development. However, there is potential for computational methods to assist further. We review approaches which have been used and highlight additional bioinformatic approaches and PK modelling as in silico methods which may be useful for SARS-CoV-2 vaccine design but remain currently unexplored. As more novel viruses with pandemic potential are expected to arise in future, these techniques are not limited to application to SARS-CoV-2 but also useful to rapidly respond to novel emerging viruses.