A Next-Generation Vaccine Candidate Using Alternative Epitopes to Protect against Wuhan and All Significant Mutant Variants of SARS-CoV-2: An Immunoinformatics Approach

Contriving a novel of CHB therapeutic vaccine based on IgV_CTLA-4 and L protein via immunoinformatics approach

Chronic infection induced by immune tolerance to hepatitis B virus (HBV) is one of the most common causes of hepatic cirrhosis and hepatoma. Fortunately, the application of therapeutic vaccine can not only reverse HBV-tolerance, but also serve a potentially effective therapeutic strategy for treating chronic hepatitis B (CHB). However, the clinical effect of the currently developed CHB therapeutic vaccine is not optimistic due to the weak immunogenicity. Given that the human leukocyte antigen CTLA-4 owns strong binding ability to the surface B7 molecules (CD80 and CD86) of antigen presenting cell (APCs), the immunoglobulin variable region of CTLA-4 (IgV_CTLA-4) was fused with the L protein of HBV to contrive a novel therapeutic vaccine (V_C4HBL) for CHB in this study. We found that the addition of IgV_CTLA-4 did not interfere with the formation of L protein T cell and B cell epitopes after analysis by means of immunoinformatics approaches. Meanwhile, we also found that the IgV_CTLA-4 had strong binding force to B7 molecules through molecular docking and molecular dynamics (MD) simulation. Notably, our vaccine V_C4HBL showed good immunogenicity and antigenicity by in vitro and in vivo experiments. Therefore, the V_C4HBL is promising to again effectively activate the cellular and humoral immunity of CHB patients, and provides a potentially effective therapeutic strategy for the treatment of CHB in the future.Communicated by Ramaswamy H. Sarma.

Development of T cell antigen-based human coronavirus vaccines against nAb-escaping SARS-CoV-2 variants

Currently approved vaccines have been successful in preventing the severity of COVID-19 and hospitalization. These vaccines primarily induce humoral immune responses; however, highly transmissible and mutated variants, such as the Omicron variant, weaken the neutralization potential of the vaccines, thus, raising serious concerns about their efficacy. Additionally, while neutralizing antibodies (nAbs) tend to wane more rapidly than cell-mediated immunity, long-lasting T cells typically prevent severe viral illness by directly killing infected cells or aiding other immune cells. Importantly, T cells are more cross-reactive than antibodies, thus, highly mutated variants are less likely to escape lasting broadly cross-reactive T cell immunity. Therefore, T cell antigen-based human coronavirus (HCoV) vaccines with the potential to serve as a supplementary weapon to combat emerging SARS-CoV-2 variants with resistance to nAbs are urgently needed. Alternatively, T cell antigens could also be included in B cell antigen-based vaccines to strengthen vaccine efficacy. This review summarizes recent advancements in research and development of vaccines containing T cell antigens or both T and B cell antigens derived from proteins of SARS-CoV-2 variants and/or other HCoVs based on different vaccine platforms.

Antibody evasion associated with the RBD significant mutations in several emerging SARS-CoV-2 variants and its subvariants

Since the origin of the wild strain of SARS-CoV-2, several variants have emerged, which were designated as VOC, VOI, and VUM from time to time. The Omicron variant is noted as the recent VOC. After the origin of the Omicron variant on November 2021, several subvariants of Omicron have originated subsequently, like BA.1/2, BA.2.75/2.75.2, BA.4/5, BF.7, BQ.1/1.1, XBB.1/1.5, etc. which are circulated throughout the globe. Scientists reported that antibody escape is a common phenomenon observed in all the previous VOCs, VOIs, including Omicron and its subvariants. The mutations in the NTD (N-terminal domain) and RBD (Receptor-binding domain) of the spike of these variants and subvariants are responsible for antibody escape. At the same time, it has been noted that spike RBD mutations have been increasing in the last few months. This review illustrates significant RBD mutations namely R346T, K417N/T, L452R, N460K E484A/K/Q, and N501Y found in the previous emerging SARS-CoV-2 variants, including Omicron and its subvariants in high frequency and their role in antibody evasion and immune evasion. The review also describes the different classes of nAb responsible for antibody escape in SARS-CoV-2 variants and the molecular perspective of the mutation in nAb escape. It will help the future researchers to develop efficient vaccines which can finally prevent the pandemic.

A novel mutation-proof, next-generation vaccine to fight against upcoming SARS-CoV-2 variants and subvariants, designed through AI enabled approaches and tools, along with the machine learning based immune simulation: A vaccine breakthrough

Emerging SARS-CoV-2 variants and subvariants are great concerns for their significant mutations, which are also responsible for vaccine escape. Therefore, the study was undertaken to develop a mutation-proof, next-generation vaccine to protect against all upcoming SARS-CoV-2 variants. We used advanced computational and bioinformatics approaches to develop a multi-epitopic vaccine, especially the AI model for mutation selection and machine learning (ML) strategies for immune simulation. AI-enabled and the top-ranked antigenic selection approaches were used to select nine mutations from 835 RBD mutations. We selected twelve common antigenic B cell and T cell epitopes (CTL and HTL) containing the nine RBD mutations and joined them with the adjuvants, PADRE sequence, and suitable linkers. The constructs' binding affinity was confirmed through docking with TLR4/MD2 complex and showed significant binding free energy (-96.67 kcal mol^-1) with positive binding affinity. Similarly, the calculated eigenvalue (2.428517e-05) from the NMA of the complex reveals proper molecular motion and superior residues' flexibility. Immune simulation shows that the candidate can induce a robust immune response. The designed mutation-proof, multi-epitopic vaccine could be a remarkable candidate for upcoming SARS-CoV-2 variants and subvariants. The study method might guide researchers in developing AI-ML and immunoinformatics-based vaccines for infectious disease.

SARS-CoV-2 Vaccines, Vaccine Development Technologies, and Significant Efforts in Vaccine Development during the Pandemic: The Lessons Learned Might Help to Fight against the Next Pandemic

We are currently approaching three years since the beginning of the coronavirus disease 2019 (COVID-19) pandemic. SARS-CoV-2 has caused extensive disruptions in everyday life, public health, and the global economy. Thus far, the vaccine has worked better than expected against the virus. During the pandemic, we experienced several things, such as the virus and its pathogenesis, clinical manifestations, and treatments; emerging variants; different vaccines; and the vaccine development processes. This review describes how each vaccine has been developed and approved with the help of modern technology. We also discuss critical milestones during the vaccine development process. Several lessons were learned from different countries during the two years of vaccine research, development, clinical trials, and vaccination. The lessons learned during the vaccine development process will help to fight the next pandemic.

B.1.1.7 (Alpha) variant is the most antigenic compared to Wuhan strain, B.1.351, B.1.1.28/triple mutant and B.1.429 variants

The rapid spread of the SARS-CoV-2 virus and its variants has created a catastrophic impact worldwide. Several variants have emerged, including B.1.351 (Beta), B.1.1.28/triple mutant (P.1), B.1.1.7 (Alpha), and B.1.429 (Epsilon). We performed comparative and comprehensive antigenicity mapping of the total S-glycoprotein using the Wuhan strain and the other variants and identified 9-mer, 15-mer, and 20-mer CTL epitopes through in silico analysis. The study found that 9-mer CTL epitope regions in the B.1.1.7 variant had the highest antigenicity and an average of the three epitope types. Cluster analysis of the 9-mer CTL epitopes depicted one significant cluster at the 70% level with two nodes (KGFNCYFPL and EGFNCYFPL). The phage-displayed peptides showed mimic 9-mer CTL epitopes with three clusters. CD spectra analysis showed the same band pattern of S-glycoprotein of Wuhan strain and all variants other than B.1.429. The developed 3D model of the superantigen (SAg)-like regions found an interaction pattern with the human TCR, indicating that the SAg-like component might interact with the TCR beta chain. The present study identified another partial SAg-like region (ANQFNSAIGKI) from the S-glycoprotein. Future research should examine the molecular mechanism of antigen processing for CD8⁺ T cells, especially all the variants’ antigens of S-glycoprotein.

Exploratory Algorithm of a Multi-epitope-based Subunit Vaccine Candidate Against Cryptosporidium hominis: Reverse Vaccinology-Based Immunoinformatic Approach

Cryptosporidiosis is the leading protozoan-induced cause of diarrheal illness in children, and it has been linked to childhood mortality, malnutrition, cognitive development, with retardation of growth. Cryptosporidium hominis, the anthroponotically transmitted species within the Cryptosporidium genus, contributes significantly to the global burden of infection, accounting for the majority of clinical cases in numerous nations, as well as its emergence in the last decade is largely due to detections obtained through noteworthy epidemiologic research. Nevertheless, there is no vaccine available, and the only licensed medication, nitazoxanide, has been demonstrated to have efficacy limitations in a number of patient groups recognized to be at high risk of complications. Therefore, current study delineates the computational vaccine design for Cryptosporidium hominis, the notable pathogen for enteric diarrhea. Firstly, a comprehensive literature search was conducted to identify six proteins based on their toxigenicity, allergenicity, antigenicity, and prediction of transmembrane helices to make up a multi-epitope-based subunit vaccine. Following that, antigenic non-toxic HTL epitope, CTL epitope with B cell epitope were predicted from the selected proteins and construct a vaccine candidate with adding an adjuvant and some linkers with immunologically superior epitopes. Afterwards, the constructed vaccine candidates and TLR2 receptor were put into the ClusPro server for molecular dynamic simulation to know the binding stability of the vaccine-TLR2 complex. Following that, Escherichia coli strain K12 was used as a cloning host for the chosen vaccine construct via the JCat server. As a result of the findings, it was resolute that the proposed chimeric peptide vaccine could improve the immune response to Cryptosporidium hominis.

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.

COVID-19 vaccine design using reverse and structural vaccinology, ontology-based literature mining and machine learning

Rational vaccine design, especially vaccine antigen identification and optimization, is critical to successful and efficient vaccine development against various infectious diseases including coronavirus disease 2019 (COVID-19). In general, computational vaccine design includes three major stages: (i) identification and annotation of experimentally verified gold standard protective antigens through literature mining, (ii) rational vaccine design using reverse vaccinology (RV) and structural vaccinology (SV) and (iii) post-licensure vaccine success and adverse event surveillance and its usage for vaccine design. Protegen is a database of experimentally verified protective antigens, which can be used as gold standard data for rational vaccine design. RV predicts protective antigen targets primarily from genome sequence analysis. SV refines antigens through structural engineering. Recently, RV and SV approaches, with the support of various machine learning methods, have been applied to COVID-19 vaccine design. The analysis of post-licensure vaccine adverse event report data also provides valuable results in terms of vaccine safety and how vaccines should be used or paused. Ontology standardizes and incorporates heterogeneous data and knowledge in a human- and computer-interpretable manner, further supporting machine learning and vaccine design. Future directions on rational vaccine design are discussed.

Comparative genomics, evolutionary epidemiology, and RBD-hACE2 receptor binding pattern in B.1.1.7 (Alpha) and B.1.617.2 (Delta) related to their pandemic response in UK and India

Background

The massive increase in COVID-19 infection had generated a second wave in India during May–June 2021 with a critical pandemic situation. The Delta variant (B.1.617.2) was a significant factor during the second wave. Conversely, the UK had passed through the crucial phase of the pandemic from November to December 2020 due to B.1.1.7. The study tried to comprehend the pandemic response in the UK and India to the spread of the B.1.1.7 (Alpha, UK) variant and B.1.617.2 (Delta, India) variant.

Methods

This study was performed in three directions to understand the pandemic response of the two emerging variants. First, we served comparative genomics, such as genome sequence submission patterns, mutational landscapes, and structural landscapes of significant mutations (N501Y, D614G, L452R, E484Q, and P681R). Second, we performed evolutionary epidemiology using molecular phylogenetics, scatter plots of the cluster evaluation, country-wise transmission pattern, and frequency pattern. Third, the receptor binding pattern was analyzed using the Wuhan reference strain and the other two variants.

Results

The study analyzed the country-wise and region-wise genome sequences and their submission pattern, molecular phylogenetics, scatter plot of the cluster evaluation, country-wise geographical distribution and transmission pattern, frequency pattern, entropy diversity, and mutational landscape of the two variants. The structural pattern was analyzed in the N501Y, D614G L452R, E484Q, and P681R mutations. The study found increased molecular interactivity between hACE2-RBD binding of B.1.1.7 and B.1.617.2 compared to the Wuhan reference strain. Our receptor binding analysis showed a similar indication pattern for hACE2-RBD of these two variants. However, B.1.617.2 offers slightly better stability in the hACE2-RBD binding pattern through MD simulation than B.1.1.7.

Conclusion

The increased hACE2-RBD binding pattern of B.1.1.7 and B.1.617.2 might help to increase the infectivity compared to the Wuhan reference strain.

Design of a Recombinant Multivalent Epitope Vaccine Based on SARS-CoV-2 and Its Variants in Immunoinformatics Approaches

The development of an effective multivalent vaccine against SARS-CoV-2 variants is an important means to improve the global public health situation caused by COVID-19. In this study, we identified the antigen epitopes of the main global epidemic SARS-CoV-2 and mutated virus strains using immunoinformatics approach, and screened out 8 cytotoxic T lymphocyte epitopes (CTLEs), 17 helper T lymphocyte epitopes (HTLEs), 9 linear B-cell epitopes (LBEs) and 4 conformational B-cell epitopes (CBEs). The global population coverage of CTLEs and HTLEs was 93.16% and 99.9% respectively. These epitopes were spliced together by corresponding linkers and recombined into multivalent vaccine. In silico tests, the vaccine protein was a non-allergen and the docking with TLR-3 molecule showed a strong interaction. The results of immune simulation showed that the vaccine may be helpful to initiate both cellular and humoral immunity against all VOC. The optimistic immunogenicity of the vaccine was confirmed in vivo and in vitro finally. Therefore, our vaccine may have potential protection against SARS-CoV-2 and its variants.

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.

A Detailed Overview of Immune Escape, Antibody Escape, Partial Vaccine Escape of SARS-CoV-2 and Their Emerging Variants With Escape Mutations

The infective SARS-CoV-2 is more prone to immune escape. Presently, the significant variants of SARS-CoV-2 are emerging in due course of time with substantial mutations, having the immune escape property. Simultaneously, the vaccination drive against this virus is in progress worldwide. However, vaccine evasion has been noted by some of the newly emerging variants. Our review provides an overview of the emerging variants' immune escape and vaccine escape ability. We have illustrated a broad view related to viral evolution, variants, and immune escape ability. Subsequently, different immune escape approaches of SARS-CoV-2 have been discussed. Different innate immune escape strategies adopted by the SARS-CoV-2 has been discussed like, IFN-I production dysregulation, cytokines related immune escape, immune escape associated with dendritic cell function and macrophages, natural killer cells and neutrophils related immune escape, PRRs associated immune evasion, and NLRP3 inflammasome associated immune evasion. Simultaneously we have discussed the significant mutations related to emerging variants and immune escape, such as mutations in the RBD region (N439K, L452R, E484K, N501Y, K444R) and other parts (D614G, P681R) of the S-glycoprotein. Mutations in other locations such as NSP1, NSP3, NSP6, ORF3, and ORF8 have also been discussed. Finally, we have illustrated the emerging variants' partial vaccine (BioNTech/Pfizer mRNA/Oxford-AstraZeneca/BBIBP-CorV/ZF2001/Moderna mRNA/Johnson & Johnson vaccine) escape ability. This review will help gain in-depth knowledge related to immune escape, antibody escape, and partial vaccine escape ability of the virus and assist in controlling the current pandemic and prepare for the next.

SARS-CoV-2 variant surge and vaccine breakthrough infection: A computational analysis

Coronavirus Delta variant was first detected in India in October of 2020, and it led to a massive second wave of COVID-19 cases in the country. Since then, the highly infectious Delta strain has been spreading globally. The Delta variant and its sub-lineages showed an increased infection rate with a reduced effect of the potential antibody neutralization. The current work is a modeled computational analysis of the mutated receptor-binding domain (RBD) of the SARS-CoV-2 B.1.617 lineage binding with ACE2 and GRP78 to understand the increased strain transmissibility. The cell-surface Glucose Regulated Protein 78 (GRP78) attached to the mutated ACE2-SARS-CoV-2 Spike RBD complex is modeled. The results showed that GRP78 β-substrate-binding domain weakly binds to the wild-type RBD combined with angiotensin-converting enzyme 2 (ACE2) within the SARS-CoV-2 Spike RBD-ACE2 complex. Both GRP78 and ACE2 bind approximately in the same region on the wild-type SARS-CoV-2 Spike RBD surface. On the other hand, GRP78 strongly binds to the mutated SARS-CoV-2 Spike RBD in the RBD-ACE2 complex through the α-substrate-binding domain instead of β-substrate-binding domain in a different region from that of ACE2. The current findings suggest that blocking the main ACE2 pathway may not prevent the interactions between GRP78 and the mutated SARS-CoV-2 Spike RBD, which might introduce an additional avenue into the virus invasion for the host cell if the ACE2 pathway is blocked by the neutralized antibodies. Hence, the peptide satpdb10668 has been proposed as a potential inhibitor of SARS-CoV-2 attachment and virus invasion into the host cell.

Evolution, Mode of Transmission, and Mutational Landscape of Newly Emerging SARS-CoV-2 Variants

The recent emergence of multiple variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a significant concern for public health worldwide. New variants have been classified either as variants of concern (VOCs) or variants of interest (VOIs) by the CDC (USA) and WHO. The VOCs include lineages such as B.1.1.7 (20I/501Y.V1 variant), P.1 (20J/501Y.V3 variant), B.1.351 (20H/501Y.V2 variant), and B.1.617.2. In contrast, the VOI category includes B.1.525, B.1.526, P.2, and B.1.427/B.1.429. The WHO provided the alert for last two variants (P.2 and B.1.427/B.1.429) and labeled them for further monitoring. As per the WHO, these variants can be reclassified due to their status at a particular time. At the same time, the CDC (USA) has marked these two variants as VOIs up through today. This article analyzes the evolutionary patterns of all these emerging variants, as well as their geographical distributions and transmission patterns, including the circulating frequency, entropy diversity, and mutational event diversity throughout the genomes of all SARS-CoV-2 lineages. The transmission pattern was observed highest in the B.1.1.7 lineage. Our frequency evaluation found that this lineage achieved 100% frequency in early October 2020. We also critically evaluated the above emerging variants mutational landscape and significant spike protein mutations (E484K, K417T/N, N501Y, and D614G) impacting public health. Finally, the effectiveness of vaccines against newly SARS-CoV-2 variants was also analyzed. IMPORTANCE Irrespective of the aggressive vaccination drive, the newly emerging multiple SARS-CoV-2 variants are causing havoc in several countries. As per the CDC (USA) and WHO, the VOCs include the B.1.1.7, P.1, B.1.351, and B.1.617.2 lineages, while the VOIs include the B.1.525, B.1.526, P.2, and B.1.427/B.1.429 lineages. This study analyzed the evolutionary patterns, geographical distributions and transmission patterns, circulating frequency, entropy diversity, and mutational event diversity throughout the genome of significant SARS-CoV-2 lineages. A higher transmission pattern was observed for the B.1.1.7 variant. The study also evaluated the mutational landscape and important spike protein mutations (E484K, K417T/N, N501Y, and D614G) of all of the above variants. Finally, a survey was performed on the efficacy of vaccines against these variants from the previously published literature. The results presented in this article will help design future countrywide pandemic planning strategies for the emerging variants, next-generation vaccine development using alternative wild-type antigens and significant viral antigens, and immediate planning for ongoing vaccination programs worldwide.

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.

Present variants of concern and variants of interest of severe acute respiratory syndrome coronavirus 2: Their significant mutations in S‐glycoprotein, infectivity, re‐infectivity, immune escape and vaccines activity

Newly arising variants of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) are now a threat to global public health and are creating COVID‐19 surges in different countries. At the same time, there is limited knowledge about these emerging variants. Even if research data are available, it is varyingly scattered. In this review, we have discussed the appearance of significant alarming SARS‐CoV‐2 variants in the entire world. The study also discusses the properties of the substantial variant of concern (VOC) variants such as B.1.1.7 (Alpha), B.1.351 (Beta), P.1 (Gamma), B.1.427 (Epsilon) and B.1.429 (Epsilon). At the same time, the characteristic properties of some significant variant of interest (VOI) variants like B.1.525 (Eta), B.1.526 (Iota) (sublineage B.1.526.1), B.1.617 (sublineages B.1.617.1 (Kappa), B.1.617.2 (Delta) and B.1.617.3), P.2 (Zeta), P.3 (Theta), B.1.616 and B.1.427 have also been discussed. Here, we have explained some essential mutations for the VOC and VOI variants such as K417T/N, L452R, E484K, N501Y, D614G and P681R. Consecutively, we also highlighted the crucial clinical characteristics of the variants, such as transmissibility, infectivity, re‐infectivity, immune escape, vaccine activity and vaccine escape. Our comprehensive review will provide updated information on the newly appearing variants of SARS‐CoV‐2 and help the researchers to formulate strategies to curtail the COVID‐19 pandemic.