A comprehensive analysis of the mutational landscape of the newly emerging Omicron (B.1.1.529) variant and comparison of mutations with VOCs and VOIs.

The Omicron variant is spreading rapidly throughout several countries. Thus, we comprehensively analyzed Omicron's mutational landscape and compared mutations with VOC/VOI. We analyzed SNVs throughout the genome, and AA variants (NSP and SP) in VOC/VOI, including Omicron. We generated heat maps to illustrate the AA variants with high mutation prevalence (> 75% frequency) of Omicron, which demonstrated eight mutations with > 90% prevalence in ORF1a and 29 mutations with > 75% prevalence in S-glycoprotein. A scatter plot for Omicron and VOC/VOI's cluster evaluation was computed. We performed a risk analysis of the antibody-binding risk among four mutations (L452, F490, P681, D614) and observed three mutations (L452R, F490S, D614G) destabilized antibody interactions. Our comparative study evaluated the properties of 28 emerging mutations of the S-glycoprotein of Omicron, and the ΔΔG values. Our results showed K417N with minimum and Q954H with maximum ΔΔG value. Furthermore, six important RBD mutations (G339D, S371L, N440K, G446S, T478K, Q498R) were chosen for comprehensive analysis for stabilizing/destabilizing properties and molecular flexibility. The G339D, S371L, N440K, and T478K were noted as stable mutations with 0.019 kcal/mol, 0.127 kcal/mol, 0.064 kcal/mol, and 1.009 kcal/mol. While, G446S and Q498R mutations showed destabilizing results. Simultaneously, among six RBD mutations, G339D, G446S, and Q498R mutations increased the molecular flexibility of S-glycoprotein. This study depicts the comparative mutational pattern of Omicron and other VOC/VOI, which will help researchers to design and deploy novel vaccines and therapeutic antibodies to fight against VOC/VOI, including Omicron.

Delta variant (B.1.617.2) of SARS-CoV-2: current understanding of infection, transmission, immune escape, and mutational landscape.

The Delta variant is one of the alarming variants of the SARS-CoV-2 virus that have been immensely detrimental and a significant cause of the prolonged pandemic (B.1.617.2). During the SARS-CoV-2 pandemic from December 2020 to October 2021, the Delta variant showed global dominance, and afterwards, the Omicron variant showed global dominance. Delta shows high infectivity rate which accounted for nearly 70% of the cases after December 2020. This review discusses the additional attributes that make the Delta variant so infectious and transmissible. The study also focuses on the significant mutations, namely the L452R and T478K present on the receptor-binding domain of spike (S)-glycoprotein, which confers specific alterations to the Delta variant. Considerably, we have also highlighted other notable factors such as the immune escape, infectivity and re-infectivity, vaccine escape, Ro number, S-glycoprotein stability, cleavage pattern, and its binding affinity with the host cell receptor protein. We have also emphasized clinical manifestations, symptomatology, morbidity, and mortality for the Delta variant compared with other significant SARS-CoV-2 variants. This review will help the researchers to get an elucidative view of the Delta variant to adopt some practical strategies to minimize the escalating spread of the SARS-CoV-2 Delta variant.

Integrative Bioinformatics Approaches Indicate a Particular Pattern of Some SARS-CoV-2 and Non-SARS-CoV-2 Proteins.

Pattern recognition plays a critical role in integrative bioinformatics to determine the structural patterns of proteins of viruses such as SARS-CoV-2. This study identifies the pattern of SARS-CoV-2 proteins to depict the structure-function relationships of the protein alphabets of SARS-CoV-2 and COVID-19. The assembly enumeration algorithm, Anisotropic Network Model, Gaussian Network Model, Markovian Stochastic Model, and image comparison protein-like alphabets were used. The distance score was the lowest with 22 for "I" and highest with 40 for "9". For post-processing and decision, two protein alphabets "C" (PDB ID: 6XC3) and "S" (PDB ID: 7OYG) were evaluated to understand the structural, functional, and evolutionary relationships, and we found uniqueness in the functionality of proteins. Here, models were constructed using "SARS-CoV-2 proteins" (12 numbers) and "non-SARS-CoV-2 proteins" (14 numbers) to create two words, "SARS-CoV-2" and "COVID-19". Similarly, we developed two slogans: "Vaccinate the world against COVID-19" and "Say no to SARS-CoV-2", which were made with the proteins structure. It might generate vaccine-related interest to broad reader categories. Finally, the evolutionary process appears to enhance the protein structure smoothly to provide suitable functionality shaped by natural selection.

Structural Landscape of nsp Coding Genomic Regions of SARS-CoV-2-ssRNA Genome: A Structural Genomics Approach Toward Identification of Druggable Genome, Ligand-Binding Pockets, and Structure-Based Druggability.

SARS-CoV-2 has a single-stranded RNA genome (+ssRNA), and synthesizes structural and non-structural proteins (nsps). All 16 nsp are synthesized from the ORF1a, and ORF1b regions associated with different life cycle preprocesses, including replication. The regions of ORF1a synthesizes nsp1 to 11, and ORF1b synthesizes nsp12 to 16. In this paper, we have predicted the secondary structure conformations, entropy & mountain plots, RNA secondary structure in a linear fashion, and 3D structure of nsp coding genes of the SARS-CoV-2 genome. We have also analyzed the A, T, G, C, A+T, and G+C contents, GC-profiling of these genes, showing the range of the GC content from 34.23 to 48.52%. We have observed that the GC-profile value of the nsp coding genomic regions was less (about 0.375) compared to the whole genome (about 0.38). Additionally, druggable pockets were identified from the secondary structure-guided 3D structural conformations. For secondary structure generation of all the nsp coding genes (nsp 1-16), we used a recent algorithm-based tool (deep learning-based) along with the conventional algorithms (centroid and MFE-based) to develop secondary structural conformations, and we found stem-loop, multi-branch loop, pseudoknot, and the bulge structural components, etc. The 3D model shows bound and unbound forms, branched structures, duplex structures, three-way junctions, four-way junctions, etc. Finally, we identified binding pockets of nsp coding genes which will help as a fundamental resource for future researchers to develop RNA-targeted therapeutics using the druggable genome.

The rapid emergence of multiple sublineages of Omicron (B.1.1.529) variant: Dynamic profiling via molecular phylogenetics and mutational landscape studies.

PURPOSE: The recent Omicron (B.1.1.529) variant poses a significant threat to global health. This variant has spread worldwide, and several sublineages have rapidly emerged. Study tried to analyze the microevolution of this variant. METHODS: We studied the molecular phylogenetics, divergence, geographical distributions, frequencies, risk mutations for antibody affinity, and mutational landscape for Omicron sublineages using in silico analysis and statistical models. The risk mutation of spike for nAb affinity was analyzed and illustrated by statistical plots. Finally, the mutational properties of the spike mutations and their stability were predicted and demonstrated. RESULTS: First, we studied the microevolutionary Omicron sublineages using molecular phylogenetics. Simultaneously, we revealed divergence events of the Omicron sublineages and observed the lowest minimum divergence of 51 in clade 21K and the highest maximum divergence of 90 in clade 21L. We have demonstrated cluster analyses, geographical distributions, frequencies of Omicron and its sublineages. Finally, we evaluated the mutational landscape of the Omicron sublineages. In this mutational study, we performed a genome-wide analysis of general mutations, mutations in the non-spike genome, and spike mutations of Omicron sublineages. The risk mutation of S-glycoprotein for nAb affinity has been analyzed for Omicron sublineages. Here, we found that some sublineages have all four significant highly destabilizing mutations. Such sublineages are BA.1 (G446S, E484A, T95I, and D614G), BA.2 (H655Y, Q493R, G493S, and D614G), BA.4 (N501Y, Y505H, N969K, and D614G), and BA.2.75 (Q454H, T547K, N764K, D614G and G446S). Finally, from the mutation stability prediction through ΔΔG, we observed that BA.1 and BA.4 had two destabilizing and two stabilizing mutations. Similarly, BA.2, BA.5, and BA.2.12.1 have one destabilizing and three stabilizing mutations. However, all four mutations in BA.2.75 are stabilizing mutations. CONCLUSIONS: Our molecular phylogenetic studies provided a deeper understanding of the microevolution of sublineages and the creation of Omicron. Similarly, this study might help scientists develop pan-coronavirus vaccines that consider their mutational properties.

Therapeutic Role of Neutralizing Antibody for the Treatment against SARS-CoV-2 and Its Emerging Variants: A Clinical and Pre-Clinical Perspective.

Since early 2020, the entire world has been facing a disastrous outbreak of the SARS-CoV-2 virus, with massive reporting of death and infections per day. Medical practitioners adopted certain measures such as convalescent plasma therapy, antibody treatment, and injecting vaccines to eradicate the pandemic. In this review, we have primarily focused on the neutralizing antibodies presently under pre-clinical and clinical trials, focusing on their structures, binding affinity, mechanism of neutralization, and advantages over other therapeutics. We have also enlisted all the nAbs against SARS-CoV-2 and its emerging variants in different phases of clinical trials (phase-1, phase-II, and phase-III). The efficacy of administering antibody cocktails over the normal antibodies and their efficacy for the mutant variants of the SARS-CoV-2 virus in minimizing viral virulence is discussed. The potent neutralizing antibodies have eliminated many of the common problems posed by several other therapeutics. A common mechanism of the antibodies and their relevant sources have also been listed in this review.

Omicron (B.1.1.529) - A new heavily mutated variant: Mapped location and probable properties of its mutations with an emphasis on S-glycoprotein.

Omicron, another SARS-CoV-2 variant, has been recorded and reported as a VoC. It has already spread across >30 countries and is a highly mutated variant. We tried to understand the role of mutations in the investigated variants by comparison with previous characterized VoC. We have mapped the mutations in Omicron S-glycoprotein's secondary and tertiary structure landscape using bioinformatics tools and statistical software and developed different models. In addition, we analyzed the effect of diverse mutations in antibody binding regions of the S-glycoprotein on the binding affinity of the investigated antibodies. This study has chosen eight significant mutations in Omicron (D614G, E484A, N501Y, Q493K, K417N, S477N, Y505H G496S), and seven of them are located in the RBD region. We also performed a comparative analysis of the ΔΔG score of these mutations to understand the stabilizing or destabilizing properties of the investigated mutations. The analysis outcome shows that D614G, Q493K, and S477N mutations are stable mutations with ΔΔG scores of 0.351 kcal/mol, 0.470 kcal/mol, and 0.628 kcal/mol, respectively, according to DynaMut estimations. While other mutations (E484A, N501Y, K417N, Y505H, G496S) showed destabilizing results. The D614G, E484A, N501Y, K417N, Y505H, and G496S mutations increased the molecular flexibility of S-glycoprotein to interact with the ACE2 receptor, increasing the variant's infectivity. Our study will contribute to research on the SARS-CoV-2 variant, Omicron, by providing information on the mutational pattern and exciting properties of these eight significant mutations, such as antibody escape and infectivity quotient (stabilizing or destabilizing; increased or decreased molecular flexibility of S-glycoprotein to interact with the human ACE2 receptor).

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.

Emerging mutations in the SARS-CoV-2 variants and their role in antibody escape to small molecule-based therapeutic resistance.

Several clinical trials started during the COVID-19 pandemic to discover effective therapeutics led to identify a few candidates from the major clinical trials. However, in the past several months, quite a few SARS-CoV-2 variants have emerged with significant mutations. Major mutations in the S-glycoprotein and other parts of the genome have led to the antibody's escape to small molecule-based therapeutic resistance. The mutations in S-glycoprotein trigger the antibody escape/resistance, and mutations in RdRp might cause remdesivir resistance. The article illustrates emerging mutations that have resulted in antibody escape to therapeutics resistance. In this direction, the article illustrates presently developed neutralizing antibodies (with their preclinical, clinical stages) and antibody escapes and associated mutations. Finally, owing to the RdRp mutations, the antiviral small molecules resistance is illustrated.

Altered gut microbiota patterns in COVID-19: Markers for inflammation and disease severity.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection leads to a severe respiratory illness and alters the gut microbiota, which dynamically interacts with the human immune system. Microbiota alterations include decreased levels of beneficial bacteria and augmentation of opportunistic pathogens. Here, we describe critical factors affecting the microbiota in coronavirus disease 2019 (COVID-19) patients. These include, such as gut microbiota imbalance and gastrointestinal symptoms, the pattern of altered gut microbiota composition in COVID-19 patients, and crosstalk between the microbiome and the gut-lung axis/gut-brain-lung axis. Moreover, we have illustrated the hypoxia state in COVID-19 associated gut microbiota alteration. The role of ACE2 in the digestive system, and control of its expression using the gut microbiota is discussed, highlighting the interactions between the lungs, the gut, and the brain during COVID-19 infection. Similarly, we address the gut microbiota in elderly or co-morbid patients as well as gut microbiota dysbiosis of in severe COVID-19. Several clinical trials to understand the role of probiotics in COVID-19 patients are listed in this review. Augmented inflammation is one of the major driving forces for COVID-19 symptoms and gut microbiome disruption and is associated with disease severity. However, understanding the role of the gut microbiota in immune modulation during SARS-CoV-2 infection may help improve therapeutic strategies for COVID-19 treatment.

Continent-wide evolutionary trends of emerging SARS-CoV-2 variants: dynamic profiles from Alpha to Omicron.

The ongoing SARS-CoV-2 evolution process has generated several variants due to its continuous mutations, making pandemics more critical. The present study illustrates SARS-CoV-2 evolution and its emerging mutations in five directions. First, the significant mutations in the genome and S-glycoprotein were analyzed in different variants. Three linear models were developed with the regression line to depict the mutational load for S-glycoprotein, total genome excluding S-glycoprotein, and whole genome. Second, the continent-wide evolution of SARS-CoV-2 and its variants with their clades and divergence were evaluated. It showed the region-wise evolution of the SARS-CoV-2 variants and their clustering event. The major clades for each variant were identified. One example is clade 21K, a major clade of the Omicron variant. Third, lineage dynamics and comparison between SARS-CoV-2 lineages across different countries are also illustrated, demonstrating dominant variants in various countries over time. Fourth, gene-wise mutation patterns and genetic variability of SARS-CoV-2 variants across various countries are illustrated. High mutation patterns were found in the ORF10, ORF6, S, and low mutation pattern E genes. Finally, emerging AA point mutations (T478K, L452R, N501Y, S477N, E484A, Q498R, and Y505H), their frequencies, and country-wise occurrence were identified, and the highest event of two mutations (T478K and L452R) was observed.

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.

A Paradigm Shift in the Combination Changes of SARS-CoV-2 Variants and Increased Spread of Delta Variant (B.1.617.2) across the World.

Since September 2020, the SARS-CoV-2 variants have gained their dominance worldwide, especially in Kenya, Italy, France, the UK, Turkey, Indonesia, India, Finland, Ireland, Singapore, Denmark, Germany, and Portugal. In this study, we developed a model on the frequency of delta variants across 28 countries (R2= 0.1497), displaying the inheritance of mutations during the generation of the delta variants with 123,526 haplotypes. The country-wise haplotype network showed the distribution of haplotypes in USA (10,174), Denmark (5,637), India (4,089), Germany (2,350), Netherlands (1,899), Sweden (1,791), Italy (1,720), France (1,293), Ireland (1,257), Belgium (1,207), Singapore (1,193), Portugal (1,184) and Spain (1,133). Our analysis shows the highest haplotype in Europe with 84% and the lowest in Australia with 0.00001%. A model of scatter plot was generated with a regression line which provided the estimated rate of mutation, including 24.048 substitutions yearly. Our study concluded that the high global prevalence of the delta variants is due to a high frequency of infectivity, supporting the paradigm shift of the viral variants.

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.

Hybrid immunity against COVID-19 in different countries with a special emphasis on the Indian scenario during the Omicron period.

Hybrid immunity has been accepted as the most robust immunity to fight against SARS-CoV-2. The hybrid immunity against the virus is produced in individuals who have contracted the disease and received the COVID-19 vaccine. This happens due to the cumulative effect of natural and acquired (vaccine) immunity, which provides higher antibody responses compared to natural and vaccine-produced immunity alone. Scientists have noted that it provides about 25 to 100 times higher antibody responses than natural and vaccine-produced immunity alone. Here, we have tried to illustrate the molecular basis of hybrid immunity against various SARS-CoV-2 variants. We have described hybrid immunity under different headings, which are as follows: an overview of hybrid immunity; a comparison between herd immunity and hybrid immunity against SARS-CoV-2; hybrid immunity in different countries; hybrid immunity and different SARS-CoV-2 variants; the molecular basis of hybrid immunity; and hybrid immunity in Indian scenario. India's large population has recovered from SARS-CoV-2, and data shows that over 1000 million of the population received at least one dose of the vaccine. Besides, many infected individuals who have recovered also received at least one dose of the vaccine leading to hybrid immunity with a less severe third wave compared to the first and second waves. Based on the available data, we hypothesize that people's hybrid immunity could be a major cause of the less severe third wave.

D614G mutation and SARS-CoV-2: impact on S-protein structure, function, infectivity, and immunity.

The progression of the COVID-19 pandemic has generated numerous emerging variants of SARS-CoV-2 on a global scale. These variants have gained evolutionary advantages, comprising high virulence and serious infectivity due to multiple spike glycoprotein mutations. As a reason, variants are demonstrating significant abilities to escape the immune responses of the host. The D614G mutation in the S-glycoprotein of SARS-CoV-2 variants has shown the most efficient interaction with the ACE2 receptor of the cells. This explicit mutation at amino acid position 614 (aspartic acid-to-glycine substitution) is the prime cause of infection and re-infection. It changes the conformation of RBD and cleavage patterns S-glycoprotein with higher stability, replication fitness, and fusion efficiencies. Therefore, this review aims to provide several crucial pieces of information associated with the D614 mutational occurrence of SARS-CoV-2 variants and their infectivity patterns. This review will also effectively emphasize the mechanism of action of D614G mutant variants, immune escape, and partial vaccine escape of this virus. Furthermore, the viral characteristic changes leading to the current global pandemic condition have been highlighted. Here, we have tried to illustrate a novel direction for future researchers to develop effective therapeutic approaches and counterweight strategies to minimize the spread of COVID-19.Key points• D614G mutation arises within the S-glycoprotein of significant SARS-CoV-2 variants.• The D614G mutation affects infection, re-infection, cleavage patterns of S-glycoprotein, and replication fitness of SARS-CoV-2 variants.• The D614G mutation influences the immunity and partial vaccine escape.

Omicron variant (B.1.1.529) of SARS-CoV-2: understanding mutations in the genome, S-glycoprotein, and antibody-binding regions.

The Omicron variant has been detected in nearly 150 countries. We analyzed the mutational landscape of Omicron throughout the genome, focusing the S-glycoprotein. We also evaluated mutations in the antibody-binding regions and observed some important mutations overlapping those of previous variants including N501Y, D614G, H655Y, N679K, and P681H. Various new receptor-binding domain mutations were detected, including Q493K, G496S, Q498R, S477N, G466S, N440K, and Y505H. New mutations were found in the NTD (Δ143-145, A67V, T95I, L212I, and Δ211) including one new mutation in fusion peptide (D796Y). There are several mutations in the antibody-binding region including K417N, E484A, Q493K, Q498R, N501Y, and Y505H and several near the antibody-binding region (S477N, T478K, G496S, G446S, and N440K). The impact of mutations in regions important for the affinity between spike proteins and neutralizing antibodies was evaluated. Furthermore, we examined the effect of significant antibody-binding mutations (K417N, T478K, E484A, and N501Y) on antibody affinity, stability to ACE2 interaction, and possibility of amino acid substitution. All the four mutations destabilize the antibody-binding affinity. This study reveals future directions for developing neutralizing antibodies against the Omicron variant.

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

Newly emerging significant SARS-CoV-2 variants such as B.1.1.7, B.1.351, and B.1.1.28 are the variant of concern (VOC) for the human race. These variants are getting challenging to contain from spreading worldwide. Because of these variants, the second wave has started in various countries and is threatening human civilization. Thus, we require efficient vaccines that can combat all emerging variants of SARS-CoV-2. Therefore, we took the initiative to develop a peptide-based next-generation vaccine using four variants (Wuhan variant, B.1.1.7, B.1.351, and B.1.1.28) that could potentially combat SARS-CoV-2 variants. We applied a series of computational tools, servers, and software to identify the most significant epitopes present on the mutagenic regions of SARS-CoV-2 variants. The immunoinformatics approaches were used to identify common B cell derived T cell epitopes, influencing the host immune system. Consequently, to develop a novel vaccine candidate, the antigenic epitopes were linked with a flexible and stable peptide linker, and the adjuvant was added at the N-terminal end. 3D vaccine candidate structure was refined, and quality was assessed using web servers. The physicochemical properties and safety parameters of the vaccine construct were assessed through bioinformatics and immunoinformatics tools. The molecular docking analysis between TLR4/MD2 and the proposed vaccine candidate demonstrated a satisfactory interaction. The molecular dynamics studies confirmed the stability of the vaccine candidate. Finally, we optimized the proposed vaccine through codon optimization and in silico cloning to study the expression. Our multi-epitopic next-generation peptide vaccine construct can boost immunity against the Wuhan variant and all significant mutant variants of SARS-CoV-2.