Immunoinformatics-aided identification of T cell and B cell epitopes in the surface glycoprotein of 2019-nCoV

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.

MultiTEP-Based Vaccines Targeting SARS-CoV-2 Spike Protein IgG Epitopes Elicit Robust Binding Antibody Titers with Limited Virus-Neutralizing Activity

Within the last two decades, SARS-CoV-2 was the third zoonotic severe acute respiratory betacoronavirus (sarbecovirus) to infect humans, following SARS and MERS. The disruptions caused by the pandemic underscore the need for a universal vaccine against respiratory betacoronaviruses. Our group previously developed the universal platform for vaccine development, MultiTEP, which has been utilized in this study to generate a range of SARS-CoV-2 epitope vaccine candidates. We prepared and characterized 18 vaccines incorporating small peptide fragments from SARS-CoV-2 Spike protein fused with the MultiTEP sequence using overlapping PCR. Wild-type mice were immunized intramuscularly with the immunogen formulated in AdvaxCpG adjuvant. Serum antibodies were detected by ELISA, surrogate neutralization, and pseudovirus neutralization assays. Finally, the most promising vaccine candidate was administered to three non-human primates. All vaccines generated high titers of spike-binding IgG antibodies. However, only three vaccines generated antibodies that blocked RBD binding to the ACE2 receptor in a surrogate virus neutralization assay. However, none of the vaccines induced antibodies able to neutralize pseudotype viruses, including after the administration of the lead vaccine to NHPs. MultiTEP-based COVID-19 vaccines elicited robust, IgG-binding responses against the Spike protein in mice and non-human primates, but these antibodies were not neutralizing, underscoring the need to refine this approach further.

The Main Mechanisms of Mesenchymal Stem Cell-Based Treatments against COVID-19

BACKGROUND

Coronavirus disease 2019 (COVID-19) has a clinical manifestation of hypoxic respiratory failure and acute respiratory distress syndrome. However, COVID-19 still lacks of effective clinical treatments so far. As a promising potential treatment against COVID-19, stem cell therapy raised recently and had attracted much attention. Here we review the mechanisms of mesenchymal stem cell-based treatments against COVID-19, and provide potential cues for the effective control of COVID-19 in the future.

METHODS

Literature is obtained from databases PubMed and Web of Science. Key words were chosen for COVID- 19, acute respiratory syndrome coronavirus 2, mesenchymal stem cells, stem cell therapy, and therapeutic mechanism. Then we summarize and critically analyze the relevant articles retrieved.

RESULTS

Mesenchymal stem cell therapy is a potential effective treatment against COVID-19. Its therapeutic efficacy is mainly reflected in reducing severe pulmonary inflammation, reducing lung injury, improving pulmonary function, protecting and repairing lung tissue of the patients. Possible therapeutic mechanisms might include immunoregulation, anti-inflammatory effect, tissue regeneration, anti-apoptosis effect, antiviral, and antibacterial effect, MSC - EVs, and so on.

CONCLUSION

Mesenchymal stem cells can effectively treat COVID-19 through immunoregulation, anti-inflammatory, tissue regeneration, anti-apoptosis, anti-virus and antibacterial, MSC - EVs, and other ways. Systematically elucidating the mechanisms of mesenchymal stem cell-based treatments for COVID-19 will provide novel insights into the follow-up research and development of new therapeutic strategies in next step.

Physicochemical properties-based hybrid machine learning technique for the prediction of SARS-CoV-2 T-cell epitopes as vaccine targets

Majority of the existing SARS-CoV-2 vaccines work by presenting the whole pathogen in the attenuated form to immune system to invoke an immune response. On the other hand, the concept of a peptide based vaccine (PBV) is based on the identification and chemical synthesis of only immunodominant peptides known as T-cell epitopes (TCEs) to induce a specific immune response against a particular pathogen. However PBVs have received less attention despite holding huge untapped potential for boosting vaccine safety and immunogenicity. To identify these TCEs for designing PBV, wet-lab experiments are difficult, expensive, and time-consuming. Machine learning (ML) techniques can accurately predict TCEs, saving time and cost for speedy vaccine development. This work proposes novel hybrid ML techniques based on the physicochemical properties of peptides to predict SARS-CoV-2 TCEs. The proposed hybrid ML technique was evaluated using various ML model evaluation metrics and demonstrated promising results. The hybrid technique of decision tree classifier with chi-squared feature weighting technique and forward search optimal feature searching algorithm has been identified as the best model with an accuracy of 98.19%. Furthermore, K-fold cross-validation (KFCV) was performed to ensure that the model is reliable and the results indicate that the hybrid random forest model performs consistently well in terms of accuracy with respect to other hybrid approaches. The predicted TCEs are highly likely to serve as promising vaccine targets, subject to evaluations both in-vivo and in-vitro. This development could potentially save countless lives globally, prevent future epidemic-scale outbreaks, and reduce the risk of mutation escape.

COVID-19: Recent Insight in Genomic Feature, Pathogenesis, Immunological Biomarkers, Treatment Options and Clinical Updates on SARS-CoV-2

SARS-CoV-2 is a highly contagious and transmissible viral infection that first emerged in 2019 and since then has sparked an epidemic of severe respiratory problems identified as "coronavirus disease 2019" (COVID-19) that causes a hazard to human life and safety. The virus developed mainly from bats. The current epidemic has presented a significant warning to life across the world by showing mutation. There are different tests available for testing Coronavirus, and RT-PCR is the best, giving more accurate results, but it is also time-consuming. There are different options available for treating n-CoV-19, which include medications such as Remdesivir, corticosteroids, plasma therapy, Dexamethasone therapy, etc. The development of vaccines such as BNT126b2, ChAdOX1, mRNA-1273 and BBIBP-CorV has provided great relief in dealing with the virus as they decreased the mortality rate. BNT126b2 and ChAdOX1 are two n-CoV vaccines found to be most effective in controlling the spread of infection. In the future, nanotechnology-based vaccines and immune engineering techniques can be helpful for further research on Coronavirus and treatment of this deadly virus. The existing knowledge about the existence of SARS-CoV-2, along with its variants, is summarized in this review. This review, based on recently published findings, presents the core genetics of COVID-19, including heritable characteristics, pathogenesis, immunological biomarkers, treatment options and clinical updates on the virus, along with patents.

Designing a multi-epitope vaccine against Peptostreptococcus anaerobius based on an immunoinformatics approach

Peptostreptococcus anaerobius is an anaerobic bacterium, which has been found selectively en-riched in the fecal and mucosal microbiota of colorectal cancer (CRC) patients. Emerging evidence suggest P. anaerobius may contribute to the development of CRC in human. In this study, we designed a multi-epitope chimeric vaccine against P. anaerobius PCWBR2, a recently identified adhesin that interacts directly with colon cell lines by binding α2/β1 integrin frequently overexpressed in human CRC tumors and cell lines. Immunoinformatics tools predicted six cytotoxic T lymphocyte epitopes, five helper T lymphocyte epitopes, and six linear B lymphocyte epitopes. The predicted epitopes were joined with AAY or GPGPG linkers and a previously reported TLR4 agonist was added to the vaccine construct's N terminal as an adjuvant using EAAAK linkers and the order of epitopes was optimized. Further in silico analysis revealed that the vaccine construct possesses satisfactory antigenicity, allergenicity, solubility, physicochemical properties, adjuvant-TLR4 molecular docking, and immune profile characteristics. Our study provided a promising design for vaccines against P. anaerobius.

De novo design of anti-variant COVID-19 vaccine

Recent studies highlight the effectiveness of hybrid Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2) vaccines combining wild-type nucleocapsid and Spike proteins. We have further enhanced this strategy by incorporating delta and omicron variants' spike protein mutations. Both delta and omicron mark the shifts in viral transmissibility and severity in unvaccinated and vaccinated patients. So their mutations are highly crucial for future viral variants also. Omicron is particularly adept at immune evasion by mutating spike epitopes. The rapid adaptations of Omicron and sub-variants to spike-based vaccines and simultaneous transmissibility underline the urgency for new vaccines in the continuous battle against SARS-CoV-2. Therefore, we have added three persistent T-cell-stimulating nucleocapsid peptides similar to homologous sequences from seasonal Human Coronaviruses (HuCoV) and an envelope peptide that elicits a strong T-cell immune response. These peptides are clustered in the hybrid spike's cytoplasmic region with non-immunogenic linkers, enabling systematic arrangement. AlphaFold (Artificial intelligence-based model building) analysis suggests omitting the transmembrane domain enhances these cytoplasmic epitopes' folding efficiency which can ensure persistent immunity for CD4+ structural epitopes. Further molecular dynamics simulations validate the compact conformation of the modeled structures and a flexible C-terminus region. Overall, the structures show stability and less conformational fluctuation throughout the simulation. Also, the AlphaFold predicted structural epitopes maintained their folds during simulation to ensure the specificity of CD4+ T-cell response after vaccination. Our proposed approach may provide options for incorporating diverse anti-viral T-cell peptides, similar to HuCoV, into linker regions. This versatility can be promising to address outbreaks and challenges posed by various viruses for effective management in this era of innovative vaccines.

Design and Assessment of a Novel In Silico Approach for Developing a Next-Generation Multi-Epitope Universal Vaccine Targeting Coronaviruses

In the past two decades, there have been three coronavirus outbreaks that have caused significant economic and health crises. Biologists predict that more coronaviruses may emerge in the near future. Therefore, it is crucial to develop preventive vaccines that can effectively combat multiple coronaviruses. In this study, we employed computational approaches to analyze genetically related coronaviruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its variants, focusing on the spike glycoprotein as a potential vaccine candidate. By predicting common epitopes, we identified the top epitopes and combined them to create a multi-epitope candidate vaccine. The overall quality of the candidate vaccine was validated through in silico analyses, confirming its antigenicity, immunogenicity, and stability. In silico docking and simulation studies suggested a stable interaction between the multi-epitope candidate vaccine and human toll-like receptor 2 (TLR2). In silico codon optimization and cloning were used to further explore the successful expression of the designed candidate vaccine in a prokaryotic expression system. Based on computational analysis, the designed candidate vaccine was found to be stable and non-allergenic in the human body. The efficiency of the multi-epitope vaccine in triggering effective cellular and humoral immune responses was assessed through immune stimulation, demonstrating that the designed candidate vaccine can elicit specific immune responses against multiple coronaviruses. Therefore, it holds promise as a potential candidate vaccine against existing and future coronaviruses.

Immunology of SARS-CoV-2 infection and vaccination

Comprehensive elucidation of humoral immune responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and vaccination is critical for understanding coronavirus disease 2019 (COVID-19) pathogenesis in general and developing antibody-based diagnostic and therapeutic strategies specifically. Following the emergence of SARS-CoV-2, significant scientific research has been conducted worldwide using omics, sequencing and immunologic approaches. These studies have been critical to the successful development of vaccines. Here, the current understanding of SARS-CoV-2 immunogenic epitopes, humoral immunity to SARS-CoV-2 structural proteins and non-structural proteins, SARS-CoV-2-specific antibodies, and T-cell responses in convalescents and vaccinated individuals are reviewed. Additionally, we explore the integrated analysis of proteomic and metabolomic data to examine mechanisms of organ injury and identify potential biomarkers. Insight into the immunologic diagnosis of COVID-19 and improvements of laboratory methods are highlighted.

Identification of B-Cell Linear Epitopes in the Nucleocapsid (N) Protein B-Cell Linear Epitopes Conserved among the Main SARS-CoV-2 Variants

The Nucleocapsid (N) protein is highlighted as the main target for COVID-19 diagnosis by antigen detection due to its abundance in circulation early during infection. However, the effects of the described mutations in the N protein epitopes and the efficacy of antigen testing across SARS-CoV-2 variants remain controversial and poorly understood. Here, we used immunoinformatics to identify five epitopes in the SARS-CoV-2 N protein (N_(34-48), N_(89-104), N_(185-197), N_(277-287), and N_(378-390)) and validate their reactivity against samples from COVID-19 convalescent patients. All identified epitopes are fully conserved in the main SARS-CoV-2 variants and highly conserved with SARS-CoV. Moreover, the epitopes N_(185-197) and N_(277-287) are highly conserved with MERS-CoV, while the epitopes N_(34-48), N_(89-104), N_(277-287), and N_(378-390) are lowly conserved with common cold coronaviruses (229E, NL63, OC43, HKU1). These data are in accordance with the observed conservation of amino acids recognized by the antibodies 7R98, 7N0R, and 7CR5, which are conserved in the SARS-CoV-2 variants, SARS-CoV and MERS-CoV but lowly conserved in common cold coronaviruses. Therefore, we support the antigen tests as a scalable solution for the population-level diagnosis of SARS-CoV-2, but we highlight the need to verify the cross-reactivity of these tests against the common cold coronaviruses.

Bioinformatics and immunoinformatics approach to develop potent multi-peptide vaccine for coxsackievirus B3 capable of eliciting cellular and humoral immune response

Coxsackievirus B3 (CVB3) is a viral pathogen of various human disorders with no effective preventative interventions. Herein, we aimed to design a chimeric vaccine construct for CVB3 using reverse vaccinology and immunoinformatics approaches by screening the whole viral polyprotein sequence. Firstly, screening and mapping of viral polyprotein to predict 21 immunodominant epitopes (B-cell, CD8+ and CD4+ T-cell epitopes), fused with an adjuvant (Resuscitation-promoting factor), appropriate linkers, HIV-TAT peptide, Pan DR epitope, and 6His-tag to assemble a multi-epitope vaccine construct. The chimeric construct is predicted as probable antigen, non-allergen, stable, possess encouraging physicochemical features, and indicates a broader population coverage (98 %). The tertiary structure of the constructed vaccine was predicted and refined, and its interaction with the Toll-like receptor 4 (TLR4) was investigated through molecular docking and dynamics simulation. Computational cloning of the construct was carried out in pET28a (+) plasmid to guarantee the higher expression of the vaccine protein. Lastly, in silico immune simulation foreseen that humoral and cellular immune responses would be elicited in response to the administration of such a potent chimeric construct. Thus, the design constructed could vaccinate against CVB3 infection and various CVB serotypes. However, further in vitro/in vivo research must assess its safety and effectiveness.

A study on the design of an in silico self-amplifying mRNA vaccine against Nipah virus using immunoinformatics

The scientific community continues to be impressed with RNA-based vaccines with great efficacy, quick synthesis and speed-to-market. The traditional vaccine may require large doses or repeat injections to achieve an expression for protection against the virus; the self-amplifying mRNA vaccine addresses this limitation. Therefore, a thorough examination of the most antigenic component of the Nipah virus was carried out to design the coding sequence of an antigen, which will provoke a virus-specific immune response. After that, we predicted and evaluated epitopes from NiV G-protein. We employed 8 HTL, 2 CTL and 3 B-cell epitopes. The study of structural compatibility was done by performing docking between HLA alleles and epitopes to get insights into the immune response of epitopes. The entire peptide coding sequence of an antigen was linked using a linker to design the structure of the vaccine. Physicochemical parameters of the designed vaccine constructs were assessed using a protparam server. Later, the vaccine sequence was converted into cDNA. We inserted a gene-expressing replicase at the start of a coding sequence for self-amplification. Next, to formulate the final version of vaccine signal sequences were added. Based on these findings, this mRNA vaccine appears to be a promising option against the Nipah virus.Communicated by Ramaswamy H. Sarma.

A hepatitis B virus core antigen-based virus-like particle vaccine expressing SARS-CoV-2 B and T cell epitopes induces epitope-specific humoral and cell-mediated immune responses but confers limited protection against SARS-CoV-2 infection

The hepatitis B virus core antigen (HBcAg) tolerates insertion of foreign epitopes and maintains its ability to self-assemble into virus-like particles (VLPs). We constructed a ∆HBcAg-based VLP vaccine expressing three predicted severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) B and T cell epitopes and determined its immunogenicity and protective efficacy. The recombinant ∆HBcAg-SARS-CoV-2 protein was expressed in Escherichia coli, purified, and shown to form VLPs. K18-hACE2 transgenic C57BL/6 mice were immunized intramuscularly with ∆HBcAg VLP control (n = 15) or ∆HBcAg-SARS-CoV-2 VLP vaccine (n = 15). One week after the 2nd booster and before virus challenge, five ∆HBcAg-SARS-CoV-2 vaccinated mice were euthanized to evaluate epitope-specific immune responses. There is a statistically significant increase in epitope-specific Immunoglobulin G (IgG) response, and statistically higher interleukin 6 (IL-6) and monocyte chemoattractant protein-1 (MCP-1) expression levels in ∆HBcAg-SARS-CoV-2 VLP-vaccinated mice compared to ∆HBcAg VLP controls. While not statistically significant, the ∆HBcAg-SARS-CoV-2 VLP mice had numerically more memory CD8+ T-cells, and 3/5 mice also had numerically higher levels of interferon gamma (IFN-γ) and tumor necrosis factor (TNF). After challenge with SARS-CoV-2, ∆HBcAg-SARS-CoV-2 immunized mice had numerically lower viral RNA loads in the lung, and slightly higher survival, but the differences are not statistically significant. These results indicate that the ∆HBcAg-SARS-CoV-2 VLP vaccine elicits epitope-specific humoral and cell-mediated immune responses but they were insufficient against SARS-CoV-2 infection.

Immunoinformatic-Based Multi-Epitope Vaccine Design for Co-Infection of Mycobacterium tuberculosis and SARS-CoV-2

(1) Background: Many co-infections of Mycobacterium tuberculosis (MTB) and severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) have emerged since the occurrence of the SARS-CoV-2 pandemic. This study aims to design an effective preventive multi-epitope vaccine against the co-infection of MTB and SARS-CoV-2. (2) Methods: The three selected proteins (spike protein, diacylglycerol acyltransferase, and low molecular weight T-cell antigen TB8.4) were predicted using bioinformatics, and 16 epitopes with the highest ranks (10 helper T lymphocyte epitopes, 2 CD8⁺ T lymphocytes epitopes, and 4 B-cell epitopes) were selected and assembled into the candidate vaccine referred to as S7D5L4. The toxicity, sensitization, stability, solubility, antigenicity, and immunogenicity of the S7D5L4 vaccine were evaluated using bioinformatics tools. Subsequently, toll-like receptor 4 docking simulation and discontinuous B-cell epitope prediction were performed. Immune simulation and codon optimization were carried out using immunoinformatics and molecular biology tools. (3) Results: The S7D5L4 vaccine showed good physical properties, such as solubility, stability, non-sensitization, and non-toxicity. This vaccine had excellent antigenicity and immunogenicity and could successfully simulate immune responses in silico. Furthermore, the normal mode analysis of the S7D5L4 vaccine and toll-like receptor 4 docking simulation demonstrated that the vaccine had docking potential and a stable reaction. (4) Conclusions: The S7D5L4 vaccine designed to fight against the co-infection of MTB and SARS-CoV-2 may be safe and effective. The protective efficacy of this promising vaccine should be further verified using in vitro and in vivo experiments.

Advances in SARS-CoV-2 receptor-binding domain-based COVID-19 vaccines

INTRODUCTION

The Coronavirus Disease 2019 (COVID-19) pandemic has caused devastating human and economic costs. Vaccination is an important step in controlling the pandemic. Severe acute respiratory coronavirus-2 (SARS-CoV-2), the causative agent of COVID-19, infects cells by binding a cellular receptor through the receptor-binding domain (RBD) within the S1 subunit of the spike (S) protein. Viral entry and membrane fusion are mediated by the S2 subunit.

AREAS COVERED

SARS-CoV-2 S protein, particularly RBD, serves as an important target for vaccines. Here we review the structure and function of SARS-CoV-2 S protein and its RBD, summarize current COVID-19 vaccines targeting the RBD, and outline potential strategies for improving RBD-based vaccines. Overall, this review provides important information that will facilitate rational design and development of safer and more effective COVID-19 vaccines.

EXPERT OPINION

The S protein of SARS-CoV-2 harbors numerous mutations, mostly in the RBD, resulting in multiple variant strains. Although many COVID-19 vaccines targeting the RBD of original virus strain (and previous variants) can prevent infection of these strains, their ability against recent dominant variants, particularly Omicron and its offspring, is significantly reduced. Collective efforts are needed to develop effective broad-spectrum vaccines to control current and future variants that have pandemic potential.

Tetraspanin-enriched Microdomain Containing CD151, CD9, and TSPAN 8 - Potential Mediators of Entry and Exit Mechanisms in Respiratory Viruses Including SARS-CoV-2

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which originated in Wuhan, the Hubei region of China, has become a pandemic worldwide. It can transmit through droplets and enter via oral, nasal, and eye mucous membranes. It consists of single-stranded RNA (positive-sense), nonstructural proteins including enzymes and transcriptional proteins, and structural proteins such as Spike, Membrane, Envelope, and Nucleocapsid -proteins. SARS-CoV-2 mediates S-proteins entry and exit via binding to host cell surface proteins like tetraspanins. The transmembrane tetraspanins, CD151, CD9, and tetraspanin 8 (TSPAN8), facilitate the entry of novel coronaviruses by scaffolding host cell receptors and proteases. Also, CD151 was reported to increase airway hyperresponsiveness to calcium and nuclear viral export signaling. They may facilitate entry and exit by activating the serine proteases required to prime S-proteins in tetraspanin-enriched microdomains (TEMs). This article updates recent advances in structural proteins, their epitopes and putative receptors, and their regulation by proteases associated with TEMs. This review furnishes recent updates on the role of CD151 in the pathophysiology of SARS-CoV-2. We describe the role of CD151 in a possible mechanism of entry and exit in the airway, a major site for infection of SARS-CoV-2. We also updated current knowledge on the role of CD9 and TSPAN 8 in the entry and exit mechanism of coronaviruses. Finally, we discussed the importance of some small molecules which target CD151 as possible targeted therapeutics for COVID-19. In conclusion, this study could identify new targets and specific therapeutics to control emerging virus infections.

SARS-CoV-2 Omicron (BA.1 and BA.2) specific novel CD8+ and CD4+ T cell epitopes targeting spike protein

The Omicron (BA.1/B.1.1.529) variant of SARS-CoV-2 harbors an alarming 37 mutations on its spike protein, reducing the efficacy of current COVID-19 vaccines. In this study, we identified CD8+ and CD4+ T cell epitopes from SARS-CoV-2 S protein mutants. To identify the highest quality CD8 and CD4 epitopes from the Omicron variant, we selected epitopes with a high binding affinity towards both MHC I and MHC II molecules. We applied other clinical checkpoint predictors, including immunogenicity, antigenicity, allergenicity, instability and toxicity. Subsequently, we found eight Omicron (BA.1/B.1.1.529) specific CD8+ and eleven CD4+ T cell epitopes with a world population coverage of 76.16% and 97.46%, respectively. Additionally, we identified common epitopes across Omicron BA.1 and BA.2 lineages that target mutations critical to SARS-CoV-2 virulence. Further, we identified common epitopes across B.1.1.529 and other circulating SARS-CoV-2 variants, such as B.1.617.2 (Delta). We predicted CD8 epitopes' binding affinity to murine MHC alleles to test the vaccine candidates in preclinical models. The CD8 epitopes were further validated using our previously developed software tool PCOptim. We then modeled the three-dimensional structures of our top CD8 epitopes to investigate the binding interaction between peptide-MHC and peptide-MHC-TCR complexes. Notably, our identified epitopes are targeting the mutations on the RNA-binding domain and the fusion sites of S protein. This could potentially eliminate viral infections and form long-term immune responses compared to relatively short-lived mRNA vaccines and maximize the efficacy of vaccine candidates against the current pandemic and potential future variants.

Designing a multi-epitope vaccine against coxsackievirus B based on immunoinformatics approaches

Coxsackievirus B (CVB) is one of the major viral pathogens of human myocarditis and cardiomyopathy without any effective preventive measures; therefore, it is necessary to develop a safe and efficacious vaccine against CVB. Immunoinformatics methods are both economical and convenient as in-silico simulations can shorten the development time. Herein, we design a novel multi-epitope vaccine for the prevention of CVB by using immunoinformatics methods. With the help of advanced immunoinformatics approaches, we predicted different B-cell, cytotoxic T lymphocyte (CTL), and helper T lymphocyte (HTL) epitopes, respectively. Subsequently, we constructed the multi-epitope vaccine by fusing all conserved epitopes with appropriate linkers and adjuvants. The final vaccine was found to be antigenic, non-allergenic, and stable. The 3D structure of the vaccine was then predicted, refined, and evaluated. Molecular docking and dynamics simulation were performed to reveal the interactions between the vaccine with the immune receptors MHC-I, MHC-II, TLR3, and TLR4. Finally, to ensure the complete expression of the vaccine protein, the sequence of the designed vaccine was optimized and further performed in-silico cloning. In conclusion, the molecule designed in this study could be considered a potential vaccine against CVB infection and needed further experiments to evaluate its safety and efficacy.

Candidate Multi-Epitope Vaccine against Corona B.1.617 Lineage: In Silico Approach

Various mutations have accumulated since the first genome sequence of SARS-CoV2 in 2020. Mutants of the virus carrying the D614G and P681R mutations in the spike protein are increasingly becoming dominant all over the world. The two mutations increase the viral infectivity and severity of the disease. This report describes an in silico design of SARS-CoV-2 multi-epitope carrying the spike D614G and P681R mutations. The designed vaccine harbors the D614G mutation that increases viral infectivity, fitness, and the P681R mutation that enhances the cleavage of S to S1 and S2 subunits. The designed multi-epitope vaccine showed an antigenic property with a value of 0.67 and the immunogenicity of the predicted vaccine was calculated and yielded 3.4. The vaccine construct is predicted to be non-allergenic, thermostable and has hydrophilic nature. The combination of the selected CTL and HTL epitopes in the vaccine resulted in 96.85% population coverage globally. Stable interactions of the vaccine with Toll-Like Receptor 4 were tested by docking studies. The multi-epitope vaccine can be a good candidate against highly infecting SARS-CoV-2 variants.

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.

A common allele of HLA mediates asymptomatic SARS-CoV-2 infection

Despite some inconsistent reporting of symptoms, studies have demonstrated that at least 20% of individuals infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) will remain asymptomatic. Although most global efforts have focused on understanding factors underlying severe illness in COVID-19 (coronavirus disease of 2019), the examination of asymptomatic infection provides a unique opportunity to consider early disease and immunologic features promoting rapid viral clearance. Owing to its critical role in the immune response, we postulated that variation in the human leukocyte antigen (HLA) loci may underly processes mediating asymptomatic infection. We enrolled 29,947 individuals registered in the National Marrow Donor Program for whom high-resolution HLA genotyping data were available in the UCSF Citizen Science smartphone-based study designed to track COVID-19 symptoms and outcomes. Our discovery cohort (n=1428) was comprised of unvaccinated, self-identified subjects who reported a positive test result for SARS-CoV-2. We tested for association of five HLA loci (HLA-A, -B, -C, -DRB1, -DQB1) with disease course and identified a strong association of HLA-B*15:01 with asymptomatic infection, and reproduced this association in two independent cohorts. Suggesting that this genetic association is due to pre-existing T-cell immunity, we show that T cells from pre-pandemic individuals carrying HLA-B*15:01 were reactive to the immunodominant SARS-CoV-2 S-derived peptide NQKLIANQF, and 100% of the reactive cells displayed memory phenotype. Finally, we characterize the protein structure of HLA-B*15:01-peptide complexes, demonstrating that the NQKLIANQF peptide from SARS-CoV-2, and the highly homologous NQKLIANAF from seasonal coronaviruses OC43-CoV and HKU1-CoV, share similar ability to be stabilized and presented by HLA-B*15:01, providing the molecular basis for T-cell cross-reactivity and HLA-B*15:01-mediated pre-existing immunity.

Dynamic SARS-CoV-2 emergence algorithm for rationally-designed logical next-generation vaccines

SARS-CoV-2 worldwide spread and evolution has resulted in variants containing mutations resulting in immune evasive epitopes that decrease vaccine efficacy. We acquired SARS-CoV-2 positive clinical samples and compared the worldwide emerged spike mutations from Variants of Concern/Interest, and developed an algorithm for monitoring the evolution of SARS-CoV-2 in the context of vaccines and monoclonal antibodies. The algorithm partitions logarithmic-transformed prevalence data monthly and Pearson's correlation determines exponential emergence of amino acid substitutions (AAS) and lineages. The SARS-CoV-2 genome evaluation indicated 49 mutations, with 44 resulting in AAS. Nine of the ten most worldwide prevalent (>70%) spike protein changes have Pearson's coefficient r > 0.9. The tenth, D614G, has a prevalence >99% and r-value of 0.67. The resulting algorithm is based on the patterns these ten substitutions elucidated. The strong positive correlation of the emerged spike protein changes and algorithmic predictive value can be harnessed in designing vaccines with relevant immunogenic epitopes. Monitoring, next-generation vaccine design, and mAb clinical efficacy must keep up with SARS-CoV-2 evolution, as the virus is predicted to remain endemic.

Immunoinformatics-Based Identification of B and T Cell Epitopes in RNA-Dependent RNA Polymerase of SARS-CoV-2

INTRODUCTION

The ongoing coronavirus disease 2019 (COVID-19), which emerged in December 2019, is a serious health concern throughout the world. Despite massive COVID-19 vaccination on a global scale, there is a rising need to develop more effective vaccines and drugs to curb the spread of coronavirus.

METHODOLOGY

In this study, we screened the amino acid sequence of the RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2 (the causative agent of COVID-19) for the identification of B and T cell epitopes using various immunoinformatic tools. These identified potent B and T cell epitopes with high antigenicity scores were linked together to design the multi-epitope vaccine construct. The physicochemical properties, overall quality, and stability of the designed vaccine construct were confirmed by suitable bioinformatic tools.

RESULTS

After proper in silico prediction and screening, we identified 3 B cell, 18 CTL, and 10 HTL epitopes from the RdRp protein sequence. The screened epitopes were non-toxic, non-allergenic, and highly antigenic in nature as revealed by appropriate servers. Molecular docking revealed stable interactions of the designed multi-epitope vaccine with human TLR3. Moreover, in silico immune simulations showed a substantial immunogenic response of the designed vaccine.

CONCLUSIONS

These findings suggest that our designed multi-epitope vaccine possessing intrinsic T cell and B cell epitopes with high antigenicity scores could be considered for the ongoing development of peptide-based novel vaccines against COVID-19. However, further in vitro and in vivo studies need to be performed to confirm our in silico observations.

Immunology to Immunotherapeutics of SARS-CoV-2: Identification of Immunogenic Epitopes for Vaccine Development

The emergence of COVID19 pandemic caused by SARS-CoV-2 virus has created a global public health and socio-economic crisis. Immunoinformatics-based approaches to investigate the potential antigens is the fastest way to move towards a multiepitope-based vaccine development. This review encompasses the underlying mechanisms of pathogenesis, innate and adaptive immune signaling along with evasion pathways of SARS-CoV-2. Furthermore, it compiles the promiscuous peptides from in silico studies which are subjected to prediction of cytokine milieu using web-based servers. Out of the 434 peptides retrieved from all studies, we have identified 33 most promising T cell vaccine candidates. This review presents a list of the most potential epitopes from several proteins of the virus based on their immunogenicity, homology, conservancy and population coverage studies. These epitopes can form a basis of second generation of vaccine development as the first generation vaccines in various stages of trials mostly focus only on Spike protein. We therefore, propose them as most potential candidates which can be taken up immediately for confirmation by experimental studies.

SARS-CoV-2 infection: Pathogenesis, Immune Responses, Diagnosis

COVID-19 has emerged as the most alarming infection of the present time instigated by the virus SARS-CoV-2. In spite of advanced research technologies, the exact pathophysiology and treatment of the condition still need to be explored. However, SARS-CoV-2 has several structural and functional similarities that resemble SARS-CoV and MERS-CoV which may be beneficial in exploring the possible treatment and diagnostic strategies for SARS-CoV-2. This review discusses the pathogen phenotype, genotype, replication, pathophysiology, elicited immune response and emerging variants of SARS-CoV-2 and their similarities with other similar viruses. SARS-CoV-2 infection is detected by a number of diagnostics techniques, their advantages and limitations are also discussed in detail. The review also focuses on nanotechnology-based easy and fast detection of SARS-CoV-2 infection. Various pathways which might play a vital role during SARS-CoV-2 infection have been elaborately discussed since immune response plays a major role during viral infections.

Vaccines platforms and COVID-19: what you need to know

BACKGROUND

The novel SARS-CoV-2, responsible for the COVID-19 pandemic, is the third zoonotic coronavirus since the beginning of the 21 first century, and it has taken more than 6 million human lives because of the lack of immunity causing global economic losses. Consequently, developing a vaccine against the virus represents the fastest way to finish the threat and regain some "normality."

OBJECTIVE

Here, we provide information about the main features of the most important vaccine platforms, some of them already approved, to clear common doubts fostered by widespread misinformation and to reassure the public of the safety of the vaccination process and the different alternatives presented.

METHODS

Articles published in open access databases until January 2022 were identified using the search terms "SARS-CoV-2," "COVID-19," "Coronavirus," "COVID-19 Vaccines," "Pandemic," COVID-19, and LMICs or their combinations.

DISCUSSION

Traditional first-generation vaccine platforms, such as whole virus vaccines (live attenuated and inactivated virus vaccines), as well as second-generation vaccines, like protein-based vaccines (subunit and viral vector vaccines), and third-generation vaccines, such as nanoparticle and genetic vaccines (mRNA vaccines), are described.

CONCLUSIONS

SARS-CoV-2 sequence information obtained in a record time provided the basis for the fast development of a COVID-19 vaccine. The adaptability characteristic of the new generation of vaccines is changing our capability to react to emerging threats to future pandemics. Nevertheless, the slow and unfair distribution of vaccines to low- and middle-income countries and the spread of misinformation are a menace to global health since the unvaccinated will increase the chances for resurgences and the surge of new variants that can escape the current vaccines.

Viral informatics: bioinformatics-based solution for managing viral infections

Several new viral infections have emerged in the human population and establishing as global pandemics. With advancements in translation research, the scientific community has developed potential therapeutics to eradicate or control certain viral infections, such as smallpox and polio, responsible for billions of disabilities and deaths in the past. Unfortunately, some viral infections, such as dengue virus (DENV) and human immunodeficiency virus-1 (HIV-1), are still prevailing due to a lack of specific therapeutics, while new pathogenic viral strains or variants are emerging because of high genetic recombination or cross-species transmission. Consequently, to combat the emerging viral infections, bioinformatics-based potential strategies have been developed for viral characterization and developing new effective therapeutics for their eradication or management. This review attempts to provide a single platform for the available wide range of bioinformatics-based approaches, including bioinformatics methods for the identification and management of emerging or evolved viral strains, genome analysis concerning the pathogenicity and epidemiological analysis, computational methods for designing the viral therapeutics, and consolidated information in the form of databases against the known pathogenic viruses. This enriched review of the generally applicable viral informatics approaches aims to provide an overview of available resources capable of carrying out the desired task and may be utilized to expand additional strategies to improve the quality of translation viral informatics research.

Lessons from SARS‑CoV‑2 and its variants (Review)

COVID-19 has swept through mainland China by human-to-human transmission. The rapid spread of SARS-CoV-2 and its variants, including the currently prevalent Omicron strain, pose a serious threat worldwide. The present review summarizes epidemiological investigation and etiological analysis of genomic, epidemiological, and pathological characteristics of the original strain and its variants, as well as progress in diagnosis and treatment. Prevention and control measures used during the current Omicron pandemic are discussed to provide further knowledge of SARS-CoV-2.

Identification of vaccine candidate against Omicron variant of SARS-CoV-2 using immunoinformatic approaches

Despite the availability of COVID-19 vaccines, additional more potent vaccines are still required against the emerging variations of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In the present investigation, we have identified a promising vaccine candidate against the Omicron (B.1.1.529) using immunoinformatics approaches. Various available tools like, the Immune Epitope Database server resource, and NetCTL-1.2, have been used for the identification of the promising T-cell and B-cell epitopes. The molecular docking was performed to check the interaction of TLR-3 receptors and validated 3D model of vaccine candidate. The codon optimization was done followed by cloning using SnapGene. Finally, In-silico immune simulation profile was also checked. The identified T-cell and B-cell epitopes have been selected based on their antigenicity (VaxiJen v2.0) and, allergenicity (AllerTOP v2.0). The identified epitopes with antigenic and non-allergenic properties were fused with the specific peptide linkers. In addition, the 3D model was constructed by the PHYRE2 server and validated using ProSA-web. The validated 3D model was further docked with the Toll-like receptor 3 (TLR3) and showed good interaction with the amino acids which indicate a promising vaccine candidate against the Omicron variant of SARS-CoV-2. Finally, the codon optimization, In-silico cloning and immune simulation profile was found to be satisfactory. Overall, the designed vaccine candidate has a potential against variant of SARS-Cov-2. However, further experimental studies are required to confirm.

Response to anti-SARS-CoV-2 mRNA vaccines in multiple myeloma and chronic lymphocytic leukemia patients

Multiple myeloma (MM) and chronic lymphocytic leukemia (CLL) patients have increased morbidity and mortality rates of COVID-19 due to immunosuppression associated with the disease and ongoing therapy. The same immune impairment accompanying CLL and MM also affects suboptimal vaccine response. The study assessed the effectiveness of the humoral and T cell-mediated immunity following mRNA COVID-19 vaccination (using either BNT162b2 or mRNA-1273) in short-term (2-5 weeks after second dose) and long-term follow-up (12 weeks after vaccination). Between March and August 2021, blood samples were obtained from 62 CLL and 60 MM patients from eight different hematology departments in Poland. Total anti-RBD antibodies were detected in 37% MM patients before vaccination, increased to 91% and 94% in short- and long-term follow-up, respectively. In CLL, serological responses were detectable in 21% of patients before vaccination and increased to 45% in the short-term and 71% in long-term observation. We detected a tendency to higher frequencies of specific CD8+ T cells against SARS-CoV-2 after vaccination compared to samples before vaccination in MM patients and no changes in frequencies of specific T cells in CLL patients. Our study provides novel insights into mRNA vaccination efficacy in immunocompromised MM and CLL patients, and our findings highlight that specific CD8+ T cells against SARS-CoV-2 might be induced by vaccination but do not correlate positively with serological responses.

Mining of Marburg Virus Proteome for Designing an Epitope-Based Vaccine

Marburg virus (MARV) is one of the most harmful zoonotic viruses with deadly effects on both humans and nonhuman primates. Because of its severe outbreaks with a high rate of fatality, the world health organization put it as a risk group 4 pathogen and focused on the urgent need for the development of effective solutions against that virus. However, up to date, there is no effective vaccine against MARV in the market. In the current study, the complete proteome of MARV (seven proteins) was analyzed for the antigenicity score and the virulence or physiological role of each protein where we nominated envelope glycoprotein (Gp), Transcriptional activator (VP30), and membrane-associated protein (VP24) as the candidates for epitope prediction. Following that, a vaccine construct was designed based on CTL, HTL, and BCL epitopes of the selected protein candidates and to finalize the vaccine construct, several amino acid linkers, β-defensin adjuvant, and PADRE peptides were incorporated. The generated potential vaccine was assessed computationally for several properties such as antigenicity, allergenicity, stability, and other structural features where the outcomes of these assessments nominated this potential vaccine to be validated for its binding affinity with two molecular targets TLR-8 and TLR-4. The binding score and the stability of the vaccine-receptor complex, which was deeply studied through molecular docking-coupled dynamics simulation, supported the selection of our designed vaccine as a putative solution for MARV that should be validated through future wet-lab experiments. Here, we describe the computational approach for designing and analysis of this potential vaccine.

Chimeric Antigen by the Fusion of SARS-CoV-2 Receptor Binding Domain with the Extracellular Domain of Human CD154: A Promising Improved Vaccine Candidate

COVID-19 is a respiratory viral disease caused by a new coronavirus called SARS-CoV-2. This disease has spread rapidly worldwide with a high rate of morbidity and mortality. The receptor-binding domain (RBD) of protein spike (S) mediates the attachment of the virus to the host's cellular receptor. The RBD domain constitutes a very attractive target for subunit vaccine development due to its ability to induce a neutralizing antibody response against the virus. With the aim of boosting the immunogenicity of RBD, it was fused to the extracellular domain of CD154, an immune system modulator molecule. To obtain the chimeric protein, stable transduction of HEK-293 was carried out with recombinant lentivirus and polyclonal populations and cell clones were obtained. RBD-CD was purified from culture supernatant and further characterized by several techniques. RBD-CD immunogenicity evaluated in mice and non-human primates (NHP) indicated that recombinant protein was able to induce a specific and high IgG response after two doses. NHP sera also neutralize SARS-CoV-2 infection of Vero E6 cells. RBD-CD could improve the current vaccines against COVID-19, based in the enhancement of the host humoral and cellular response. Further experiments are necessary to confirm the utility of RBD-CD as a prophylactic vaccine and/or booster purpose.

Bioengineering of Novel Non-Replicating mRNA (NRM) and Self-Amplifying mRNA (SAM) Vaccine Candidates Against SARS-CoV-2 Using Immunoinformatics Approach

Presently, the world needs safe and effective vaccines to overcome the COVID-19 pandemic. Our work has focused on formulating two types of mRNA vaccines that differ in capacity to copy themselves inside the cell. These are non-amplifying mRNA (NRM) and self-amplifying mRNA (SAM) vaccines. Both the vaccine candidates encode an engineered viral replicon which can provoke an immune response. Hence we predicted and screened twelve epitopes from the spike glycoprotein of SARS-CoV-2. We used five CTL, four HTL, and three B-cell-activating epitopes to formulate each mRNA vaccine. Molecular docking revealed that these epitopes could combine with HLA molecules that are important for boosting immunogenicity. The B-cell epitopes were adjoined with GPGPG linkers, while CTL and HTL epitopes were linked with KK linkers. The entire protein chain was reverse translated to develop a specific NRM-based vaccine. We incorporate gene encoding replicase in the upstream region of CDS encoding antigen to design the SAM vaccine. Subsequently, signal sequences were added to human mRNA to formulate vaccines. Both vaccine formulations translated to produce the epitopes in host cells, initiate a protective immune cascade, and generate immunogenic memory, which can counter future SARS-CoV-2 viral exposures before the onset of infection.

Passive Immunotherapy Against SARS-CoV-2: From Plasma-Based Therapy to Single Potent Antibodies in the Race to Stay Ahead of the Variants

The COVID-19 pandemic is now approaching 2 years old, with more than 440 million people infected and nearly six million dead worldwide, making it the most significant pandemic since the 1918 influenza pandemic. The severity and significance of SARS-CoV-2 was recognized immediately upon discovery, leading to innumerable companies and institutes designing and generating vaccines and therapeutic antibodies literally as soon as recombinant SARS-CoV-2 spike protein sequence was available. Within months of the pandemic start, several antibodies had been generated, tested, and moved into clinical trials, including Eli Lilly's bamlanivimab and etesevimab, Regeneron's mixture of imdevimab and casirivimab, Vir's sotrovimab, Celltrion's regdanvimab, and Lilly's bebtelovimab. These antibodies all have now received at least Emergency Use Authorizations (EUAs) and some have received full approval in select countries. To date, more than three dozen antibodies or antibody combinations have been forwarded into clinical trials. These antibodies to SARS-CoV-2 all target the receptor-binding domain (RBD), with some blocking the ability of the RBD to bind human ACE2, while others bind core regions of the RBD to modulate spike stability or ability to fuse to host cell membranes. While these antibodies were being discovered and developed, new variants of SARS-CoV-2 have cropped up in real time, altering the antibody landscape on a moving basis. Over the past year, the search has widened to find antibodies capable of neutralizing the wide array of variants that have arisen, including Alpha, Beta, Gamma, Delta, and Omicron. The recent rise and dominance of the Omicron family of variants, including the rather disparate BA.1 and BA.2 variants, demonstrate the need to continue to find new approaches to neutralize the rapidly evolving SARS-CoV-2 virus. This review highlights both convalescent plasma- and polyclonal antibody-based approaches as well as the top approximately 50 antibodies to SARS-CoV-2, their epitopes, their ability to bind to SARS-CoV-2 variants, and how they are delivered. New approaches to antibody constructs, including single domain antibodies, bispecific antibodies, IgA- and IgM-based antibodies, and modified ACE2-Fc fusion proteins, are also described. Finally, antibodies being developed for palliative care of COVID-19 disease, including the ramifications of cytokine release syndrome (CRS) and acute respiratory distress syndrome (ARDS), are described.

Immunoinformatics approach of epitope prediction for SARS-CoV-2

BACKGROUND

The novel coronavirus (SARS-CoV-2) caused lethal infections worldwide during an unprecedented pandemic. Identification of the candidate viral epitopes is the first step in the design of vaccines against the viral infection. Several immunoinformatic approaches were employed to identify the SARS-CoV-2 epitopes that bind specifically with the major histocompatibility molecules class I (MHC-I). We utilized immunoinformatic tools to analyze the whole viral protein sequences, to identify the SARS-CoV-2 epitopes responsible for binding to the most frequent human leukocyte antigen (HLA) alleles in the Egyptian population. These alleles were also found with high frequency in other populations worldwide.

RESULTS

Molecular docking approach showed that using the co-crystallized MHC-I and T cell receptor (TCR) instead of using MHC-I structure only, significantly enhanced docking scores and stabilized the conformation, as well as the binding affinity of the identified SARS-CoV-2 epitopes. Our approach directly predicts 7 potential vaccine subunits from the available SARS-CoV-2 spike and ORF1ab protein sequence. This prediction has been confirmed by published experimentally validated and in silico predicted spike epitope. On the other hand, we predicted novel epitopes (RDLPQGFSA and FCLEASFNY) showing high docking scores and antigenicity response with both MHC-I and TCR. Moreover, antigenicity, allergenicity, toxicity, and physicochemical properties of the predicted SARS-CoV-2 epitopes were evaluated via state-of-the-art bioinformatic approaches, showing high efficacy of the proposed epitopes as a vaccine candidate.

CONCLUSION

Our predicted SARS-CoV-2 epitopes can facilitate vaccine development to enhance the immunogenicity against SARS-CoV-2 and provide supportive data for further experimental validation. Our proposed molecular docking approach of exploiting both MHC and TCR structures can be used to identify potential epitopes for most microbial pathogens, provided the crystal structure of MHC co-crystallized with TCR.

Drummondin E and Flinderole B are potential inhibitors of RNA-dependent RNA polymerase of SARS-CoV-2: an in silico study

Coronavirus disease 2019 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has affected 235.6 million people worldwide. In the present study, RNA-dependent RNA polymerase (RdRp) (PDB Id: 6M71) of SARS-CoV-2, an essential enzyme needed for subgenomic replication and amplification of RNA, was selected. Similar to other RdRps, it is a conserved protein and a popular target for antiviral drug therapy. Based on a computational approach, potential RdRp inhibitors were identified. The absorption, distribution, metabolism, excretion, and toxicity (ADMET) of selected molecules were determined using computation tools. The potential inhibitors were docked to the RdRp and later confirmed by Molecular Dynamics (MD) using the "Flare" module of Cresset software. Drummondin E and Flinderole B had higher drug similarity scores among the compounds selected in this study. Both these compounds are noncarcinogenic, nonirritant, nontumorigenic, and nonmutagenic. Molecular docking studies showed that both compounds can bind to RdRp. The best ligand interaction patterns were validated by MD using the "Flare" module. MD was performed for the period of 100 ns with the time step of 1 fs. The simulation results suggest that Thr-680, Arg-624, Lys-676, and Val-557 are key interacting partners in the Drummondin E-RdRp complex, while Asp-618, Asp-760, Asp-623, Arg-624, and Asp-761 are the interacting partners in the Flinderole B-RdRp complex. Based on the in silico drug-likeness score; ADMET properties; and molecular simulation result, we surmise that Flinderole B and Drummondin E could impede SARS-CoV-2 genome replication and transcription by targeting the RdRp protein.

Computationally validated SARS-CoV-2 CTL and HTL Multi-Patch vaccines, designed by reverse epitomics approach, show potential to cover large ethnically distributed human population worldwide

The SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) is responsible for the COVID-19 outbreak. The highly contagious COVID-19 disease has spread to 216 countries in less than six months. Though several vaccine candidates are being claimed, an effective vaccine is yet to come. A novel reverse epitomics approach, 'overlapping-epitope-clusters-to-patches' method is utilized to identify the antigenic regions from the SARS-CoV-2 proteome. These antigenic regions are named as 'Ag-Patch or Ag-Patches', for Antigenic Patch or Patches. The identification of Ag-Patches is based on the clusters of overlapping epitopes rising from SARS-CoV-2 proteins. Further, we have utilized the identified Ag-Patches to design Multi-Patch Vaccines (MPVs), proposing a novel method for the vaccine design. The designed MPVs were analyzed for immunologically crucial parameters, physiochemical properties and cDNA constructs. We identified 73 CTL (Cytotoxic T-Lymphocyte) and 49 HTL (Helper T-Lymphocyte) novel Ag-Patches from the proteome of SARS-CoV-2. The identified Ag-Patches utilized to design MPVs cover 768 overlapping epitopes targeting 55 different HLA alleles leading to 99.98% of world human population coverage. The MPVs and Toll-Like Receptor ectodomain complex shows stable complex formation tendency. Further, the cDNA analysis favors high expression of the MPVs constructs in a human cell line. We identified highly immunogenic novel Ag-Patches from the entire proteome of SARS CoV-2 by a novel reverse epitomics approach and utilized them to design MPVs. We conclude that the novel MPVs could be a highly potential novel approach to combat SARS-CoV-2, with greater effectiveness, high specificity and large human population coverage worldwide. Communicated by Ramaswamy H. Sarma.

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.

microRNAs and Inflammatory Immune Response in SARS-CoV-2 Infection: A Narrative Review

The current SARS-CoV-2 pandemic has emerged as an international challenge with strong medical and socioeconomic impact. The spectrum of clinical manifestations of SARS-CoV-2 is wide, covering asymptomatic or mild cases up to severe and life-threatening complications. Critical courses of SARS-CoV-2 infection are thought to be driven by the so-called “cytokine storm”, derived from an excessive immune response that induces the release of proinflammatory cytokines and chemokines. In recent years, non-coding RNAs (ncRNAs) emerged as potential diagnostic and therapeutic biomarkers in both inflammatory and infectious diseases. Therefore, the identification of SARS-CoV-2 miRNAs and host miRNAs is an important research topic, investigating the host–virus crosstalk in COVID-19 infection, trying to answer the pressing question of whether miRNA-based therapeutics can be employed to tackle SARS-CoV-2 complications. In this review, we aimed to directly address ncRNA role in SARS-CoV-2-immune system crosstalk upon COVID-19 infection, particularly focusing on inflammatory pathways and cytokine storm syndromes.

Immunodominant Linear B-Cell Epitopes of SARS-CoV-2 Spike, Identified by Sera from K18-hACE2 Mice Infected with the WT or Variant Viruses

SARS-CoV-2 surface spike protein mediates the viral entry into the host cell and represents the primary immunological target of COVID-19 vaccines as well as post-exposure immunotherapy. Establishment of the highly immunogenic B-cell epitope profile of SARS-CoV-2 proteins in general, and that of the spike protein in particular, may contribute to the development of sensitive diagnostic tools and identification of vaccine` candidate targets. In the current study, the anti-viral antibody response in transgenic K18-hACE-2 mice was examined by implementing an immunodominant epitope mapping approach of the SARS-CoV-2 spike. Serum samples for probing an epitope array covering the entire spike protein were collected from mice following infection with the original SARS-CoV-2 strain as well as the B.1.1.7 Alpha and B.1.351 Beta genetic variants of concern. The analysis resulted in distinction of six linear epitopes common to the humoral response against all virus variants inspected at a frequency of more than 20% of the serum samples. Finally, the universality of the response was probed by cross-protective in vitro experiments using plaque-reducing neutralization tests. The data presented here has important implications for prediction of the efficacy of immune countermeasures against emerging SARS-CoV-2 variants.

A novel ensemble fuzzy classification model in SARS-CoV-2 B-cell epitope identification for development of protein-based vaccine

B-cell epitope prediction research has received growing interest since the development of the first method. B-cell epitope identification with the aid of an accurate prediction method is one of the most important steps in epitope-based vaccine development, immunodiagnostic testing, antibody production, disease diagnosis, and treatment. Nevertheless, using experimental methods in epitope mapping is very time-consuming, costly, and labor-intensive. Therefore, although successful predictions with in silico methods are very important in epitope prediction, there are limited studies in this area. The aim of this study is to propose a new approach for successfully predicting B-cell epitopes for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, the SARS-CoV B-cell epitope prediction performances of different fuzzy learning classification models genetic cooperative competitive learning (GCCL), fuzzy genetics-based machine learning (GBML), Chi's method (CHI), Ishibuchi's method with weight factor (W), structural learning algorithm on vague environment (SLAVE) and the state-of-the-art ensemble fuzzy classification model were compared. The obtained results showed that the proposed ensemble approach has the lowest error in SARS-CoV B-cell epitope estimation compared to the base fuzzy learners (average error rates; ensemble fuzzy=8.33, GCCL=30.42, GBML=23.82, CHI=29.17, W=46.25, and SLAVE=20.42). SARS-CoV and SARS-CoV-2 have high genome similarities. Therefore, the most successful method determined for SARS-CoV B-cell epitope prediction was used in SARS-CoV-2 cell epitope prediction. Finally, the eventual B-cell epitope prediction results obtained for SARS-CoV-2 with the ensemble fuzzy classification model were compared with the epitope sequences predicted by the BepiPred server and immunoinformatics studies in the literature for the same protein sequences according to VaxiJen 2.0 scores. We hope that the developed epitope prediction method will help design effective vaccines and drugs against future outbreaks of the coronavirus family, especially SARS-CoV-2 and its possible mutations.

A Comparative and Comprehensive Review of Antibody Applications in the Treatment of Lung Disease

Antibodies are a type of protein produced by active B cells in response to antigen stimulation. A series of monoclonal antibodies and neutralizing antibodies have been invented and put into clinical use because of their high therapeutic effect and bright developing insight. Patients with cancer, infectious diseases, and autoimmune diseases can all benefit from antibody therapy. However, the targeting aspects and potential mechanisms for treating these diseases differ. In the treatment of patients with infectious diseases such as COVID-19, neutralizing antibodies have been proposed as reliable vaccines against COVID-19, which target the ACE2 protein by preventing virus entry into somatic cells. Monoclonal antibodies can target immune checkpoints (e.g., PD-L1 and CTLA-4), tyrosine kinase and subsequent signaling pathways (e.g., VEGF), and cytokines in cancer patients (e.g. IL-6 and IL-1β). It is debatable whether there is any connection between the use of antibodies in these diseases. It would be fantastic to discover the related points and explain the burden for the limitation of cross-use of these techniques. In this review, we provided a comprehensive overview of the use of antibodies in the treatment of infectious disease and cancer patients. There are also discussions of their mechanisms and history. In addition, we discussed our future outlook on the use of antibodies.

COVID-19 phase 4 vaccine candidates, effectiveness on SARS-CoV-2 variants, neutralizing antibody, rare side effects, traditional and nano-based vaccine platforms: a review

The COVID-19 pandemic has endangered world health and the economy. As the number of cases is increasing, different companies have started developing potential vaccines using both traditional and nano-based platforms to overcome the pandemic. Several countries have approved a few vaccine candidates for emergency use authorization (EUA), showing significant effectiveness and inducing a robust immune response. Oxford-AstraZeneca, Pfizer-BioNTech's BNT162, Moderna's mRNA-1273, Sinovac's CoronaVac, Johnson & Johnson, Sputnik-V, and Sinopharm's vaccine candidates are leading the race. However, the SARS-CoV-2 is constantly mutating, making the vaccines less effective, possibly by escaping immune response for some variants. Besides, some EUA vaccines have been reported to induce rare side effects such as blood clots, cardiac injury, anaphylaxis, and some neurological effects. Although the COVID-19 vaccine candidates promise to overcome the pandemic, a more significant and clear understanding is needed. In this review, we brief about the clinical trial of some leading candidates, their effectiveness, and their neutralizing effect on SARS-CoV-2 variants. Further, we have discussed the rare side effects, different traditional and nano-based platforms to understand the scope of future development.

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

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

Immunoinformatics and reverse vaccinomic approaches for effective design

The emergence of mutagenic strains of severe acute respiratory syndrome-Coronavirus-2 (SARS-CoV-2) worst hit the world which already suffered from the Coronavirus disease-2019 (COVID-19) pandemic for 2 years. Due to recent advances in vaccinomics, many vaccine candidates are available but their efficacy against a mutant version of SARS-CoV-2 has remained uncertain. The immune-informatics-based reverse vaccinomic approaches have shown promising investigations recently for the development of cost-effective vaccinomics candidates in a very short period of time. The strategic vaccine development of selected epitopes using artificial intelligence for both B- and T-cells is a very crucial step in this process. This approach provides a highly effective and immunogenic vaccine that offers immunological safety against autoimmunity and other adverse effects over ethnicities, pregnant women, and vulnerable age groups. Several researchers have developed effective vaccine candidates using computational vaccinology and the immune-informatics approach. In this process, a unique peptide sequence of viral proteins such as Nucleocapsid, spike, envelope protein was identified by various in silico tools which are acting as immunological epitopes against TLRs, T-cells, and B-cells. While the conventional immunological vaccine studies take years for vaccine candidature, the immunoinformatics approach is a time-efficient way for the next generation research to study host-pathogen interactions and vaccine development. It is also cost-effective and leads to a better understanding of disease pathogenesis, diagnosis, and immunological response. Owing to the advantage of immunoinformatics-based vaccine approaches the present chapter aimed to discuss vaccine development using immunoinformatics approaches. Besides, the current challenges and future aspects have also been discussed herewith.

Immuno-informatics analysis predicts B and T cell consensus epitopes for designing peptide vaccine against SARS-CoV-2 with 99.82% global population coverage

The current global pandemic due to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has taken a substantial number of lives across the world. Although few vaccines have been rolled-out, a number of vaccine candidates are still under clinical trials at various pharmaceutical companies and laboratories around the world. Considering the intrinsic nature of viruses in mutating and evolving over time, persistent efforts are needed to develop better vaccine candidates. In this study, various immuno-informatics tools and bioinformatics databases were deployed to derive consensus B-cell and T-cell epitope sequences of SARS-CoV-2 spike glycoprotein. This approach has identified four potential epitopes which have the capability to initiate both antibody and cell-mediated immune responses, are non-allergenic and do not trigger autoimmunity. These peptide sequences were also evaluated to show 99.82% of global population coverage based on the genotypic frequencies of HLA binding alleles for both MHC class-I and class-II and are unique for SARS-CoV-2 isolated from human as a host species. Epitope number 2 alone had a global population coverage of 98.2%. Therefore, we further validated binding and interaction of its constituent T-cell epitopes with their corresponding HLA proteins using molecular docking and molecular dynamics simulation experiments, followed by binding free energy calculations with molecular mechanics Poisson–Boltzmann surface area, essential dynamics analysis and free energy landscape analysis. The immuno-informatics pipeline described and the candidate epitopes discovered herein could have significant impact upon efforts to develop globally effective SARS-CoV-2 vaccines.

Community-level SARS-CoV-2 sequence diversity revealed by wastewater sampling

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for causing the COVID-19 pandemic, can be detected in untreated wastewater. Wastewater surveillance of SARS-CoV-2 complements clinical data by offering earlier community-level detection, removing underlying factors such as access to healthcare, sampling asymptomatic patients, and reaching a greater population. Here, we compare 24-hour composite samples from the influents of two different wastewater treatment plants (WWTPs) in South Carolina, USA: Columbia and Rock Hill. The sampling intervals span the months of July 2020 and January 2021, which cover the first and second waves of elevated SARS-CoV-2 transmission and COVID-19 clinical cases in these regions. We identify four signature mutations in the surface glycoprotein (spike) gene that are associated with the following variants of interest or concern, VOI or VOC (listed in parenthesis): S477N (B.1.526, Iota), T478K (B.1.617.2, Delta), D614G (present in all VOC as of May 2021), and H655Y (P.1, Gamma). The N501Y mutation, which is associated with three variants of concern, was identified in samples from July 2020, but not detected in January 2021 samples. Comparison of mutations identified in viral sequence databases such as NCBI Virus and GISAID indicated that wastewater sampling detected mutations that were present in South Carolina, but not reflected in the clinical data deposited into databases.

Quasispecies of SARS-CoV-2 revealed by single nucleotide polymorphisms (SNPs) analysis

New SARS-CoV-2 mutants have been continuously indentified with enhanced transmission ever since its outbreak in early 2020. As an RNA virus, SARS-CoV-2 has a high mutation rate due to the low fidelity of RNA polymerase. To study the single nucleotide polymorphisms (SNPs) dynamics of SARS-CoV-2, 158 SNPs with high confidence were identified by deep meta-transcriptomic sequencing, and the most common SNP type was C > T. Analyses of intra-host population diversity revealed that intra-host quasispecies' composition varies with time during the early onset of symptoms, which implicates viral evolution during infection. Network analysis of co-occurring SNPs revealed the most abundant non-synonymous SNP 22,638 in the S glycoprotein RBD region and 28,144 in the ORF8 region. Furthermore, SARS-CoV-2 variations differ in an individual's respiratory tissue (nose, throat, BALF, or sputum), suggesting independent compartmentalization of SARS-CoV-2 populations in patients. The positive selection analysis of the SARS-CoV-2 genome uncovered the positive selected amino acid G251V on ORF3a. Alternative allele frequency spectrum (AAFS) of all variants revealed that ORF8 could bear alternate alleles with high frequency. Overall, the results show the quasispecies' profile of SARS-CoV-2 in the respiratory tract in the first two months after the outbreak.

Immunoinformatics mapping of potential epitopes in SARS-CoV-2 structural proteins

All approved coronavirus disease 2019 (COVID-19) vaccines in current use are safe, effective, and reduce the risk of severe illness. Although data on the immunological presentation of patients with COVID-19 is limited, increasing experimental evidence supports the significant contribution of B and T cells towards the resolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Despite the availability of several COVID-19 vaccines with high efficacy, more effective vaccines are still needed to protect against the new variants of SARS-CoV-2. Employing a comprehensive immunoinformatic prediction algorithm and leveraging the genetic closeness with SARS-CoV, we have predicted potential immune epitopes in the structural proteins of SARS-CoV-2. The S and N proteins of SARS-CoV-2 and SARS-CoVs are main targets of antibody detection and have motivated us to design four multi-epitope vaccines which were based on our predicted B- and T-cell epitopes of SARS-CoV-2 structural proteins. The cardinal epitopes selected for the vaccine constructs are predicted to possess antigenic, non-allergenic, and cytokine-inducing properties. Additionally, some of the predicted epitopes have been experimentally validated in published papers. Furthermore, we used the C-ImmSim server to predict effective immune responses induced by the epitope-based vaccines. Taken together, the immune epitopes predicted in this study provide a platform for future experimental validations which may facilitate the development of effective vaccine candidates and epitope-based serological diagnostic assays.