Immunoinformatics and Structural Analysis for Identification of Immunodominant Epitopes in SARS-CoV-2 as Potential Vaccine Targets

Enhancing explainable SARS-CoV-2 vaccine development leveraging bee colony optimised Bi-LSTM, Bi-GRU models and bioinformatic analysis

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a single-stranded RNA virus that caused the outbreak of the coronavirus disease 2019 (COVID-19). The COVID-19 outbreak has led to millions of deaths and economic losses globally. Vaccination is the most practical solution, but finding epitopes (antigenic peptide regions) in the SARS-CoV-2 proteome is challenging, costly, and time-consuming. Here, we proposed a deep learning method based on standalone Recurrent Neural networks to predict epitopes from SARS-CoV-2 proteins easily. We optimised the standalone Bidirectional Long Short-Term Memory (Bi-LSTM) and Bidirectional Gated Recurrent Unit (Bi-GRU) with a bioinspired optimisation algorithm, namely, Bee Colony Optimization (BCO). The study shows that LSTM-based models, particularly BCO-Bi-LSTM, outperform all other models and achieve an accuracy of 0.92 and AUC of 0.944. To overcome the challenge of understanding the model predictions, explainable AI using the Shapely Additive Explanations (SHAP) method was employed to explain how Blackbox models make decisions. Finally, the predicted epitopes led to the development of a multi-epitope vaccine. The multi-epitope vaccine effectiveness evaluation is based on vaccine toxicity, allergic response risk, and antigenic and biochemical characteristics using bioinformatic tools. The developed multi-epitope vaccine is non-toxic and highly antigenic. Codon adaptation, cloning, gel electrophoresis assess genomic sequence, protein composition, expression and purification while docking and IMMSIM servers simulate interactions and immunological response, respectively. These investigations provide a conceptual framework for developing a SARS-CoV-2 vaccine.

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.

An immunoinformatics approach to study the epitopes of SARS-CoV-2 helicase, Nsp13

Introduction and objective.

Vaccines are administered worldwide to control on-going coronavirus disease-19 (COVID-19) pandemic caused by SARS-CoV-2. Vaccine efficacy is largely contributed by the epitopes present on the viral proteins and their alteration might help emerging variants to escape host immune surveillance. Therefore, this study was designed to study SARS-CoV-2 Nsp13 protein, its epitopes and evolution.

Methods

Clustal Omega was used to identify mutations in Nsp13 protein. Secondary structure and disorder score was predicted by CFSSP and PONDR-VSL2 webservers. Protein stability was predicted by DynaMut webserver. B cell epitopes were predicted by IEDB DiscoTope 2.0 tools and their 3D structures were represented by discovery studio. Antigenicity and allergenicity of epitopes were predicted by Vaxijen2.0 and AllergenFPv.1.0. Physiochemical properties of epitopes were predicted by Toxinpred, HLP webserver tool.

Results

Our data revealed 182 mutations in Nsp13 among Indian SARS-CoV-2 isolates, which were characterised by secondary structure and per-residue disorderness, stability and dynamicity predictions. To correlate the functional impact of these mutations, we characterised the most prominent B cell and T cell epitopes contributed by Nsp13. Our data revealed twenty-one epitopes, which exhibited antigenicity, stability and interactions with MHC class-I and class-II molecules. Subsequently, the physiochemical properties of these epitopes were analysed. Furthermore, eighteen mutations reside in these Nsp13 epitopes.

Conclusions

We report appearance of eighteen mutations in the predicted twenty-one epitopes of Nsp13. Among these, at least seven epitopes closely matches with the functionally validated epitopes. Altogether, our study shows the pattern of evolution of Nsp13 epitopes and their probable implications.

Retrospective in silico mutation profiling of SARS-CoV-2 structural proteins circulating in Uganda by July 2021: Towards refinement of COVID-19 disease vaccines, diagnostics, and therapeutics

The SARS-CoV-2 virus, the agent of COVID-19, caused unprecedented loss of lives and economic decline worldwide. Although the introduction of public health measures, vaccines, diagnostics, and therapeutics disrupted the spread of the SARS-CoV-2, the emergence of variants poses substantial threat. This study traced SARS-CoV-2 variants circulating in Uganda by July 2021 to inform the necessity for refinement of the intervention medical products. A comprehensive in silico analysis of the SARS-CoV-2 genomes detected in clinical samples collected from COVID-19 patients in Uganda revealed occurrence of structural protein variants with potential of escaping detection, resisting antibody therapy, or increased infectivity. The genome sequence dataset was retrieved from the GISAID database and the open reading frame encoding the spike, envelope, membrane, or nucleocapsid proteins was translated. The obtained protein sequences were aligned and inspected for existence of variants. The variant positions on each of the four alignment sets were mapped on predicted epitopes as well as the 3D structures. Additionally, sequences within each of the sets were clustered by family. A phylogenetic tree was constructed to assess relationship between the encountered spike protein sequences and Wuhan-Hu-1 wild-type, or the Alpha, Beta, Delta and Gamma variants of concern. Strikingly, the frequency of each of the spike protein point mutations F157L/Del, D614G and P681H/R was over 50%. The furin and the transmembrane serine protease 2 cleavage sites were unaffected by mutation. Whereas the Delta dominated the spike sequences (16.5%, 91/550), Gamma was not detected. The envelope protein was the most conserved with 96.3% (525/545) sequences being wild-type followed by membrane at 68.4% (397/580). Although the nucleocapsid protein sequences varied, the variant residue positions were less concentrated at the RNA binding domains. The dominant nucleocapsid sequence variant was S202N (34.5%, 205/595). These findings offer baseline information required for refining the existing COVID-19 vaccines, diagnostics, and therapeutics.

Mapping Potential Vaccine Candidates Predicted by VaxiJen for Different Viral Pathogens between 2017-2021-A Scoping Review

Reverse vaccinology (RV) is a promising alternative to traditional vaccinology. RV focuses on in silico methods to identify antigens or potential vaccine candidates (PVCs) from a pathogen's proteome. Researchers use VaxiJen, the most well-known RV tool, to predict PVCs for various pathogens. The purpose of this scoping review is to provide an overview of PVCs predicted by VaxiJen for different viruses between 2017 and 2021 using Arksey and O'Malley's framework and the Preferred Reporting Items for Systematic Reviews extension for Scoping Reviews (PRISMA-ScR) guidelines. We used the term 'vaxijen' to search PubMed, Scopus, Web of Science, EBSCOhost, and ProQuest One Academic. The protocol was registered at the Open Science Framework (OSF). We identified articles on this topic, charted them, and discussed the key findings. The database searches yielded 1033 articles, of which 275 were eligible. Most studies focused on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), published between 2020 and 2021. Only a few articles (8/275; 2.9%) conducted experimental validations to confirm the predictions as vaccine candidates, with 2.2% (6/275) articles mentioning recombinant protein expression. Researchers commonly targeted parts of the SARS-CoV-2 spike (S) protein, with the frequently predicted epitopes as PVCs being major histocompatibility complex (MHC) class I T cell epitopes WTAGAAAYY, RQIAPGQTG, IAIVMVTIM, and B cell epitope IAPGQTGKIADY, among others. The findings of this review are promising for the development of novel vaccines. We recommend that vaccinologists use these findings as a guide to performing experimental validation for various viruses, with SARS-CoV-2 as a priority, because better vaccines are needed, especially to stay ahead of the emergence of new variants. If successful, these vaccines could provide broader protection than traditional vaccines.

Computational design of a broad-spectrum multi-epitope vaccine candidate against seven strains of human coronaviruses

Spike (S) proteins are an attractive target as it mediates the binding of the SARS-CoV-2 to the host through ACE-2 receptors. We hypothesize that the screening of the S protein sequences of all the seven known HCoVs would result in the identification of potential multi-epitope vaccine candidates capable of conferring immunity against various HCoVs. In the present study, several machine learning-based in-silico tools were employed to design a broad-spectrum multi-epitope vaccine candidate targeting the S protein of seven known strains of human coronaviruses. Herein, multiple B-cell epitopes and T-cell epitopes (CTL and HTL) were predicted from the S protein sequences of all seven known HCoVs. Post-prediction they were linked together with an adjuvant to construct a potential broad-spectrum vaccine candidate. Secondary and tertiary structures were predicted and validated, and the refined 3D-model was docked with an immune receptor. The vaccine candidate was evaluated for antigenicity, allergenicity, solubility, and its ability to achieve high-level expression in bacterial hosts. Finally, the immune simulation was carried out to evaluate the immune response after three vaccine doses. The designed vaccine is antigenic (with or without the adjuvant), non-allergenic, binds well with TLR-3 receptor and might elicit a diverse and strong immune response.

Clinical and Molecular Characterization of a Rare Case of BNT162b2 mRNA COVID-19 Vaccine-Associated Myositis

Initial clinical trials and surveillance data have shown that the most commonly administered BNT162b2 COVID-19 mRNA vaccine is effective and safe. However, several cases of mRNA vaccine-induced mild to moderate adverse events were recently reported. Here, we report a rare case of myositis after injection of the first dose of BNT162b2 COVID-19 mRNA vaccine into the left deltoid muscle of a 34-year-old, previously healthy woman who presented progressive proximal muscle weakness, progressive dysphagia, and dyspnea with respiratory failure. One month after vaccination, BNT162b2 vaccine mRNA expression was detected in a tissue biopsy of the right deltoid and quadriceps muscles. We propose this case as a rare example of COVID-19 mRNA vaccine-induced myositis. This study comprehensively characterizes the clinical and molecular features of BNT162b2 mRNA vaccine-associated myositis in which the patient was severely affected.

Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2

Despite tremendous efforts in the past two years, our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), virus-host interactions, immune response, virulence, transmission, and evolution is still very limited. This limitation calls for further in-depth investigation. Computational studies have become an indispensable component in combating coronavirus disease 2019 (COVID-19) due to their low cost, their efficiency, and the fact that they are free from safety and ethical constraints. Additionally, the mechanism that governs the global evolution and transmission of SARS-CoV-2 cannot be revealed from individual experiments and was discovered by integrating genotyping of massive viral sequences, biophysical modeling of protein-protein interactions, deep mutational data, deep learning, and advanced mathematics. There exists a tsunami of literature on the molecular modeling, simulations, and predictions of SARS-CoV-2 and related developments of drugs, vaccines, antibodies, and diagnostics. To provide readers with a quick update about this literature, we present a comprehensive and systematic methodology-centered review. Aspects such as molecular biophysics, bioinformatics, cheminformatics, machine learning, and mathematics are discussed. This review will be beneficial to researchers who are looking for ways to contribute to SARS-CoV-2 studies and those who are interested in the status of the field.

Generic approach for mathematical model of multi-strain pandemics

Multi-strain pandemics have emerged as a major concern. We introduce a new model for assessing the connection between multi-strain pandemics and mortality rate, basic reproduction number, and maximum infected individuals. The proposed model provides a general mathematical approach for representing multi-strain pandemics, generalizing for an arbitrary number of strains. We show that the proposed model fits well with epidemiological historical world health data over a long time period. From a theoretical point of view, we show that the increasing number of strains increases logarithmically the maximum number of infected individuals and the mean mortality rate. Moreover, the mean basic reproduction number is statistically identical to the single, most aggressive pandemic strain for multi-strain pandemics.

Peptides for Vaccine Development

This review discusses peptide epitopes used as antigens in the development of vaccines in clinical trials as well as future vaccine candidates. It covers peptides used in potential immunotherapies for infectious diseases including SARS-CoV-2, influenza, hepatitis B and C, HIV, malaria, and others. In addition, peptides for cancer vaccines that target examples of overexpressed proteins are summarized, including human epidermal growth factor receptor 2 (HER-2), mucin 1 (MUC1), folate receptor, and others. The uses of peptides to target cancers caused by infective agents, for example, cervical cancer caused by human papilloma virus (HPV), are also discussed. This review also provides an overview of model peptide epitopes used to stimulate non-specific immune responses, and of self-adjuvanting peptides, as well as the influence of other adjuvants on peptide formulations. As highlighted in this review, several peptide immunotherapies are in advanced clinical trials as vaccines, and there is great potential for future therapies due the specificity of the response that can be achieved using peptide epitopes.

Computational construction of a glycoprotein multi-epitope subunit vaccine candidate for old and new South-African SARS-CoV-2 virus strains

The discovery of a new SARS-CoV-2 virus strain in South Africa presents a major public health threat, therefore contributing to increased infections and transmission rates during the second wave of the global pandemic. This study lays the groundwork for the development of a novel subunit vaccine candidate from the circulating strains of South African SARS-CoV-2 and provides an understanding of the molecular epidemiological trend of the circulating strains. A total of 475 whole-genome nucleotide sequences from South Africa submitted between December 1, 2020 and February 15, 2021 available at the GISAID database were retrieved based on its size, coverage level and hosts. To obtain the distribution of the clades and lineages of South African SARS-CoV-2 circulating strains, the metadata of the sequence retrieved were subjected to an epidemiological analysis. There was a prediction of the cytotoxic T lymphocytes (CTL), Helper T cells (HTL) and B-cell epitopes. Furthermore, there was allergenicity, antigenicity and toxicity predictions on the epitopes. The analysis of the physicochemical properties of the vaccine construct was performed; the secondary structure, tertiary structure and B-cell 3D conformational structure of the vaccine construct were predicted. Also, molecular binding simulations and dynamics simulations were adopted in the prediction of the vaccine construct's stability and binding affinity with TLRs. Result obtained from the metadata analysis indicated lineage B.1.351 to be in higher circulation among various circulating strains of SARS-CoV-2 in South Africa and GH has the highest number of circulating clades. The construct of the novel vaccine was antigenic, non-allergenic and non-toxic. The Instability index (II) score and aliphatic index were estimated as 41.74 and 78.72 respectively. The computed half-life in mammalian reticulocytes was 4.4 h in vitro, for yeast and in E. coli was >20 h and >10 h in vivo respectively. The grand average of hydropathicity (GRAVY) score is estimated to be -0.129, signifying the hydrophilic nature of the protein. The molecular docking indicates that the vaccine construct has a high binding affinity towards the TLRs with TLR 3 having the highest binding energy (-1203.2 kcal/mol) and TLR 9 with the lowest (-1559.5 kcal/mol). These results show that the vaccine construct is promising and should be evaluated using animal model.

A peptide-based subunit candidate vaccine against SARS-CoV-2 delivered by biodegradable mesoporous silica nanoparticles induced high humoral and cellular immunity in mice

Development of a rapidly scalable vaccine is still an urgent task to halt the spread of COVID-19. We have demonstrated biodegradable mesoporous silica nanoparticles (BMSNs) as a good drug delivery carrier for tumor therapy. In this study, seven linear B cell epitopes and three CD8⁺ T cell epitopes were screened from the spike (S) glycoprotein of SARS-CoV-2 by computer-based immunoinformatic approaches for vaccine design. A nanoparticle-based candidate vaccine (B/T@BMSNs) against SARS-CoV-2 was rapidly prepared by encapsulating these ten epitope peptides within BMSNs, respectively. BMSNs with potential biodegradability, proved to possess excellent safety in vitro and in vivo, could efficiently deliver epitope peptides into the cytoplasm of RAW264.7 cells. Strong Th1-biased humoral and cellular immunity were induced by B/T@BMSNs in mice and all the 10 selected epitopes were identified as effective antigen epitopes, which could induce robust peptide-specific immune response. The elicited functional antibody could bind to the recombinant S protein and block the binding of the S protein to the ACE-2 receptor. These results demonstrate the potential of a nanoparticles vaccine platform based on BMSNs to rapidly develop peptide-based subunit vaccine candidates against SARS-CoV-2.

Immunodominant linear B cell epitopes in the spike and membrane proteins of SARS-CoV-2 identified by immunoinformatics prediction and immunoassay

SARS-CoV-2 continues to infect an ever-expanding number of people, resulting in an increase in the number of deaths globally. With the emergence of new variants, there is a corresponding decrease in the currently available vaccine efficacy, highlighting the need for greater insights into the viral epitope profile for both vaccine design and assessment. In this study, three immunodominant linear B cell epitopes in the SARS-CoV-2 spike receptor-binding domain (RBD) were identified by immunoinformatics prediction, and confirmed by ELISA with sera from Macaca fascicularis vaccinated with a SARS-CoV-2 RBD subunit vaccine. Further immunoinformatics analyses of these three epitopes gave rise to a method of linear B cell epitope prediction and selection. B cell epitopes in the spike (S), membrane (M), and envelope (E) proteins were subsequently predicted and confirmed using convalescent sera from COVID-19 infected patients. Immunodominant epitopes were identified in three regions of the S2 domain, one region at the S1/S2 cleavage site and one region at the C-terminus of the M protein. Epitope mapping revealed that most of the amino acid changes found in variants of concern are located within B cell epitopes in the NTD, RBD, and S1/S2 cleavage site. This work provides insights into B cell epitopes of SARS-CoV-2 as well as immunoinformatics methods for B cell epitope prediction, which will improve and enhance SARS-CoV-2 vaccine development against emergent variants.

Seasonal UV exposure and vitamin D: association with the dynamics of COVID-19 transmission in Europe

Several recent studies have demonstrated that low plasma 25(OH) vitamin D levels are associated with the risk of COVID‐19 infection. The primary source of vitamin D production in humans is environmental UV radiation. In many viral respiratory diseases, peak infection rates are observed during winter due to reduced UV exposure and low temperatures. In Europe, the second wave of COVID‐19 began early in the winter of 2020. Investigating the impact of seasonal temperature and UV exposure on COVID‐19 transmission could thus aid in prevention and intervention. As such, we first performed a comprehensive meta‐analysis of all related published literature based on the association between vitamin D and COVID‐19, which supported the hypothesis that the low vitamin D level is a critical risk factor for COVID‐19 infection. Next, to understand the potential impact of seasonal UV and temperature levels on COVID‐19 cases, we analyzed meteorological data and daily COVID‐19 cases per million in the populations of 26 European countries. We observed that low temperature, UV index, and cloud‐free vitamin D UV dose (UVDVF) levels are negatively correlated with COVID‐19 prevalence in Europe. Furthermore, a distributed lag nonlinear model was used to assess the nonlinear delayed effects of individual seasonal factors on COVID‐19 cases. Such analysis highlighted the significantly delayed impact of UVDVF on the cumulative relative risk of COVID‐19 infection. The findings of this study suggest that low UV exposure can affect the required production of vitamin D in the body, which substantially influences the dynamics of COVID‐19 transmission and severity.

A reverse vaccinology and immunoinformatics approach for designing a multiepitope vaccine against SARS-CoV-2

Since 2019, the world was involved with SARS-CoV-2 and consequently, with the announcement by the World Health Organization that COVID-19 was a pandemic, scientific were an effort to obtain the best approach to combat this global dilemma. The best way to prevent the pandemic from spreading further is to use a vaccine against COVID-19. Here, we report the design of a recombinant multi-epitope vaccine against the four proteins spike or crown (S), membrane (M), nucleocapsid (N), and envelope (E) of SARS-CoV-2 using immunoinformatics tools. We evaluated the most antigenic epitopes that bind to HLA class 1 subtypes, along with HLA class 2, as well as B cell epitopes. Beta-defensin 3 and PADRE sequence were used as adjuvants in the structure of the vaccine. KK, GPGPG, and AAY linkers were used to fuse the selected epitopes. The nucleotide sequence was cloned into pET26b(+) vector using restriction enzymes XhoI and NdeI, and HisTag sequence was considered in the C-terminal of the construct. The results showed that the proposed candidate vaccine is a 70.87 kDa protein with high antigenicity and immunogenicity as well as non-allergenic and non-toxic. A total of 95% of the selected epitopes have conservancy with similar sequences. Molecular docking showed a strong binding between the vaccine structure and tool-like receptor (TLR) 7/8. The docking, molecular dynamics, and MM/PBSA analysis showed that the vaccine established a stable interaction with both structures of TLR7 and TLR8. Simulation of immune stimulation by this vaccine showed that it evokes immune responses related to humoral and cellular immunity.

COVID-19 Pandemic and Vaccines Update on Challenges and Resolutions

The coronavirus disease (COVID-19) is caused by a positive-stranded RNA virus called severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), belonging to the Coronaviridae family. This virus originated in Wuhan City, China, and became the cause of a multiwave pandemic that has killed 3.46 million people worldwide as of May 22, 2021. The havoc intensified with the emergence of SARS-CoV-2 variants (B.1.1.7; Alpha, B.1.351; Beta, P.1; Gamma, B.1.617; Delta, B.1.617.2; Delta-plus, B.1.525; Eta, and B.1.429; Epsilon etc.) due to mutations generated during replication. More variants may emerge to cause additional pandemic waves. The most promising approach for combating viruses and their emerging variants lies in prophylactic vaccines. Several vaccine candidates are being developed using various platforms, including nucleic acids, live attenuated virus, inactivated virus, viral vectors, and protein-based subunit vaccines. In this unprecedented time, 12 vaccines against SARS-CoV-2 have been phased in following WHO approval, 184 are in the preclinical stage, and 100 are in the clinical development process. Many of them are directed to elicit neutralizing antibodies against the viral spike protein (S) to inhibit viral entry through the ACE-2 receptor of host cells. Inactivated vaccines, to the contrary, provide a wide range of viral antigens for immune activation. Being an intracellular pathogen, the cytotoxic CD8+ T Cell (CTL) response remains crucial for all viruses, including SARS-CoV-2, and needs to be explored in detail. In this review, we try to describe and compare approved vaccines against SARS-CoV-2 that are currently being distributed either after phase III clinical trials or for emergency use. We discuss immune responses induced by various candidate vaccine formulations; their benefits, potential limitations, and effectiveness against variants; future challenges, such as antibody-dependent enhancement (ADE); and vaccine safety issues and their possible resolutions. Most of the current vaccines developed against SARS-CoV-2 are showing either promising or compromised efficacy against new variants. Multiple antigen-based vaccines (multivariant vaccines) should be developed on different platforms to tackle future variants. Alternatively, recombinant BCG, containing SARS-CoV-2 multiple antigens, as a live attenuated vaccine should be explored for long-term protection. Irrespective of their efficacy, all vaccines are efficient in providing protection from disease severity. We must insist on vaccine compliance for all age groups and work on vaccine hesitancy globally to achieve herd immunity and, eventually, to curb this pandemic.

An immunogenetic view of COVID-19

Meeting the challenges brought by the COVID-19 pandemic requires an interdisciplinary approach. In this context, integrating knowledge of immune function with an understanding of how genetic variation influences the nature of immunity is a key challenge. Immunogenetics can help explain the heterogeneity of susceptibility and protection to the viral infection and disease progression. Here, we review the knowledge developed so far, discussing fundamental genes for triggering the innate and adaptive immune responses associated with a viral infection, especially with the SARS-CoV-2 mechanisms. We emphasize the role of the HLA and KIR genes, discussing what has been uncovered about their role in COVID-19 and addressing methodological challenges of studying these genes. Finally, we comment on questions that arise when studying admixed populations, highlighting the case of Brazil. We argue that the interplay between immunology and an understanding of genetic associations can provide an important contribution to our knowledge of COVID-19.

Towards an Ensemble Vaccine against the Pegivirus Using Computational Modelling Approaches and Its Validation through In Silico Cloning and Immune Simulation

Pegivirus, HPgV, which was earlier known as Gb virus and hepatitis G virus, is an enveloped, positive-stranded RNA and lymphotropic virus classified into the Flaviviridae family. The transmission routes primarily involve blood products, and infections are worldwide, leading up to 25% of persistent infections. To date, no effective therapeutic means are available to clear Pegivirus infections. Effective vaccine therapeutics is the best alternative to manage this disease and any associated potential pandemic. Thus, whole proteome-based mining of immunogenic peptides, i.e., CTL (cytotoxic T lymphocytes), HTL (helper T lymphocytes), and B cell epitopes, was mapped to design a vaccine ensemble. Our investigation revealed that 29 different epitopes impart a critical role in immune response induction, which was also validated by exploring its physiochemical properties and experimental feasibility. In silico expression and host immune simulation were examined using an agent-based modeling approach and confirmed the induction of both primary and secondary immune factors such as IL, cytokines, and antibodies. The current study warrants further lab experiments to demonstrate its efficacy and safety.

Bioinformatics Prediction of SARS-CoV-2 Epitopes as Vaccine Candidates for the Colombian Population

Coronavirus disease (COVID-19) pandemic caused by the coronavirus SARS-CoV-2 represents an enormous challenge to global public health, with thousands of infections and deaths in over 200 countries worldwide. The purpose of this study was to identify SARS-CoV-2 epitopes with potential to interact in silico with the alleles of the human leukocyte antigen class I (HLA I) and class II (HLA II) commonly found in the Colombian population to promote both CD4 and CD8 immune responses against this virus. The generation and evaluation of the peptides in terms of HLA I and HLA II binding, immune response, toxicity and allergenicity were performed by using computer-aided tools, such as NetMHCpan 4.1, NetMHCIIpan 4.0, VaxiJem, ToxinPred and AllerTop. Furthermore, the interaction between the predicted epitopes with HLA I and HLA II proteins frequently found in the Colombian population was studied through molecular docking simulations in AutoDock Vina and interaction analysis in LigPlot+. One of the promising peptides proposed in this study is the HLA I epitope YQPYRVVVL, which displayed an estimated coverage of over 82% and 96% for the Colombian and worldwide population, respectively. These findings could be useful for the design of new epitope-vaccines that include Colombia among their population target.

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.

Multi-Subunit SARS-CoV-2 Vaccine Design Using Evolutionarily Conserved T- and B- Cell Epitopes

The SARS-CoV-2 pandemic has created a public health crisis worldwide. Although vaccines against the virus are efficiently being rolled out, they are proving to be ineffective against certain emerging SARS-CoV-2 variants. The high degree of sequence similarity between SARS-CoV-2 and other human coronaviruses (HCoV) presents the opportunity for designing vaccines that may offer protection against SARS-CoV-2 and its emerging variants, with cross-protection against other HCoVs. In this study, we performed bioinformatics analyses to identify T and B cell epitopes originating from spike, membrane, nucleocapsid, and envelope protein sequences found to be evolutionarily conserved among seven major HCoVs. Evolutionary conservation of these epitopes indicates that they may have critical roles in viral fitness and are, therefore, unlikely to mutate during viral replication thus making such epitopes attractive candidates for a vaccine. Our designed vaccine construct comprises of twelve T and six B cell epitopes that are conserved among HCoVs. The vaccine is predicted to be soluble in water, stable, have a relatively long half-life, and exhibit low allergenicity and toxicity. Our docking results showed that the vaccine forms stable complex with toll-like receptor 4, while the immune simulations predicted that the vaccine may elicit strong IgG, IgM, and cytotoxic T cell responses. Therefore, from multiple perspectives, our multi-subunit vaccine design shows the potential to elicit a strong immune-protective response against SARS-CoV-2 and its emerging variants while carrying minimal risk for causing adverse effects.

Comparison of Immunological Profiles of SARS-CoV-2 Variants in the COVID-19 Pandemic Trends: An Immunoinformatics Approach

The current dynamics of the COVID-19 pandemic have become a serious concern with the emergence of a series of mutant variants of the SARS-CoV-2 virus. Unlike the previous strain, it is reported that the descendants are associated with increased risk of transmission yet causing less impact in terms of hospital admission, the severity of illness, or mortality. Moreover, the vaccine efficacy is also not believed to vary among the population depending on the variants of the virus and ethnicity. It has been determined that the mutations recorded in the spike gene and protein of the newly evolved viruses are specificallyresponsible for this transformation in the behavior of the virus and its disease condition. Hence, this study aimed to compare the immunogenic profiles of the spike protein from the latest variants of the SARS-CoV-2 virus concerning the probability of COVID-19 severity. Genome sequences of the latest SARS-CoV-2 variants were obtained from GISAID and NCBI repositories. The translated protein sequences were run against T-cell and B-cell epitope prediction tools. Subsequently, antigenicity, immunogenicity, allergenicity, toxicity, and conservancy of the identified epitopes were ascertained using various prediction servers. Only the non-allergic and non-toxic potential epitopes were matched for population relevance by using the Human Leucocyte Antigen population registry in IEDB. Finally, the selected epitopes were validated by docking and simulation studies. The evaluated immunological parameters would concurrently reveal the severity of COVID-19, determining the infection rate of the pathogen. Our immunoinformatics approach disclosed that spike protein of the five variants was capable of forming potential T and B-cell epitopes with varying immune responses. Although the Wuhan strain showed a high number of epitope/HLA combinations, relatively less antigenicity and higher immunogenicity results in poor neutralizing capacity, which could be associated with increased disease severity. Our data demonstrate that increased viral antigenicity with moderate to high immunogenicity, and several potential epitope/HLA combinations in England strain, the USA, India, and South Africa variants, could possess a high neutralizing ability. Therefore, our findings reinforce that the newly circulating variants of SARS-CoV-2 might be associated with more infectiousness and less severe disease condition despite their greater viremia, as reported in the recent COVID-19 cases, whichconsequently determine their increased epidemiological fitness.

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.

In silico T cell epitope identification for SARS-CoV-2: Progress and perspectives

Growing evidence suggests that T cells may play a critical role in combating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Hence, COVID-19 vaccines that can elicit a robust T cell response may be particularly important. The design, development and experimental evaluation of such vaccines is aided by an understanding of the landscape of T cell epitopes of SARS-CoV-2, which is largely unknown. Due to the challenges of identifying epitopes experimentally, many studies have proposed the use of in silico methods. Here, we present a review of the in silico methods that have been used for the prediction of SARS-CoV-2 T cell epitopes. These methods employ a diverse set of technical approaches, often rooted in machine learning. A performance comparison is provided based on the ability to identify a specific set of immunogenic epitopes that have been determined experimentally to be targeted by T cells in convalescent COVID-19 patients, shedding light on the relative performance merits of the different approaches adopted by the in silico studies. The review also puts forward perspectives for future research directions.

Specific epitopes form extensive hydrogen-bonding networks to ensure efficient antibody binding of SARS-CoV-2: Implications for advanced antibody design

Neutralizing antibody targeting to the SARS-CoV-2 could provide powerful therapies. A neutralizing antibody CC12.1 which was found in SARS-CoV-2 patient samples provides potential protection from disease. The aim of molecular dynamics simulations is to identify key epitopes that are crucial to the antibody binding of SARS-CoV-2 spike glycoprotein receptor binding domain (RBD) to promote the development of superior antibodies. Binding modes of the antibody were investigated and compared with RBD bound receptor ACE2. Key epitopes were revealed and a distal motif of RBD (residue numbers 473–488) was demonstrated by analyzing dynamic trajectories. Compared to the receptor ACE2, conformation of RBD could be better stabilized through additional interaction of antibody with the distal motif of RBD, which was further found driven by electrostatic complementarity. By further analysis of the extensive hydrogen-bonding networks, residues D405, K417, Y421, Y453, L455, R457, Y473, A475, N487, G502, Y505 of RBD, which mainly interacted with CDR H3/L3 and two conserved motifs SNY, SGGS, were identified as key epitopes. Higher binding free energy calculated after point mutations on key residues confirms the crucial role for the specific binding. Subsequently, mutations of V_H V98E and V_L G68D in CC12.1, which could significantly enhance the binding affinity of the antibody, were also proposed. The results indicate the key epitopes for antibody binding and give explanations for failure of neutralization antibody caused by specific residues mutations on structural basis. Simulations of two point mutations on antibody provide feasible information for advanced antibody design.

The impact of structural bioinformatics tools and resources on SARS-CoV-2 research and therapeutic strategies

SARS-CoV-2 is the causative agent of COVID-19, the ongoing global pandemic. It has posed a worldwide challenge to human health as no effective treatment is currently available to combat the disease. Its severity has led to unprecedented collaborative initiatives for therapeutic solutions against COVID-19. Studies resorting to structure-based drug design for COVID-19 are plethoric and show good promise. Structural biology provides key insights into 3D structures, critical residues/mutations in SARS-CoV-2 proteins, implicated in infectivity, molecular recognition and susceptibility to a broad range of host species. The detailed understanding of viral proteins and their complexes with host receptors and candidate epitope/lead compounds is the key to developing a structure-guided therapeutic design. Since the discovery of SARS-CoV-2, several structures of its proteins have been determined experimentally at an unprecedented speed and deposited in the Protein Data Bank. Further, specialized structural bioinformatics tools and resources have been developed for theoretical models, data on protein dynamics from computer simulations, impact of variants/mutations and molecular therapeutics. Here, we provide an overview of ongoing efforts on developing structural bioinformatics tools and resources for COVID-19 research. We also discuss the impact of these resources and structure-based studies, to understand various aspects of SARS-CoV-2 infection and therapeutic development. These include (i) understanding differences between SARS-CoV-2 and SARS-CoV, leading to increased infectivity of SARS-CoV-2, (ii) deciphering key residues in the SARS-CoV-2 involved in receptor-antibody recognition, (iii) analysis of variants in host proteins that affect host susceptibility to infection and (iv) analyses facilitating structure-based drug and vaccine design against SARS-CoV-2.

mRNA-lncRNA Co-Expression Network Analysis Reveals the Role of lncRNAs in Immune Dysfunction during Severe SARS-CoV-2 Infection

The recently emerged SARS-CoV-2 virus is responsible for the ongoing COVID-19 pandemic that has rapidly developed into a global public health threat. Patients severely affected with COVID-19 present distinct clinical features, including acute respiratory disorder, neutrophilia, cytokine storm, and sepsis. In addition, multiple pro-inflammatory cytokines are found in the plasma of such patients. Transcriptome sequencing of different specimens obtained from patients suffering from severe episodes of COVID-19 shows dynamics in terms of their immune responses. However, those host factors required for SARS-CoV-2 propagation and the underlying molecular mechanisms responsible for dysfunctional immune responses during COVID-19 infection remain elusive. In the present study, we analyzed the mRNA-long non-coding RNA (lncRNA) co-expression network derived from publicly available SARS-CoV-2-infected transcriptome data of human lung epithelial cell lines and bronchoalveolar lavage fluid (BALF) from COVID-19 patients. Through co-expression network analysis, we identified four differentially expressed lncRNAs strongly correlated with genes involved in various immune-related pathways crucial for cytokine signaling. Our findings suggest that the aberrant expression of these four lncRNAs can be associated with cytokine storms and anti-viral responses during severe SARS-CoV-2 infection of the lungs. Thus, the present study uncovers molecular interactions behind the cytokine storm activation potentially responsible for hyper-inflammatory responses in critical COVID-19 patients.

Public Baseline and shared response structures support the theory of antibody repertoire functional commonality

The naïve antibody/B-cell receptor (BCR) repertoires of different individuals ought to exhibit significant functional commonality, given that most pathogens trigger an effective antibody response to immunodominant epitopes. Sequence-based repertoire analysis has so far offered little evidence for this phenomenon. For example, a recent study estimated the number of shared ('public') antibody clonotypes in circulating baseline repertoires to be around 0.02% across ten unrelated individuals. However, to engage the same epitope, antibodies only require a similar binding site structure and the presence of key paratope interactions, which can occur even when their sequences are dissimilar. Here, we search for evidence of geometric similarity/convergence across human antibody repertoires. We first structurally profile naïve ('baseline') antibody diversity using snapshots from 41 unrelated individuals, predicting all modellable distinct structures within each repertoire. This analysis uncovers a high (much greater than random) degree of structural commonality. For instance, around 3% of distinct structures are common to the ten most diverse individual samples ('Public Baseline' structures). Our approach is the first computational method to find levels of BCR commonality commensurate with epitope immunodominance and could therefore be harnessed to find more genetically distant antibodies with same-epitope complementarity. We then apply the same structural profiling approach to repertoire snapshots from three individuals before and after flu vaccination, detecting a convergent structural drift indicative of recognising similar epitopes ('Public Response' structures). We show that Antibody Model Libraries derived from Public Baseline and Public Response structures represent a powerful geometric basis set of low-immunogenicity candidates exploitable for general or target-focused therapeutic antibody screening.

Interplay of Antibody and Cytokine Production Reveals CXCL13 as a Potential Novel Biomarker of Lethal SARS-CoV-2 Infection

The SARS-CoV-2 pandemic is impacting the global population. This study was designed to assess the interplay of antibodies with the cytokine response in SARS-CoV-2 patients. We demonstrate that significant levels of anti-SARS-CoV-2 antibody to receptor binding domain (RBD), nucleocapsid, and spike S1 subunit of SARS-CoV-2 develop over the first 10 to 20 days of infection. The majority of patients produced antibodies against all three antigens (219/255 SARS-CoV-2+ patient specimens, 86%), suggesting a broad response to viral proteins. Antibody levels to SARS-CoV-2 antigens were different based on patient mortality, sex, blood type, and age. Analyses of these findings may help explain variation in immunity between these populations. To better understand the systemic immune response, we analyzed the levels of 20 cytokines by SARS-CoV-2 patients throughout infection. Cytokine analysis of SARS-CoV-2+ patients exhibited increases in proinflammatory markers (interleukin 6 [IL-6], IL-8, IL-18, and gamma interferon [IFN-γ]) and chemotactic markers (IP-10 and eotaxin) relative to healthy individuals. Patients who succumbed to infection produced decreased IL-2, IL-4, IL-12, RANTES, tumor necrosis factor alpha (TNF-α), GRO-α, and MIP-1α relative to patients who survived infection. We also observed that the chemokine CXCL13 was particularly elevated in patients who succumbed to infection. CXCL13 is involved in B cell activation, germinal center development, and antibody maturation, and we observed that CXCL13 levels in blood trended with anti-SARS-CoV-2 antibody levels. Furthermore, patients who succumbed to infection produced high CXCL13 and had a higher ratio of nucleocapsid to RBD antibodies. This study provides insights into SARS-CoV-2 immunity implicating the magnitude and specificity of response in relation to patient outcomes.IMPORTANCE The SARS-CoV-2 pandemic is continuing to impact the global population, and knowledge of the immune response to COVID-19 is still developing. This study assesses the interplay of different parts of the immune system during COVID-19 disease. We demonstrate that COVID-19 patients produce antibodies to three proteins of the COVID-19 virus (SARS-CoV-2) and identify many other immunological proteins that are involved during infection. The data suggest that one of these proteins (CXCL13) may be a novel biomarker for severe COVID-19 that can be readily measured in blood. This information combined with our broad-scale analysis of immune activity during COVID-19 provides new information on the immunological response throughout the course of disease and identifies a novel potential marker for assessing disease severity.

Who Is Really at Risk for Anaphylaxis Due to COVID-19 Vaccine?

The vaccination campaign against the Severe acute respiratory syndrome coronavirus 2 (Sars-Cov-2) started on 8 December 2020 in UK, after the approval of BNT162b2 by the Healthcare products Regulatory Agency (MHRA) [...].

Interpretative immune targets and contemporary position for vaccine development against SARS-CoV-2: A systematic review

The year 2020 started with the emergence of novel coronavirus, severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2), which causes COVID‐19 infection. Soon after the first evidence was reported in Wuhan, China, the World Health Organization declared global public health emergency and imminent need to understand the pathogenicity of the virus was required in limited time. Once the genome sequence of the virus was delineated, scientists across the world started working on the development of vaccines. Although, some laboratories have been using previously developed vaccine platforms from severe acute respiratory syndrome coronavirus (SARS) and middle east respiratory syndrome‐related coronavirus and apply them in COVID‐19 vaccines due to genetic similarities between coronaviruses. We have conducted a literature review to assess the background and current status of COVID‐19 vaccines. The worldwide implementation and strategies for COVID‐19 vaccine development are summarized from studies reported in years 2015–2020. While discussing the vaccine candidates, we have also explained interpretative immune responses of SARS‐CoV‐2 infection. There are several vaccine candidates at preclinical and clinical stages; however, only 42 vaccines are under clinical trials. Therefore, more industry collaborations and financial supports to COVID‐19 studies are needed for mass‐scale vaccine development. To develop effective vaccine platforms against SARS‐CoV‐2, the genetic resemblance with other coronaviruses are being evaluated which may further promote fast‐track trials on previously developed SARS‐CoV vaccines.

Designing of Nucleocapsid Protein Based Novel Multi-epitope Vaccine Against SARS-COV-2 Using Immunoinformatics Approach

The COVID-19 disease is caused by SARS-CoV-2 and spreading rapidly worldwide with extremely high infection rate. Since effective and specific vaccine is not available to combat the deadly COVID-19, the objective of our study was to design a multi-epitope vaccine using immunoinformatics approach with translational implications. Nucleocapsid (N) protein of SARS-CoV-2 is stable, conserved and highly immunogenic along with being less prone to mutations during infection, which makes it a suitable candidate for designing vaccine. In our study, B- and T-cells epitopes were identified from N protein and screened based on crucial parameters to design the multi-epitope vaccine construct. Additionally, human beta-defensin-2 was incorporated into the vaccine construct as an adjuvant along with suitable linkers followed by its further evaluation based on crucial parameters including allergenicity, antigenicity, stability etc. Combined major histocompatibility complexes (MHC-I and MHC-II) binding epitopes presented broader population coverage of the vaccine throughout the world. The three-dimensional structure of vaccine candidate implied strong interaction with toll-like receptor 3 (TLR3) using molecular docking. The vaccine-TLR3 complex was observed to be highly stable during simulation and electrostatic free energy was foremost contributor for stabilization of the structure. Subsequently, in silico cloning of vaccine candidate was carried out to generate the construct into pET-28a(+) expression vector succeeded by its virtual confirmation. Altogether, our results advocate that the designed vaccine candidate could be an effective and promising weapon to fight with COVID-19 infection worldwide.

Computational Immune Proteomics Approach to Target COVID-19

Progress of the omics platforms widens their application to diverse fields, including immunology. This enables a deeper level of knowledge and the provision of a huge amount of data for which management and fruitful integration with the past evidence requires a steadily growing computational effort. In light of this, immunoinformatics emerges as a new discipline placed in between the traditional lab-based investigations and the computational analysis of the biological data. Immunoinformatics make use of tailored bioinformatics tools and data repositories to facilitate the analysis of data from a plurality of disciplines and help drive novel research hypotheses and in silico screening investigations in a fast, reliable, and cost-effective manner. Such computational immunoproteomics studies may as well prepare and guide lab-based investigations, representing valuable technology for the investigation of novel pathogens, to tentatively evaluate specificity of diagnostic products, to forecast on potential adverse effects of vaccines and to reduce the use of animal models. The present manuscript provides an overview of the COVID-19 pandemic and reviews the state of the art of the omics technologies employed in fighting SARS-CoV-2 infections. A comprehensive description of the immunoinformatics approaches and its potential role in contrasting COVID-19 pandemics is provided.

Generation of SARS-CoV-2 S1 Spike Glycoprotein Putative Antigenic Epitopes in Vitro by Intracellular Aminopeptidases

Presentation of antigenic peptides by MHCI is central to cellular immune responses against viral pathogens. While adaptive immune responses versus SARS-CoV-2 can be of critical importance to both recovery and vaccine efficacy, how protein antigens from this pathogen are processed to generate antigenic peptides is largely unknown. Here, we analyzed the proteolytic processing of overlapping precursor peptides spanning the entire sequence of the S1 spike glycoprotein of SARS-CoV-2, by three key enzymes that generate antigenic peptides, aminopeptidases ERAP1, ERAP2, and IRAP. All enzymes generated shorter peptides with sequences suitable for binding onto HLA alleles, but with distinct specificity fingerprints. ERAP1 was the most efficient in generating peptides 8-11 residues long, the optimal length for HLA binding, while IRAP was the least efficient. The combination of ERAP1 with ERAP2 greatly limited the variability of peptide sequences produced. Less than 7% of computationally predicted epitopes were found to be produced experimentally, suggesting that aminopeptidase processing may constitute a significant filter to epitope presentation. These experimentally generated putative epitopes could be prioritized for SARS-CoV-2 immunogenicity studies and vaccine design. We furthermore propose that this in vitro trimming approach could constitute a general filtering method to enhance the prediction robustness for viral antigenic epitopes.

Omics and Bioinformatics Approaches to Identify Novel Antigens for Vaccine Investigation and Development

Despite the outstanding technological advances achieved in the last few decades, infectious diseases remain a major societal challenge. From the variolation carried out in ancient China during the 15th century to the more advanced RNA and DNA vaccines presently available, vaccines have been proven as highly effective therapeutic tools to combat various infectious diseases. Vaccine research and development is now empowered with recent advances in Omics sciences and the developments of powerful bioinformatics tools. This Special Issue has gathered a total of nine original papers, including seven research papers and two reviews, illustrating the use of Omics data and bioinformatics in the research, design and development of vaccines against pathogens and cancer. The integration of knowledge from Omics and Bioinformatics will certainly boost vaccine research and development, leading to novel therapeutic tools against new and old pathogens and cancer in the near future.

Non-synonymous mutations of SARS-CoV-2 leads epitope loss and segregates its variants

The non-synonymous mutations of SARS-CoV-2 isolated from across the world have been identified during the last few months. The surface glycoprotein spike of SARS-CoV-2 forms the most important hotspot for amino acid alterations followed by the ORF1a/ORF1ab poly-proteins. It is evident that the D614G mutation in spike glycoprotein and P4715L in RdRp is the important determinant of SARS-CoV-2 evolution since its emergence. P4715L in RdRp, G251V in ORF3a and S1498F of Nsp3 is associated with the epitope loss that may influence pathogenesis caused by antibody escape variants. The phylogenomics distinguished the ancestral viral samples from China and most part of Asia, isolated since the initial outbreak and the later evolved variants isolated from Europe and Americas. The evolved variants have been found to predominant globally with the loss of epitopes from its proteins. These have implications for SARS-CoV-2 transmission, pathogenesis and immune interventions.

Immunoinformatic Analysis of SARS-CoV-2 Nucleocapsid Protein and Identification of COVID-19 Vaccine Targets

COVID-19 is a worldwide emergency; therefore, there is a critical need for foundational knowledge about B and T cell responses to SARS-CoV-2 essential for vaccine development. However, little information is available defining which determinants of SARS-CoV-2 other than the spike glycoprotein are recognized by the host immune system. In this study, we focus on the SARS-CoV-2 nucleocapsid protein as a suitable candidate target for vaccine formulations. Major B and T cell epitopes of the SARS-CoV-2 N protein are predicted and resulting sequences compared with the homolog immunological domains of other coronaviruses that infect human beings. The most dominant of B cell epitope is located between 176–206 amino acids in the SRGGSQASSRSSSRSRNSSRNSTPGSSRGTS sequence. Further, we identify sequences which are predicted to bind multiple common MHC I and MHC II alleles. Most notably there is a region of potential T cell cross-reactivity within the SARS-CoV-2 N protein position 102–110 amino acids that traverses multiple human alpha and betacoronaviruses. Vaccination strategies designed to target these conserved epitope regions could generate immune responses that are cross-reactive across human coronaviruses, with potential to protect or modulate disease. Finally, these predictions can facilitate effective vaccine design against this high priority virus.

A systematic review of SARS-CoV-2 vaccine candidates

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an emerging virus that is highly pathogenic and has caused the recent worldwide pandemic officially named coronavirus disease (COVID-19). Currently, considerable efforts have been put into developing effective and safe drugs and vaccines against SARS-CoV-2. Vaccines, such as inactivated vaccines, nucleic acid-based vaccines, and vector vaccines, have already entered clinical trials. In this review, we provide an overview of the experimental and clinical data obtained from recent SARS-CoV-2 vaccines trials, and highlight certain potential safety issues that require consideration when developing vaccines. Furthermore, we summarize several strategies utilized in the development of vaccines against other infectious viruses, such as severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV), with the aim of aiding in the design of effective therapeutic approaches against SARS-CoV-2.

Vaccine Candidates against Coronavirus Infections. Where Does COVID-19 Stand?

Seven years after the Middle East respiratory syndrome (MERS) outbreak, a new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) made its first appearance in a food market in Wuhan, China, drawing an entirely new course to our lives. As the virus belongs to the same genus of MERS and SARS, researchers have been trying to draw lessons from previous outbreaks to find a potential cure. Although there were five Phase I human vaccine trials against SARS and MERS, the lack of data in humans provided us with limited benchmarks that could help us design a new vaccine for Coronavirus disease 2019 (COVID-19). In this review, we showcase the similarities in structures of virus components between SARS-CoV, MERS-CoV, and SARS-CoV-2 in areas relevant to vaccine design. Using the ClinicalTrials.gov and World Health Organization (WHO) databases, we shed light on the 16 current approved clinical trials worldwide in search for a COVID-19 vaccine. The different vaccine platforms being tested are Bacillus Calmette-Guérin (BCG) vaccines, DNA and RNA-based vaccines, inactivated vaccines, protein subunits, and viral vectors. By thoroughly analyzing different trials and platforms, we also discuss the advantages and disadvantages of using each type of vaccine and how they can contribute to the design of an adequate vaccine for COVID-19. Studying past efforts invested in conducting vaccine trials for MERS and SARS will provide vital insights regarding the best approach to designing an effective vaccine against COVID-19.