Synonymous codon usage pattern in glycoprotein gene of rabies virus

Codon usage analysis in selected virulence genes of Staphylococcal species

The Staphylococcus genus, composed of Gram-positive bacteria, includes several pathogenic species such as Staphylococcus aureus, S. epidermidis, S. haemolyticus, and S. saprophyticus, each implicated in a range of infections. This study investigates the codon usage patterns in key virulence genes, including Autolysin (alt), Elastin Binding protein (EbpS), Lipase, Thermonuclease, Intercellular Adhesion Protein (IcaR), and V8 Protease, across four Staphylococcus species. Using metrics such as the Effective Number of Codons (ENc), Relative Synonymous Codon Usage (RSCU), Codon Adaptation Index (CAI), alongside neutrality and parity plots, we explored the codon preferences and nucleotide composition biases. Our findings revealed a pronounced AT-rich codon preference, with AT-rich genomes likely aiding in energy-efficient translation and bacterial survival in host environments. These insights provide a deeper understanding of the evolutionary adaptations and translational efficiency mechanisms that contribute to the pathogenicity of Staphylococcus species. This knowledge could pave the way for novel therapeutic interventions targeting codon usage to disrupt virulence gene expression.

Designing and comparative analysis of anti-oxidant and heat shock proteins based multi-epitopic filarial vaccines

BACKGROUND

Lymphatic Filariasis (LF) is a neglected tropical disease affecting more than 882 million people in 44 countries of the world. A multi-epitope prophylactic/therapeutic vaccination targeting filarial defense proteins would be invaluable to achieve the current LF elimination goal.

METHOD

Two groups of proteins, namely Anti-oxidant (AO) and Heat shock proteins (HSPs), have been implicated in the effective survival of the filarial parasites in their hosts. Several B-cell, CTL, and T-helper epitopes were predicted from the three anti-oxidant proteins GST, GPx, and SOD. Likewise, epitopes were also predicted for HSP110, HSP90, and HSP70. Among the predicted epitopes, screening was applied to include only non-allergenic, non-toxic epitopes to construct two MEVs, PVAO and PVHSP. The epitopes for each group of proteins were connected to each other by the inclusion of suitable linkers and an adjuvant. The 3D models for PVAO and PVHSP were predicted, and validated, followed by prediction of physicochemical properties using bioinformatics tools. The binding free energy of PVAO and PVHSP with Toll like Receptors (TLR) TLR1/2, TLR4, TLR5, TLR6, and TLR9 was calculated with HawkDock. The immunogenicity of both the MEVs were assessed by Immune simulation after which codon adaptation and in-silico cloning were carried out.

RESULTS

Conservation of the selected AOs and HSPs in other parasitic nematode species suggested that both the generated chimera could be helpful in cross-protection too. The 3D models of both MEVs contained more than 97% residues in allowed regions, as predicted by PROCHECK server. High MMGBSA and docking scores were obtained between MEVs and TLR4, TLR1/2, TLR6, and TLR9. Molecular dynamics simulation confirmed the stability of candidate vaccines in dynamic conditions present in the biological systems. The in-silico immune simulation indicated significantly high levels of IgG1, T-helper, T-cytotoxic cells, INF-γ, and IL-2 responses following immunization with PVAO and PVHSP.

CONCLUSION

The immunoinformatics approaches used in this study confirmed that, the designed vaccines are capable of eliciting sustained immunity against LF, however, additional in-vivo studies would be required to confirm their efficacy. Furthermore, by employing multi-epitope structures and constructing two different cocktail vaccines for LF, this study can form an important milestone in the development of future LF vaccine/s.

Using a dual immunoinformatics and bioinformatics approach to design a novel and effective multi-epitope vaccine against human torovirus disease

Human Torovirus (HToV), a member of the Coronaviridae family, causes severe enteric diseases with no specific medication available. To develop novel preventative measures, we employed immunoinformatics techniques to design a multi-epitope-based subunit vaccine (HToV-MEV) triggering diverse immune responses. We selected non-allergenic, non-toxic, and antigenic epitopes from structural polyproteins, joined them with suitable linkers, and added an adjuvant 50S ribosomal L7/L12 peptide. The vaccine's solubility score of 0.903678 and physiochemical properties were found effective. Molecular dynamics simulations and free energy calculations revealed strong binding affinity for Toll-like receptor 3 (TLR-3), with a lowest energy score of -303.88, indicating high affinity. In-silico cloning and codon optimization showed significant production potential in E. coli. Immune simulations predicted a human immunological response. Our results are promising, but subsequent in vivo research is recommended. The HToV-MEV vaccine design demonstrates potential for preventing HToV-related diseases, and further investigation is warranted to explore its therapeutic applications.

Immunoinformatics Design of a Multiepitope Vaccine (MEV) Targeting Streptococcus mutans: A Novel Computational Approach

Dental caries, a persistent oral health challenge primarily linked to Streptococcus mutans, extends its implications beyond dental decay, affecting over 4 billion individuals globally. Despite its historical association with childhood, dental caries often persists into adulthood with prevalence rates ranging from 60 to 90% in children and 26 to 85% in adults. Currently, there is a dearth of multiepitope vaccines (MEVs) specifically designed to combat S. mutans. To address this gap, we employed an immunoinformatics approach for MEV design, identifying five promising vaccine candidates (PBP2X, PBP2b, MurG, ATP-F, and AGPAT) based on antigenicity and conservation using several tools including CELLO v.2.5, Vaxign, v2.0, ANTIGENpro, and AllerTop v2.0 tools. Subsequent identification of linear B-cell and T-cell epitopes by SVMTrip and NetCTL/NetMHC II tools, respectively, guided the construction of a MEV comprising 10 Cytotoxic T Lymphocyte (CTL) epitopes, 5 Helper T Lymphocyte (HTL) epitopes, and 5 linear B-cell epitopes, interconnected by suitable linkers. The resultant MEV demonstrated high antigenicity, solubility, and structural stability. In silico immune simulations showcased the MEV's potential to elicit robust humoral and cell-mediated immune responses. Molecular docking studies revealed strong interactions between the MEV construct and Toll-Like Receptors (TLRs) and Major Histocompatibility Complex (MHC) molecules. Remarkably, the MEV-TLR-4 complexes exhibited a low energy score, high binding affinity, and a low dissociation constant. The Molecular Dynamic (MD) simulation analysis suggested that MEV-TLR-4 complexes had the highest stability and minimal conformational changes indicating equilibrium within 40 nanosecond time frames. Comprehensive computational analyses strongly support the potential of the proposed MEV to combat dental caries and associated infections. The study's computational assays yielded promising results, but further validation through in vitro and in vivo experiments is needed to assess its efficacy and safety.

In silico design and evaluation of a multiepitope vaccine targeting the nucleoprotein of Puumala orthohantavirus

The Puumala orthohantavirus is present in the body of the bank vole (Myodes glareolus). Humans infected with this virus may develop hemorrhagic fever accompanying renal syndrome. In addition, the infection may further lead to the failure of an immune system completely. The present study aimed to propose a possible vaccine by employing bioinformatics techniques to identify B and T-cell antigens. The best multi-epitope of potential immunogenicity was generated by combining epitopes. Additionally, the linkers EAAAK, AAY, and GPGPG were utilized in order to link the epitopes successfully. Further, C-ImmSim was used to perform in silico immunological simulations upon the vaccine. For the purpose of conducting expression tests in Escherichia coli, the chimeric protein construct was cloned using Snapgene into the pET-9c vector. The designed vaccine showed adequate results, evidenced by the global population coverage and favorable immune response. The developed vaccine was found to be highly effective and to have excellent population coverage in a number of computer-based assessments. This work is fully dependent on the development of nucleoprotein-based vaccines, which would constitute a significant step forward if our findings were used in developing a global vaccination to combat the Puumala virus.

Exploring Codon Usage Patterns and Influencing Factors in Ranavirus DNA Polymerase Genes

Ranaviruses, members of the genus Ranavirus within the family Iridoviridae, have become a significant concern for amphibian populations globally, along with other cold-blooded vertebrates, due to their emergence as a significant threat. We employed bioinformatics tools to examine the codon usage patterns in 61 DNA pol genes from Ranavirus, Lymphocystivirus, Megalocytivirus, and two unclassified ranaviruses, as no prior studies had been conducted on this topic. The results showed a slight or low level of codon usage bias (CUB) in the DNA pol genes of Ranavirus. Relative synonymous codon usage (RSCU) analysis indicated that the predominant codons favored in Ranavirus DNA pol genes terminate with C or G. Correlation analysis examining nucleotide content, third codon position, effective number of codons (ENC), correspondence analysis (COA), Aroma values, and GRAVY values indicated that the CUB across DNA pol genes could be influenced by both mutation pressure and natural selection. The neutrality plot indicated that natural selection is the primary factor driving codon usage. Furthermore, the analysis of the codon adaptation index (CAI) illustrated the robust adaptability of Ranavirus DNA pol genes to their hosts. Analysis of the relative codon deoptimization index (RCDI) suggested that Ranavirus DNA pol genes underwent greater selection pressure from their hosts. These findings will aid in comprehending the factors influencing the evolution and adaptation of Ranavirus to its hosts.

Comparative genome wise analysis of codon usage of Staphylococcus Genus

The genus Staphylococcus encompasses a diverse array of bacteria with significant implications for human health, including disreputable pathogens such as Staphylococcus aureus and Staphylococcus epidermidis. Understanding the genetic composition and codon usage patterns of Staphylococcus species is crucial for unraveling their evolutionary dynamics, adaptive strategies, and pathogenic potential. In this study, we conducted a comprehensive analysis of codon usage patterns across 48 species within the Staphylococcus genus. Our findings uncovered variations in genomic G-C content across Staphylococcus species, impacting codon usage preferences, with a notable preference for A/T-rich codons observed in pathogenic strains. This preference for A/T-rich codons suggests an energy-saving strategy in pathogenic organisms. Analysis of dinucleotide pair expression patterns unveiled insights into genomic dynamics, with overrepresented codon pairs reflecting trends in dinucleotide expression across genomes. Additionally, a significant correlation between CAI and genomic G-C content underscored the intricate relationship between codon usage patterns and gene expression strategies. Amino acid usage analysis highlighted preferences for energetically cheaper amino acids, suggesting adaptive strategies promoting energy efficiency. This comprehensive analysis sheds light on the evolutionary dynamics and adaptive mechanisms employed by Staphylococcus species, providing valuable insights into their pathogenic potential and clinical implications. Understanding these genomic features is crucial for devising strategies to combat staphylococcal infections and improve public health outcomes.

Formulation of next-generation polyvalent vaccine candidates against three important poxviruses by targeting DNA-dependent RNA polymerase using an integrated immunoinformatics and molecular modeling approach

BACKGROUND

Poxviruses comprise a group of large double-stranded DNA viruses and are known to cause diseases in humans, livestock animals, and other animal species. The Mpox virus (MPXV; formerly Monkeypox), variola virus (VARV), and volepox virus (VPXV) are among the prevalent poxviruses of the Orthopoxviridae genera. The ongoing Mpox infectious disease pandemic caused by the Mpox virus has had a major impact on public health across the globe. To date, only limited repurposed antivirals and vaccines are available for the effective treatment of Mpox and other poxviruses that cause contagious diseases.

METHODS

The present study was conducted with the primary goal of formulating multi-epitope vaccines against three evolutionary closed poxviruses i.e., MPXV, VARV, and VPXV using an integrated immunoinformatics and molecular modeling approach. DNA-dependent RNA polymerase (DdRp), a potential vaccine target of poxviruses, has been used to determine immunodominant B and T-cell epitopes followed by interactions analysis with Toll-like receptor 2 at the atomic level.

RESULTS

Three multi-epitope vaccine constructs, namely DdRp_MPXV (V1), DdRp_VARV (V2), and DdRp_VPXV (V3) were designed. These vaccine constructs were found to be antigenic, non-allergenic, non-toxic, and soluble with desired physicochemical properties. Protein-protein docking and interaction profiling analysis depicts a strong binding pattern between the targeted immune receptor TLR2 and the structural models of the designed vaccine constructs, and manifested a number of biochemical bonds (hydrogen bonds, salt bridges, and non-bonded contacts). State-of-the-art all-atoms molecular dynamics simulations revealed highly stable interactions of vaccine constructs with TLR2 at the atomic level throughout the simulations on 300 nanoseconds. Additionally, the outcome of the immune simulation analysis suggested that designed vaccines have the potential to induce protective immunity against targeted poxviruses.

CONCLUSIONS

Taken together, formulated next-generation polyvalent vaccines were found to have good efficacy against closely related poxviruses (MPXV, VARV, and VPXV) as demonstrated by our extensive immunoinformatics and molecular modeling evaluations; however, further experimental investigations are still needed.

Enhancing tuberculosis vaccine development: a deconvolution neural network approach for multi-epitope prediction

Tuberculosis (TB) a disease caused by Mycobacterium tuberculosis (Mtb) poses a significant threat to human life, and current BCG vaccinations only provide sporadic protection, therefore there is a need for developing efficient vaccines. Numerous immunoinformatic methods have been utilized previously, here for the first time a deep learning framework based on Deconvolutional Neural Networks (DCNN) and Bidirectional Long Short-Term Memory (DCNN-BiLSTM) was used to predict Mtb Multiepitope vaccine (MtbMEV) subunits against six Mtb H37Rv proteins. The trained model was used to design MEV within a few minutes against TB better than other machine learning models with 99.5% accuracy. The MEV has good antigenicity, and physiochemical properties, and is thermostable, soluble, and hydrophilic. The vaccine's BLAST search ruled out the possibility of autoimmune reactions. The secondary structure analysis revealed 87% coil, 10% beta, and 2% alpha helix, while the tertiary structure was highly upgraded after refinement. Molecular docking with TLR3 and TLR4 receptors showed good binding, indicating high immune reactions. Immune response simulation confirmed the generation of innate and adaptive responses. In-silico cloning revealed the vaccine is highly expressed in E. coli. The results can be further experimentally verified using various analyses to establish a candidate vaccine for future clinical trials.

In silico design of a novel multi-epitope vaccine against HCV infection through immunoinformatics approaches

Infection with the hepatitis C virus (HCV) is one of the causes of liver cancer, which is the world's sixth most prevalent and third most lethal cancer. The current treatments do not prevent reinfection; because they are expensive, their usage is limited to developed nations. Therefore, a prophylactic vaccine is essential to control this virus. Hence, in this study, an immunoinformatics method was applied to design a multi-epitope vaccine against HCV. The best B- and T-cell epitopes from conserved regions of the E2 protein of seven HCV genotypes were joined with the appropriate linkers to design a multi-epitope vaccine. In addition, cholera enterotoxin subunit B (CtxB) was included as an adjuvant in the vaccine construct. This study is the first to present this epitopes-adjuvant combination. The vaccine had acceptable physicochemical characteristics. The vaccine's 3D structure was predicted and validated. The vaccine's binding stability with Toll-like receptor 2 (TLR2) and TLR4 was confirmed using molecular docking and molecular dynamics (MD) simulation. The immune simulation revealed the vaccine's efficacy by increasing the population of B and T cells in response to vaccination. In silico expression in Escherichia coli (E. coli) was also successful.

Development of membrane protein-based vaccine against lumpy skin disease virus (LSDV) using immunoinformatic tools

INTRODUCTION

Lumpy skin disease, an economically significant bovine illness, is now found in previously unheard-of geographic regions. Vaccination is one of the most important ways to stop its further spread.

AIM

Therefore, in this study, we applied advanced immunoinformatics approaches to design and develop an effective lumpy skin disease virus (LSDV) vaccine.

METHODS

The membrane glycoprotein was selected for prediction of the different B- and T-cell epitopes by using the immune epitope database. The selected B- and T-cell epitopes were combined with the appropriate linkers and adjuvant resulted in a vaccine chimera construct. Bioinformatics tools were used to predict, refine and validate the 2D, 3D structures and for molecular docking with toll-like receptor 4 using different servers. The constructed vaccine candidate was further processed on the basis of antigenicity, allergenicity, solubility, different physiochemical properties and molecular docking scores.

RESULTS

The in silico immune simulation induced significant response for immune cells. In silico cloning and codon optimization were performed to express the vaccine candidate in Escherichia coli. This study highlights a good signal for the design of a peptide-based LSDV vaccine.

CONCLUSION

Thus, the present findings may indicate that the engineered multi-epitope vaccine is structurally stable and can induce a strong immune response, which should help in developing an effective vaccine towards controlling LSDV infection.

Designing, cloning and simulation studies of cancer/testis antigens based multi-epitope vaccine candidates against cutaneous melanoma: An immunoinformatics approach

Background

Melanoma is the most fatal kind of skin cancer. Among its various types, cutaneous melanoma is the most prevalent one. Melanoma cells are thought to be highly immunogenic due to the presence of distinct tumor-associated antigens (TAAs), which includes carcinoembryonic antigen (CEA), cancer/testis antigens (CTAs) and neo-antigens. The CTA family is a group of antigens that are only expressed in malignancies and testicular germ cells.

Methods

We used integrative framework and systems-level analysis to predict potential vaccine candidates for cutaneous melanoma involving epitopes prediction, molecular modeling and molecular docking to cross-validate the binding affinity and interaction between potential vaccine agents and major histocompatibility molecules (MHCs) followed by molecular dynamics simulation, immune simulation and in silico cloning.

Results

In this study, three cancer/testis antigens were targeted for immunotherapy of cutaneous melanoma. Among many CTAs that were studied for their expression in primary and malignant melanoma, NY-ESO-1, MAGE1 and SSX2 antigens are most prevalent in cutaneous melanoma. Cytotoxic and Helper epitopes were predicted, and the finest epitopes were shortlisted based on binding score. The vaccine construct was composed of the four epitope-rich domains of antigenic proteins, an appropriate adjuvant, His tag and linkers. This potential multi-epitope vaccine was further evaluated in terms of antigenicity, allergencity, toxicity and other physicochemical properties. Molecular interaction estimated through protein-protein docking unveiled good interactions characterized by favorable binding energies. Molecular dynamics simulation ensured the stability of docked complex and the predicted immune response through immune simulation revealed elevated levels of antibodies titer, cytokines, interleukins and immune cells (NK, DC and MA) population.

Conclusion

The findings indicate that the potential vaccine candidates could be effective immunotherapeutic agents that modify the treatment strategies of cutaneous melanoma.

Molecular insights into codon usage analysis of mitochondrial fission and fusion gene: relevance to neurodegenerative diseases

Mitochondrial dysfunction is the leading cause of neurodegenerative disorders like Alzheimer's disease and Parkinson's disease. Mitochondria is a highly dynamic organelle continuously undergoing the process of fission and fusion for even distribution of components and maintaining proper shape, number, and bioenergetic functionality. A set of genes governs the process of fission and fusion. OPA1, Mfn1, and Mfn2 govern fusion, while Drp1, Fis1, MIEF1, and MIEF2 genes control fission. Determination of specific molecular patterns of transcripts of these genes revealed the impact of compositional constraints on selecting optimal codons. AGA and CCA codons were over-represented, and CCC, GTC, TTC, GGG, ACG were under-represented in the fusion gene set. In contrast, CTG was over-represented, and GCG, CCG, and TCG were under-represented in the fission gene set. Hydropathicity analysis revealed non-polar protein products of both fission and fusion gene set transcripts. AGA codon repeats are an integral part of translational regulation machinery and present a distinct pattern of over-representation and under-representation in different transcripts within the gene sets, suggestive of selective translational force precisely controlling the occurrence of the codon. Out of six synonymous codons, five synonymous codons encoding for leucine were used differently in both gene sets. Hence, forces regulating the occurrence of AGA and five synonymous leucine-encoding codons suggest translational selection. A correlation of mutational bias with gene expression and codon bias and GRAVY and AROMA signifies the selection pressure in both gene sets, while the correlation of compositional bias with gene expression, codon bias, protein properties, and minimum free energy signifies the presence of compositional constraints. More than 25% of codons of both gene sets showed a significant difference in codon usage. The overall analysis shed light on molecular features of gene sets involved in fission and fusion.

Designing a T-cell epitope-based vaccine using in silico approaches against the Sal k 1 allergen of Salsola kali plant

Allergens originated from Salsola kali (Russian thistle) pollen grains are one of the most important sources of aeroallergens causing pollinosis in desert and semi-desert regions. T-cell epitope-based vaccines (TEV) are more effective among different therapeutic approaches developed to alleviate allergic diseases. The physicochemical properties, and B as well as T cell epitopes of Sal k 1 (a major allergen of S. kali) were predicted using immunoinformatic tools. A TEV was constructed using the linkers EAAAK, GPGPG and the most suitable CD4+ T cell epitopes. RS04 adjuvant was added as a TLR4 agonist to the amino (N) and carboxyl (C) terminus of the TEV protein. The secondary and tertiary structures, solubility, allergenicity, toxicity, stability, physicochemical properties, docking with immune receptors, BLASTp against the human and microbiota proteomes, and in silico cloning of the designed TEV were assessed using immunoinformatic analyses. Two CD4+ T cell epitopes of Sal k1 that had high affinity with different alleles of MHC-II were selected and used in the TEV. The molecular docking of the TEV with HLADRB1, and TLR4 showed TEV strong interactions and stable binding pose to these receptors. Moreover, the codon optimized TEV sequence was cloned between NcoI and XhoI restriction sites of pET-28a(+) expression plasmid. The designed TEV can be used as a promising candidate in allergen-specific immunotherapy against S. kali. Nonetheless, effectiveness of this vaccine should be validated through immunological bioassays.

Tackling suppressive cancer microenvironment by NARF-derived immune modulatory vaccine and its validation using simulation strategies

Introduction: Targeting tumor microenvironment is beneficial and present an ideal setting for the development of futuristic immunotherapy. Here, we make use of Nuclear prelamin A recognition factor (NARF), a protein linked to the coactivation of transcriptional regulators in human breast cancer stem cells (CSC) in our investigation.

Methods: In this study, we initially computed the epitope regions possessing the ability to stimulate both T and B cells within the NARF protein. These identified epitope areas were fused with an adjuvant such as RpfB and RpfE as well as linkers like AAY, GPGPG, KK, and EAAAK. The constructed vaccine was further characterized by assessing its physicochemical properties and population coverage. The potential interactions of the designed vaccine with different toll-like receptors were examined by a sequence of computational studies. Of note, docking study were employed to understand its mechanism of action. Molecular dynamics and immune simulation studies were conducted to comprehend more into their structural stability and immune responses. The resultant vaccine was back-translated, codon-optimised and introduced into pET-28 (+) vector.

Results and discussion: We hypothesize from the results that the designed NARF protein-based vaccine in our analysis could effectively provoke the immune responses in the target organism through TLR-7 binding and promotes MHC class-II mediated antigen presentation. Indeed, comprehensive evaluations conducted in both in vitro and in vivo settings are imperative to substantiate the safety and efficacy of the developed vaccine.

Development of a novel multi‑epitope vaccine against the pathogenic human polyomavirus V6/7 using reverse vaccinology

BACKGROUND

Human polyomaviruses contribute to human oncogenesis through persistent infections, but currently there is no effective preventive measure against the malignancies caused by this virus. Therefore, the development of a safe and effective vaccine against HPyV is of high priority.

METHODS

First, the proteomes of 2 polyomavirus species (HPyV6 and HPyV7) were downloaded from the NCBI database for the selection of the target proteins. The epitope identification process focused on selecting proteins that were crucial, associated with virulence, present on the surface, antigenic, non-toxic, and non-homologous with the human proteome. Then, the immunoinformatic methods were used to identify cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and B-cell epitopes from the target antigens, which could be used to create epitope-based vaccine. The physicochemical features of the designed vaccine were predicted through various online servers. The binding pattern and stability between the vaccine candidate and Toll-like receptors were analyzed through molecular docking and molecular dynamics (MD) simulation, while the immunogenicity of the designed vaccines was assessed using immune simulation.

RESULTS

Online tools were utilized to forecast the most optimal epitope from the immunogenic targets, including LTAg, VP1, and VP1 antigens of HPyV6 and HPyV7. A multi-epitope vaccine was developed by combining 10 CTL, 7 HTL, and 6 LBL epitopes with suitable linkers and adjuvant. The vaccine displayed 98.35% of the world's population coverage. The 3D model of the vaccine structure revealed that the majority of residues (87.7%) were located in favored regions of the Ramachandran plot. The evaluation of molecular docking and MD simulation revealed that the constructed vaccine exhibits a strong binding (-1414.0 kcal/mol) towards the host's TLR4. Moreover, the vaccine-TLR complexes remained stable throughout the dynamic conditions present in the natural environment. The immune simulation results demonstrated that the vaccine design had the capacity to elicit robust immune responses in the host.

CONCLUSION

The multi-parametric analysis revealed that the designed vaccine is capable of inducing sustained immunity against the selected polyomaviruses, although further in-vivo investigations are needed to verify its effectiveness.

Development of a tetravalent subunit vaccine against dengue virus through a vaccinomics approach

Dengue virus infection (DVI) is a mosquito-borne disease that can lead to serious morbidity and mortality. Dengue fever (DF) is a major public health concern that affects approximately 3.9 billion people each year globally. However, there is no vaccine or drug available to deal with DVI. Dengue virus consists of four distinct serotypes (DENV1-4), each raising a different immunological response. In the present study, we designed a tetravalent subunit multi-epitope vaccine, targeting proteins including the structural protein envelope domain III (EDIII), precursor membrane proteins (prM), and a non-structural protein (NS1) from each serotype by employing an immunoinformatic approach. Only conserved sequences obtained through a multiple sequence alignment were used for epitope mapping to ensure efficacy against all serotypes. The epitopes were shortlisted based on an IC50 value <50, antigenicity, allergenicity, and a toxicity analysis. In the final vaccine construct, overall, 11 B-cell epitopes, 10 HTL epitopes, and 10 CTL epitopes from EDIII, prM, and NS1 proteins targeting all serotypes were selected and joined via KK, AAY, and GGGS linkers, respectively. We incorporated a 45-amino-acid-long B-defensins adjuvant in the final vaccine construct for a better immunogenic response. The vaccine construct has an antigenic score of 0.79 via VaxiJen and is non-toxic and non-allergenic. Our refined vaccine structure has a Ramachandran score of 96.4%. The vaccine has shown stable interaction with TLR3, which has been validated by 50 ns of molecular dynamics (MD) simulation. Our findings propose that a designed multi-epitope vaccine has substantial potential to elicit a strong immune response against all dengue serotypes without causing any adverse effects. Furthermore, the proposed vaccine can be experimentally validated as a probable vaccine, suggesting it may serve as an effective preventative measure against dengue virus infection.

Analyzing the Evolution and Host Adaptation of the Rabies Virus from the Perspective of Codon Usage Bias

Rabies virus (RABV) is a highly pathogenic virus that causes a fatal disease in humans and other mammals, but the mechanism of its evolution, spread, and spillover remains unknown. In this study, we analyzed the codon usage pattern of 2,018 RABV full-length genome sequences from 79 countries collected between 1931 and 2021 to provide an insight into its molecular evolution and unravel its unknown host-adapted pattern. We found that RABV exhibited a weak codon usage bias, with a preference for the codons ending in A (28.10 ± 0.01) or U (26.43 ± 0.02). Moreover, natural selection plays a major role in shaping the codon usage bias of the RABV. Notably, nearly half of the 18 codons in the virus were best matched to the hosts' most abundant isoacceptor tRNAs, which might account for the wide range of RABV hosts. Furthermore, significant differences were observed in the codon usage patterns of RABV for different host species, suggesting that codon usage bias may be influenced by host-specific factors. In conclusion, our study reveals codon usage patterns of RABV that may help in the development of control strategies and effective vaccines and therapies against this deadly virus.

Design of a novel multi-epitope vaccine candidate against endometrial cancer using immunoinformatics and bioinformatics approaches

Endometrial cancer (EC) is one of the most common cancers of the female reproductive system. Multi-epitope vaccine may be a promising and effective strategy against EC. In this study, we designed a novel multi-epitope vaccine based on the antigenic proteins PRAME and TMPRSS4 using immunoinformatics and bioinformatics approaches. After a rigorous selection process, 14 cytotoxic T lymphocyte (CTL) epitopes, 6 helper T lymphocyte (HTL) epitopes, and 8 B cell epitopes (BCEs) were finally selected for vaccine construction. To enhance the immunogenicity of the vaccine candidate, the pan HLA DR-binding epitope was included in the vaccine design as an adjuvant. The final vaccine construct had 455 amino acids and a molecular weight of 49.8 kDa, and was predicted to cover 95.03% of the total world population. Docking analysis showed that there were 10 hydrogen bonds and 19 hydrogen bonds in the vaccine-HLA-A*02:01 and vaccine-HLA-DRB1*01:01 complexes, respectively, indicating that the vaccine has a good affinity to MHC molecules. This was further supported by molecular dynamics (MD) simulation. Immune simulation showed that the designed vaccine was able to induce higher levels of immune cell activity, with the secretion of numerous cytokines. The codon adaptation index (CAI) value and GC content of the optimised codon sequences of the vaccine were 0.986 and 54.43%, respectively, indicating that the vaccine has the potential to be highly expressed. The in silico analysis suggested that the designed vaccine may provide a novel therapeutic option for the individualised treatment of EC patients in the future.Communicated by Ramaswamy H. Sarma.

Computational design of a multi-epitope vaccine candidate against Langya henipavirus using surface proteins

In July 2022, Langya henipavirus (LayV) was identified in febrile patients in China. There is currently no approved vaccine against this virus. Therefore, this research aimed to design a multi-epitope vaccine against LayV using reverse vaccinology. The best epitopes were selected from LayV's fusion protein (F) and glycoprotein (G), and a multi-epitope vaccine was designed using these epitopes, adjuvant, and appropriate linkers. The physicochemical properties, antigenicity, allergenicity, toxicity, and solubility of the vaccine were evaluated. The vaccine's secondary and 3D structures were predicted, and molecular docking and molecular dynamics (MD) simulations were used to assess the vaccine's interaction and stability with toll-like receptor 4 (TLR4). Immune simulation, codon optimization, and in silico cloning of the vaccine were also performed. The vaccine candidate showed good physicochemical properties, as well as being antigenic, non-allergenic, and non-toxic, with acceptable solubility. Molecular docking and MD simulation revealed that the vaccine and TLR4 have stable interactions. Furthermore, immunological simulation of the vaccine indicated its ability to elicit immune responses against LayV. The vaccine's increased expression was also ensured using codon optimization. This study's findings were encouraging, but in vitro and in vivo tests are needed to confirm the vaccine's protective effect.Communicated by Ramaswamy H. Sarma.

Comprehensive examination on codon usage bias pattern of the Bovine Ephemeral fever virus

Bovine Ephemeral Fever Virus (BEFV) is a non-contagious virus that commonly infects cattle and water buffalo, reduces milk productivity, decreases the quality of beef, and causes an adverse economic impact on the global livestock industry. However, the evolution of BEFV is unclear, and uncertainty exists regarding its global geodynamics. Consequently, this study aims to comprehend the pattern of viral evolution and gene expression in the BEFV genes G, M, N, and P, including synonymous codons. Additionally, we performed recombination analyses, which exclusively detected recombination signals in the G- and P-genes. Subsequently, a phylogenetic tree was constructed to validate and support these findings. The codon usage bias results showed that the BEFV-selected genes were influenced by both natural and mutation pressure. Furthermore, nucleotide A is more abundant in all the selected genes. The eNC values, ranging from 42.99 to 47.10, revealed the presence of moderate codon usage bias, where gene P exhibited the highest and gene G had the lowest codon usage bias. The neutrality and PR-2 plots, specified codon usage patterns of the genes, are also being shaped by strong selectional pressure. This comprehensive analysis of BEFV genes (G, M, N, and P) sheds light on the molecular evolutionary patterns, co-adaptation, and different genes expression in diverse regions, facilitating the development of preventative programs and insights into viral pathogenesis and vaccine design.Communicated by Ramaswamy H. Sarma.

Novel "GaEl Antigenic Patches" Identified by a "Reverse Epitomics" Approach to Design Multipatch Vaccines against NIPAH Infection, a Silent Threat to Global Human Health

Nipah virus (NiV) is a zoonotic virus that causes lethal encephalitis and respiratory disease with the symptom of endothelial cell-cell fusion. Several NiV outbreaks have been reported since 1999 with nearly annual occurrences in Bangladesh. The outbreaks had high mortality rates ranging from 40 to 90%. No specific vaccine has yet been reported against NiV. Recently, several vaccine candidates and different designs of vaccines composed of epitopes against NiV were proposed. Most of the vaccines target single protein or protein complex subunits of the pathogen. The multiepitope vaccines proposed also cover a largely limited number of epitopes, and hence, their efficiency is still uncertain. To address the urgent need for a specific and effective vaccine against NiV infection, in the present study, we have utilized the "reverse epitomics" approach ("overlapping-epitope-clusters-to-patches" method) to identify "antigenic patches" (Ag-Patches) and utilize them as immunogenic composition for multipatch vaccine (MPV) design. The designed MPVs were analyzed for immunologically crucial parameters, physiochemical properties, and interaction with Toll-like receptor 3 ectodomain. In total, 30 CTL (cytotoxic T lymphocyte) and 27 HTL (helper T lymphocyte) antigenic patches were identified from the entire NiV proteome based on the clusters of overlapping epitopes. These identified Ag-Patches cover a total of discrete 362 CTL and 414 HTL epitopes from the entire proteome of NiV. The antigenic patches were utilized as immunogenic composition for the design of two CTL and two HTL multipatch vaccines. The 57 antigenic patches utilized here cover 776 overlapping epitopes targeting 52 different HLA class I and II alleles, providing a global ethnically distributed human population coverage of 99.71%. Such large number of epitope coverage resulting in large human population coverage cannot be reached with single-protein/subunit or multiepitope based vaccines. The reported antigenic patches also provide potential immunogenic composition for early detection diagnostic kits for NiV infection. Further, all the MPVs and Toll-like receptor ectodomain complexes show a stable nature of molecular interaction with numerous hydrogen bonds, salt bridges, and nonbounded contact formation and acceptable root mean square deviation and fluctuation. The cDNA analysis shows a favorable large-scale expression of the MPV constructs in a human cell line. By utilizing the novel "reverse epitomics" approach, highly immunogenic novel "GaEl antigenic patches" (GaEl Ag-Patches), a synonym term for "antigenic patches", were identified and utilized as immunogenic composition to design four MPVs against NiV. We conclude that the novel multipatch vaccines are potential candidates to combat NiV, with greater effectiveness, high specificity, and large human population coverage worldwide.

In silico analysis of the conserved surface-exposed epitopes to design novel multiepitope peptide vaccine for all variants of the SARS-CoV-2

Recently the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a pervasive threat to generic health. The SARS-CoV-2 spike (S) glycoprotein plays a fundamental role in binds and fusion to the angiotensin-converting enzyme 2 (ACE2). The multi-epitope peptide vaccines would be able to elicit both long-lasting humoral and cellular immune responses, resulting the eliminating SARS-CoV-2 infections as asymptomatic patients are in large numbers. Recently, the omicron variant of the SARS-CoV-2 became a variant of concern that contained just 15-point mutations in the receptor-binding domain of the spike protein. In order to eliminate new evidence on coronavirus variants of concern detected through epidemic intelligence, the conserved epitopes of the receptor-binding domain (RBD) and spike cleavage site is the most probable target for vaccine development to inducing binds and fusion inhibitors neutralizing antibodies respectively. In this study, we utilized bioinformatics tools for identifying and analyzing the spike (S) glycoprotein sequence, e.g. the prediction of the potential linear B-cell epitopes, B-cell multi‑epitope design, secondary and tertiary structures, physicochemical properties, solubility, antigenicity, allergenicity, the molecular docking and molecular dynamics simulation for the promising vaccine candidate against all variant of concern of SARS-CoV-2. Among the epitopes of the RBD region are surface-exposed epitopes SVYAWNRKRISNCV and ATRFASVYAWNRKR as the conserved sequences in all variants of concern can be a good candidate to induce an immune response.Communicated by Ramaswamy H. Sarma.

A multi-epitope based vaccine against the surface proteins expressed in cyst and trophozoite stages of parasite Entamoeba histolytica

Entamoeba histolytica, an anaerobic parasite, infects humans and other primates and causes fatal diseases, such as amebiasis, amebic liver abscesses, and many others. Thousands of people are infected and dying due to the need for a proper protective cure, especially in poor sanitizing regions, such as Latin America, Asia, and Africa. Around 10% of the world population is infected by E. histolytica every year. Consequently, novel preventive approaches are required to eliminate the threats of the parasite. A designed vaccine targeting the exposed proteins that are common between cyst and trophozoite stages of the parasite's life cycle would be an effective way to repress the impact of the parasite. Therefore, an in silico bioinformatics approach was performed to design an effective vaccine targeting surface proteins common between both stages of the parasite's life cycle using B-cell and T-cell epitopes. The epitopes derived from the conserved portions of the proteins and their corresponding isomers specific to the parasite suggested that the vaccine could benefit cross-protection. Furthermore, the three-dimensional structure of the designed vaccine was modelled, refined, and validated using multiple bioinformatics tools. The physiological properties and solubility were also predicted using different algorithmic tools and found to be highly soluble in nature. The vaccine was found interactcted with TLR immune receptors, and the stability was observed via dynamics simulation. Codon optimization and cloning were performed for expression analysis. Immune simulation prediction anticipated significant immune responses with a high IgG and IgM antibodies expression, Th and Tc cells population, B-cell population, memory cells, INF-γ, and IL-2 cytokines. Therefore, the constructed multi-epitope putative vaccine can effectively neutralize the parasite's harmful effects.

In silico design and immunoinformatics analysis of a universal multi-epitope vaccine against monkeypox virus

Monkeypox virus (MPXV) outbreaks have been reported in various countries worldwide; however, there is no specific vaccine against MPXV. In this study, therefore, we employed computational approaches to design a multi-epitope vaccine against MPXV. Initially, cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL), linear B lymphocytes (LBL) epitopes were predicted from the cell surface-binding protein and envelope protein A28 homolog, both of which play essential roles in MPXV pathogenesis. All of the predicted epitopes were evaluated using key parameters. A total of 7 CTL, 4 HTL, and 5 LBL epitopes were chosen and combined with appropriate linkers and adjuvant to construct a multi-epitope vaccine. The CTL and HTL epitopes of the vaccine construct cover 95.57% of the worldwide population. The designed vaccine construct was found to be highly antigenic, non-allergenic, soluble, and to have acceptable physicochemical properties. The 3D structure of the vaccine and its potential interaction with Toll-Like receptor-4 (TLR4) were predicted. Molecular dynamics (MD) simulation confirmed the vaccine's high stability in complex with TLR4. Finally, codon adaptation and in silico cloning confirmed the high expression rate of the vaccine constructs in strain K12 of Escherichia coli (E. coli). These findings are very encouraging; however, in vitro and animal studies are needed to ensure the potency and safety of this vaccine candidate.

Exploring the structural basis to develop efficient multi-epitope vaccines displaying interaction with HLA and TAP and TLR3 molecules to prevent NIPAH infection, a global threat to human health

Nipah virus (NiV) is an emerging zoonotic virus that caused several serious outbreaks in the south asian region with high mortality rates ranging from 40 to 90% since 2001. NiV infection causes lethal encephalitis and respiratory disease with the symptom of endothelial cell-cell fusion. No specific and effective vaccine has yet been reported against NiV. To address the urgent need for a specific and effective vaccine against NiV infection, in the present study, we have designed two Multi-Epitope Vaccines (MEVs) composed of 33 Cytotoxic T lymphocyte (CTL) epitopes and 38 Helper T lymphocyte (HTL) epitopes. Out of those CTL and HTL combined 71 epitopes, 61 novel epitopes targeting nine different NiV proteins were not used before for vaccine design. Codon optimization for the cDNA of both the designed MEVs might ensure high expression potential in the human cell line as stable proteins. Both MEVs carry potential B cell linear epitope overlapping regions, B cell discontinuous epitopes as well as IFN-γ inducing epitopes. Additional criteria such as sequence consensus amongst CTL, HTL and B Cell epitopes was implemented for the design of final constructs constituting MEVs. Hence, the designed MEVs carry the potential to elicit cell-mediated as well as humoral immune response. Selected overlapping CTL and HTL epitopes were validated for their stable molecular interactions with HLA class I and II alleles and in case of CTL epitopes with human Transporter Associated with antigen Processing (TAP) cavity. The structure based epitope cross validation for interaction with TAP cavity was used as another criteria choosing final epitopes for NiV MEVs. Finally, human Beta-defensin 2 and Beta-defensin 3 were used as adjuvants to enhance the immune response of both the MEVs. Molecular dynamics simulation studies of MEVs-TLR3 ectodomain (Human Toll-Like Receptor 3) complex indicated the stable molecular interaction. We conclude that the MEVs designed and in silico validated here could be highly potential vaccine candidates to combat NiV infections, with great effectiveness, high specificity and large human population coverage worldwide.

Employing an immunoinformatics approach revealed potent multi-epitope based subunit vaccine for lymphocytic choriomeningitis virus

BACKGROUND

Lymphocytic choriomeningitis virus (LCMV) infects many individuals worldwide and causes severe infection in the immunosuppressant recipient, spontaneous abortion, and congenital disabilities in infants.

OBJECTIVES

There is no specific vaccine or therapeutics available to protect against LCMV infection; thus, there is a need to design a potential vaccine to combat the virus by developing immunity in the population. Herein, we attempted to design a potent multi-epitope vaccine for LCMV using immunoinformatics methods.

METHODS

The whole proteome of the virus was screened and mapped to extract immunodominant B-cell and T-cell epitopes which were fused with appropriate linkers (EAAAK, GGGS, AAY, GPGPG, and AAY), PADRE sequence (13aa) and an adjuvant (50 S ribosomal protein L7/L12) to formulate a multi-epitope vaccine ensemble. Codon adaptation and in silico cloning of the constructed vaccine were carried out using bioinformatics tools. The secondary and tertiary structure of the vaccine construct was predicted and refined. The physicochemical profile of the designed vaccine was analyzed, and the multi-epitope vaccine's potential to bind Toll-like receptors (TLR2 and TLR4) was evaluated through molecular docking and molecular dynamics simulations. Computational immune simulation of the designed vaccine antigen was performed using the C-ImmSim server.

RESULTS

The designed multi-epitope-based vaccine (613 aa) comprised 26 immunodominant (six B-cell, nine cytotoxic T lymphocytes, and 11 helper T lymphocytes) epitopes and is predicted antigenic, non-toxic, non-allergen, soluble, and topographically accessible with a suitable physicochemical profile. The designed vaccine is expected to cover a broad worldwide population (96.35 %) and stimulate a robust adaptive immune response against the virus upon administration. In silico cloning of the constructed vaccine in PET28a (+) vector ensured its optimal expression in the Escherichia coli system. Molecular docking, molecular dynamics simulation, and binding free energy estimation collectively support the stability and energetically favourable interaction of the modeled vaccine-TLR2/4 complexes.

CONCLUSION

The designed multi-epitope vaccine in the present study could serve as a potential vaccine candidate to protect against LMCV infection; however, the experimental validation and safety testing of the vaccine is warranted to validate the study's outcomes.

CD171 Multi-epitope peptide design based on immuno-informatics approach as a cancer vaccine candidate for glioblastoma

Glioblastoma (GB) is a common primary malignancy of the central nervous system, and one of the highly lethal brain tumors. GB cells can promote therapeutic resistance and tumor angiogenesis. The CD171 is an adhesion molecule in neuronal cells that is expressed in glioma cells as a regulator of brain development during the embryonic period. CD171 is one of the immunoglobulin-like CAMs (cell adhesion molecules) families that can be associated with prognosis in a variety of human tumors. The multi-epitope peptide vaccines are based on synthetic peptides with a combination of both B-cell epitopes and T-cell epitopes, which can induce specific humoral or cellular immune responses. Moreover, Cholera toxin subunit B (CTB), a novel TLR agonist was utilized in the final construct to polarize CD4+ T cells toward T-helper 1 to induce strong cytotoxic T lymphocytes (CTL) responses. In the present study, several immune-informatics tools were used for analyzing the CD171 sequence and studying the important characteristics of a designed vaccine. The results included molecular docking, molecular dynamics simulation, immune response simulation, prediction and validation of the secondary and tertiary structure, physicochemical properties, solubility, conservancy, toxicity as well as antigenicity and allergenicity of the promising candidate for a vaccine against CD171. The immuno-informatic analyze suggested 12 predicted multi-epitope peptides, whose construction consists of 582 residues long. Therewith, cloning adaptation of the designed vaccine was performed, and eventually sequence was inserted into pET30a (+) vector for the application of the anti-glioblastoma vaccine development.Communicated by Ramaswamy H. Sarma.

Molecular cloning, expression, mRNA secondary structure and immunological characterization of mussel foot proteins (Mfps) (Mollusca: Bivalvia)

The macroscale production of mussel foot proteins (Mfps) in the expression system has not succeeded to date. The principal reasons for this are low levels of expression and yield of Mfps, lack of post-translational modifications (PTMs), and immunological toxic effects on the host system. Identification of post-translational modification sites, suitable expression hosts, and immunological responses through an experimental approach is very costly and time-consuming. However, in the present study, in silico post-translation modification, antigenicity, allergenicity, and the immunological reaction of all available Mfps were characterized. Furthermore, all Mfps were codon optimized in three different expression systems to determine the best expression host. Finally, we performed the in-silico cloning of all codon-optimized Mfps in a suitable host (E. coli K12, pET28a(+) vector) and analyzed the secondary structure of mRNA and its structural stability. Among the 78 Mfps, six fps are considered potential allergenic proteins, six fps are considered non-allergenic proteins, and all other fps are probably allergenic. High antigenicity was observed in bacterial cells as compared to yeast and tumor cells. Nevertheless, the predicted expression of Mfps in a bacterial host is higher than in other expression hosts. Important to note that all Mfps showed significant immunological activity in the human system, and we concluded that these antigenic, allergenic, and immunological properties are directly correlated with their amino acid composition. The study's major goal is to provide a comprehensive understanding of Mfps and aid in the future genetic engineering and expression of Mfps and its diverse applications in different fields.Communicated by Ramaswamy H. Sarma.

Immunoinformatics-guided designing and in silico analysis of epitope-based polyvalent vaccines against multiple strains of human coronavirus (HCoV)

OBJECTIVES

The group of human coronaviruses (HCoVs) consists of some highly pathogenic viruses that have caused several outbreaks in the past. The newly emerged strain of HCoV, the SARS-CoV-2 is responsible for the recent global pandemic that has already caused the death of hundreds of thousands of people due to the lack of effective therapeutic options.

METHODS

In this study, immunoinformatics methods were used to design epitope-based polyvalent vaccines which are expected to be effective against four different pathogenic strains of HCoV i.e., HCoV-OC43, HCoV-SARS, HCoV-MERS, and SARS-CoV-2.

RESULTS

The constructed vaccines consist of highly antigenic, non-allergenic, nontoxic, conserved, and non-homologous T-cell and B-cell epitopes from all the four viral strains. Therefore, they should be able to provide strong protection against all these strains. Protein-protein docking was performed to predict the best vaccine construct. Later, the MD simulation and immune simulation of the best vaccine construct also predicted satisfactory results. Finally, in silico cloning was performed to develop a mass production strategy of the vaccine.

CONCLUSION

If satisfactory results are achieved in further in vivo and in vitro studies, then the vaccines designed in this study might be effective as preventative measures against the selected HCoV strains.

A subtractive proteomics and immunoinformatics approach towards designing a potential multi-epitope vaccine against pathogenic Listeriamonocytogenes

Listeria monocytogenes is the causative agent of listeriosis, which is dangerous for pregnant women, the elderly or individuals with a weakened immune system. Individuals with leukaemia, cancer, HIV/AIDS, kidney transplant and steroid therapy suffer from immunological damage are menaced. World Health Organization (WHO) reports that human listeriosis has a high mortality rate of 20-30% every year. To date, no vaccine is available to treat listeriosis. Thereby, it is high time to design novel vaccines against L. monocytogenes. Here, we present computational approaches to design an antigenic, stable and safe vaccine against the L. monocytogenes that could help to control the infections associated with the pathogen. Three vital pathogenic proteins of L. monocytogenes, such as Listeriolysin O (LLO), Phosphatidylinositol-specific phospholipase C (PI-PLC), and Actin polymerization protein (ActA), were selected using a subtractive proteomics approach to design the multi-epitope vaccine (MEV). A total of 5 Cytotoxic T-lymphocyte (CTL) and 9 Helper T-lymphocyte (HTL) epitopes were predicted from these selected proteins. To design the multi-epitope vaccine (MEV) from the selected proteins, CTL epitopes were joined with the AAY linker, and HTL epitopes were joined with the GPGPG linker. Additionally, a human β-defensin-3 (hBD-3) adjuvant was added to the N-terminal side of the final MEV construct to increase the immune response to the vaccine. The final MEV was predicted to be antigenic, non-allergen and non-toxic in nature. Physicochemical property analysis suggested that the MEV construct is stable and could be easily purified through the E. coli expression system. This in-silico study showed that MEV has a robust binding interaction with Toll-like receptor 2 (TLR2), a key player in the innate immune system. Current subtractive proteomics and immunoinformatics study provides a background for designing a suitable, safe and effective vaccine against pathogenic L. monocytogenes.

Analysis of Foot and Mouth Disease Virus Polyprotein for Multi Peptides Vaccine Design: An In silico Strategy

Foot-and-mouth disease virus (FMDV) is small RNA virus from Picornaviridae family; genus Aphthovirus. FMDV causes maximum levels of infectivity in cattle and harmful socioeconomic effects. The present report attempted to design vaccine candidate from the polyprotein of FMDV to stimulate protective immune response. The IEDB server was used to predict B and T cells epitopes that were linked via GPGPG and YAA linkers, respectively. Mycobacterium tuberculosis 50S ribosomal protein was exploited as an adjuvant and a six histidine-tag sequence was linked to the carboxyl end of the vaccine for purification and identification. The predicted vaccine comprised 313aa and was antigenic and not allergic. Moreover, the vaccine was acidic and showed stability and hydrophilicity. Vaccine secondary and tertiary structures were predicted. The tertiary structure was refined to ameliorate the quality of the global and local structures of the vaccine. Vaccine model validation was performed and the final quality score of the structural model was computed. The validated model was used for molecular docking with bovine (N*01801-BoLA-A11) allele. Docking process in terms of binding free energy score was significant. Vaccine solubility was investigated based on the protein of E. coli and the stability was based on the disulfide bonding to lessen the entropic and mobile points in vaccine. Lastly, the in silico cloning ensured the proper cloning and best translation of the DNA of vaccine in molecular vectors.

In silico design of a multi-epitope vaccine against HPV16/18

BACKGROUND

Cervical cancer is the fourth most common cancer affecting women and is caused by human Papillomavirus (HPV) infections that are sexually transmitted. There are currently commercially available prophylactic vaccines that have been shown to protect vaccinated individuals against HPV infections, however, these vaccines have no therapeutic effects for those who are previously infected with the virus. The current study's aim was to use immunoinformatics to develop a multi-epitope vaccine with therapeutic potential against cervical cancer.

RESULTS

In this study, T-cell epitopes from E5 and E7 proteins of HPV16/18 were predicted. These epitopes were evaluated and chosen based on their antigenicity, allergenicity, toxicity, and induction of IFN-γ production (only in helper T lymphocytes). Then, the selected epitopes were sequentially linked by appropriate linkers. In addition, a C-terminal fragment of Mycobacterium tuberculosis heat shock protein 70 (HSP70) was used as an adjuvant for the vaccine construct. The physicochemical parameters of the vaccine construct were acceptable. Furthermore, the vaccine was soluble, highly antigenic, and non-allergenic. The vaccine's 3D model was predicted, and the structural improvement after refinement was confirmed using the Ramachandran plot and ProSA-web. The vaccine's B-cell epitopes were predicted. Molecular docking analysis showed that the vaccine's refined 3D model had a strong interaction with the Toll-like receptor 4. The structural stability of the vaccine construct was confirmed by molecular dynamics simulation. Codon adaptation was performed in order to achieve efficient vaccine expression in Escherichia coli strain K12 (E. coli). Subsequently, in silico cloning of the multi-epitope vaccine was conducted into pET-28a ( +) expression vector.

CONCLUSIONS

According to the results of bioinformatics analyses, the multi-epitope vaccine is structurally stable, as well as a non-allergic and non-toxic antigen. However, in vitro and in vivo studies are needed to validate the vaccine's efficacy and safety. If satisfactory results are obtained from in vitro and in vivo studies, the vaccine designed in this study may be effective as a therapeutic vaccine against cervical cancer.

Designing a novel multi‑epitope vaccine against Ebola virus using reverse vaccinology approach

Ebola virus (EBOV) is a dangerous zoonotic infectious disease. To date, more than 25 EBOV outbreaks have been documented, the majority of which have occurred in Central Africa. The rVSVG-ZEBOV-GP vaccine (ERVEBO), a live attenuated vaccine, has been approved by the US Food and Drug Administration (FDA) to combat EBOV. Because of the several drawbacks of live attenuated vaccines, multi-epitope vaccines probably appear to be safer than live attenuated vaccines. In this work, we employed immunoinformatics tools to design a multi-epitope vaccine against EBOV. We collected sequences of VP35, VP24, VP30, VP40, GP, and NP proteins from the NCBI database. T-cell and linear B-cell epitopes from target proteins were identified and tested for antigenicity, toxicity, allergenicity, and conservancy. The selected epitopes were then linked together in the vaccine's primary structure using appropriate linkers, and the 50S ribosomal L7/L12 (Locus RL7 MYCTU) sequence was added as an adjuvant to the vaccine construct's N-terminal. The physicochemical, antigenicity, and allergenicity parameters of the vaccine were all found to be satisfactory. The 3D model of the vaccine was predicted, refined, and validated. The vaccine construct had a stable and strong interaction with toll-like receptor 4 (TLR4) based on molecular docking and molecular dynamic simulation (MD) analysis. The results of codon optimization and in silico cloning revealed that the proposed vaccine was highly expressed in Escherichia coli (E. coli). The findings of this study are promising; however, experimental validations should be carried out to confirm these findings.

A Systematic Immuno-Informatic Approach to Design a Multiepitope-Based Vaccine Against Emerging Multiple Drug Resistant Serratia marcescens

Serratia marcescens is now an important opportunistic pathogen that can cause serious infections in hospitalized or immunocompromised patients. Here, we used extensive bioinformatic analyses based on reverse vaccinology and subtractive proteomics-based approach to predict potential vaccine candidates against S. marcescens. We analyzed the complete proteome sequence of 49 isolate of Serratia marcescens and identified 5 that were conserved proteins, non-homologous from human and gut flora, extracellular or exported to the outer membrane, and antigenic. The identified proteins were used to select 5 CTL, 12 HTL, and 12 BCL epitopes antigenic, non-allergenic, conserved, hydrophilic, and non-toxic. In addition, HTL epitopes were able to induce interferon-gamma immune response. The selected peptides were used to design 4 multi-epitope vaccines constructs (SMV1, SMV2, SMV3 and SMV4) with immune-modulating adjuvants, PADRE sequence, and linkers. Peptide cleavage analysis showed that antigen vaccines are processed and presented via of MHC class molecule. Several physiochemical and immunological analyses revealed that all multiepitope vaccines were non-allergenic, stable, hydrophilic, and soluble and induced the immunity with high antigenicity. The secondary structure analysis revealed the designed vaccines contain mainly coil structure and alpha helix structures. 3D analyses showed high-quality structure. Molecular docking analyses revealed SMV4 as the best vaccine construct among the four constructed vaccines, demonstrating high affinity with the immune receptor. Molecular dynamics simulation confirmed the low deformability and stability of the vaccine candidate. Discontinuous epitope residues analyses of SMV4 revealed that they are flexible and can interact with antibodies. In silico immune simulation indicated that the designed SMV4 vaccine triggers an effective immune response. In silico codon optimization and cloning in expression vector indicate that SMV4 vaccine can be efficiently expressed in E. coli system. Overall, we showed that SMV4 multi-epitope vaccine successfully elicited antigen-specific humoral and cellular immune responses and may be a potential vaccine candidate against S. marcescens. Further experimental validations could confirm its exact efficacy, the safety and immunogenicity profile. Our findings bring a valuable addition to the development of new strategies to prevent and control the spread of multidrug-resistant Gram-negative bacteria with high clinical relevance.

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.

Vaccines Targeting Numerous Coronavirus Antigens, Ensuring Broader Global Population Coverage: Multi-epitope and Multi-patch Vaccines

Coronaviruses are causative agents of different zoonosis including SARS, MERS, or COVID-19 in humans. The high transmission rate of coronaviruses, the time-consuming development of efficient anti-infectives and vaccines, the possible evolutionary adaptation of the virus to conventional vaccines, and the challenge to cover broad human population worldwide are the major reasons that made it challenging to avoid coronaviruses outbreaks. Although, a plethora of different approaches are being followed to design and develop vaccines against coronaviruses, most of them target subunits, full-length single, or only a very limited number of proteins. Vaccine targeting multiple proteins or even the entire proteome of the coronavirus is yet to come. In the present chapter, we will be discussing multi-epitope vaccine (MEV) and multi-patch vaccine (MPV) approaches to design and develop efficient and sustainably successful strategies against coronaviruses. MEV and MPV utilize highly conserved, potentially immunogenic epitopes and antigenic patches, respectively, and hence they have the potential to target large number of coronavirus proteins or even its entire proteome, allowing us to combat the challenge of its evolutionary adaptation. In addition, the large number of human leukocyte antigen (HLA) alleles targeted by the chosen specific epitopes enables MEV and MPV to cover broader global population.

Immunoinformatics design of a novel epitope-based vaccine candidate against dengue virus

Dengue poses a global health threat, which will persist without therapeutic intervention. Immunity induced by exposure to one serotype does not confer long-term protection against secondary infection with other serotypes and is potentially capable of enhancing this infection. Although vaccination is believed to induce durable and protective responses against all the dengue virus (DENV) serotypes in order to reduce the burden posed by this virus, the development of a safe and efficacious vaccine remains a challenge. Immunoinformatics and computational vaccinology have been utilized in studies of infectious diseases to provide insight into the host-pathogen interactions thus justifying their use in vaccine development. Since vaccination is the best bet to reduce the burden posed by DENV, this study is aimed at developing a multi-epitope based vaccines for dengue control. Combined approaches of reverse vaccinology and immunoinformatics were utilized to design multi-epitope based vaccine from the sequence of DENV. Specifically, BCPreds and IEDB servers were used to predict the B-cell and T-cell epitopes, respectively. Molecular docking was carried out using Schrödinger, PATCHDOCK and FIREDOCK. Codon optimization and in silico cloning were done using JCAT and SnapGene respectively. Finally, the efficiency and stability of the designed vaccines were assessed by an in silico immune simulation and molecular dynamic simulation, respectively. The predicted epitopes were prioritized using in-house criteria. Four candidate vaccines (DV-1-4) were designed using suitable adjuvant and linkers in addition to the shortlisted epitopes. The binding interactions of these vaccines against the receptors TLR-2, TLR-4, MHC-1 and MHC-2 show that these candidate vaccines perfectly fit into the binding domains of the receptors. In addition, DV-1 has a better binding energies of - 60.07, - 63.40, - 69.89 kcal/mol against MHC-1, TLR-2, and TLR-4, with respect to the other vaccines. All the designed vaccines were highly antigenic, soluble, non-allergenic, non-toxic, flexible, and topologically assessable. The immune simulation analysis showed that DV-1 may elicit specific immune response against dengue virus. Moreover, codon optimization and in silico cloning validated the expressions of all the designed vaccines in E. coli. Finally, the molecular dynamic study shows that DV-1 is stable with minimum RMSF against TLR4. Immunoinformatics tools are now applied to screen genomes of interest for possible vaccine target. The designed vaccine candidates may be further experimentally investigated as potential vaccines capable of providing definitive preventive measure against dengue virus infection.

An immunoinformatics approach to design a multi-epitope vaccine against Mycobacterium tuberculosis exploiting secreted exosome proteins

Tuberculosis is one the oldest known affliction of mankind caused by the pathogen Mycobacterium tuberculosis. Till date, there is no absolute single treatment available to deal with the pathogen, which has acquired a great potential to develop drug resistance rapidly. BCG is the only anti-tuberculosis vaccine available till date which displays limited global efficacy due to genetic variation and concurrent pathogen infections. Extracellular vesicles or exosomes vesicle (EVs) lie at the frontier cellular talk between pathogen and the host, and therefore play a significant role in establishing pathogenesis. In the present study, an in-silico approach has been adopted to construct a multi-epitope vaccine from selected immunogenic EVs proteins to elicit a cellular as well as a humoral immune response. Our designed vaccine has wide population coverage and can effectively compensate for the genetic variation among different populations. For maximum efficacy and minimum adverse effects possibilities the antigenic, non-allergenic and non-toxic B-cell, HTL and CTL epitopes from experimentally proven EVs proteins were selected for the vaccine construct. TLR4 agonist RpfE served as an adjuvant for the vaccine construct. The vaccine construct structure was modelled, refined and docked on TLR4 immune receptor. The designed vaccine construct displayed safe usage and exhibits a high probability to elicit the critical immune regulators, like B cells, T-cells and memory cells as displayed by the in-silico immunization assays. Therefore, it can be further corroborated using in vitro and in vivo assays to fulfil the global need for a more efficacious anti-tuberculosis vaccine.

Design of a multi-epitope vaccine against cervical cancer using immunoinformatics approaches

Cervical cancer, caused by human papillomavirus (HPV), is the fourth most common type of cancer among women worldwide. While HPV prophylactic vaccines are available, they have no therapeutic effects and do not clear up existing infections. This study aims to design a therapeutic vaccine against cervical cancer using reverse vaccinology. In this study, the E6 and E7 oncoproteins from HPV16 were chosen as the target antigens for epitope prediction. Cytotoxic T lymphocytes (CTL) and helper T lymphocytes (HTL) epitopes were predicted, and the best epitopes were selected based on antigenicity, allergenicity, and toxicity. The final vaccine construct was composed of the selected epitopes, along with the appropriate adjuvant and linkers. The multi-epitope vaccine was evaluated in terms of physicochemical properties, antigenicity, and allergenicity. The tertiary structure of the vaccine construct was predicted. Furthermore, several analyses were also carried out, including molecular docking, molecular dynamics (MD) simulation, and in silico cloning of the vaccine construct. The results showed that the final proposed vaccine could be considered an effective therapeutic vaccine for HPV; however, in vitro and in vivo experiments are required to validate the efficacy of this vaccine candidate.

Exploring SARS-COV-2 structural proteins to design a multi-epitope vaccine using immunoinformatics approach: An in silico study

In December 2019, a new virus called SARS-CoV-2 was reported in China and quickly spread to other parts of the world. The development of SARS-COV-2 vaccines has recently received much attention from numerous researchers. The present study aims to design an effective multi-epitope vaccine against SARS-COV-2 using the reverse vaccinology method. In this regard, structural proteins from SARS-COV-2, including the spike (S), envelope (E), membrane (M), and nucleocapsid (N) proteins, were selected as target antigens for epitope prediction. A total of five helper T lymphocytes (HTL) and five cytotoxic T lymphocytes (CTL) epitopes were selected after screening the predicted epitopes for antigenicity, allergenicity, and toxicity. Subsequently, the selected HTL and CTL epitopes were fused via flexible linkers. Next, the cholera toxin B-subunit (CTxB) as an adjuvant was linked to the N-terminal of the chimeric structure. The proposed vaccine was analyzed for the properties of physicochemical, antigenicity, and allergenicity. The 3D model of the vaccine construct was predicted and docked with the Toll-like receptor 4 (TLR4). The molecular dynamics (MD) simulation was performed to evaluate the stable interactions between the vaccine construct and TLR4. The immune simulation was also conducted to explore the immune responses induced by the vaccine. Finally, in silico cloning of the vaccine construct into the pET-28 (+) vector was conducted. The results obtained from all bioinformatics analysis stages were satisfactory; however, in vitro and in vivo tests are essential to validate these results.

Immunoinformatics and molecular modeling approach to design universal multi-epitope vaccine for SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmittable and pathogenic human coronavirus that caused a pandemic situation of acute respiratory syndrome, called COVID-19, which has posed a significant threat to global health security. The aim of the present study is to computationally design an effective peptide-based multi-epitope vaccine (MEV) against SARS-CoV-2. The overall model quality of the vaccine candidate, immunogenicity, allergenicity, and physiochemical analysis have been conducted and validated. Molecular dynamics studies confirmed the stability of the candidate vaccine. The docked complexes during the simulation revealed a strong and stable binding interactions of MEV with human and mice toll-like receptors (TLR), TLR3 and TLR4. Finally, candidate vaccine codons have been optimized for their in silico cloning in E. coli expression system, to confirm increased expression. The proposed MEV can be a potential candidate against SARS-CoV-2, but experimental validation is needed to ensure its safety and immunogenicity status.

Structural Analysis of the Polymerase Protein for Multiepitopes Vaccine Prediction against Hepatitis B Virus

Hepatitis B virus (HBV) is the most common cause of hepatocellular carcinoma and liver cirrhosis with significant morbidity and mortality worldwide. DNA polymerase protein of HBV is the immunogenic protein inducing immune response against B and T cells. The aim of this study wasto develop multi-epitope vaccine fromthe polymerase protein elicitingimmune responses.The predicted vaccine comprises epitopes against B and T lymphocytesobtained by IEDB server. The predicted epitopes were linked via suitable spacers (linkers). The 50S ribosomal protein L7/L12 was used as an adjuvant at amino terminal and His-tag at the carboxyl terminal of the vaccine construct. The candidate vaccine contains 457aa and was potentially antigenic and nonallergic. Vaccine molecular weightwas 50.03 KDa with pI of 10.04. The instability index was 25.78 and GRAVY was -0.354 indicating stability andhydrophilicity of the chimeric vaccine,respectively.Vaccine structure (Secondary and tertiary structures) were predicted, refined and used for molecular docking with TLR4.The docking with TLR4 provided energy scores of -1458.7 and -1410.3 for chain A and B, respectively, demonstrated strong binding between the chimeric vaccine and TLR4 chains.The vaccine provided favorable solubility compared to E. coli proteins. Stability via disulfide bonds engineering was predicted to reduce the entropy and mobility regions invaccine construct. Molecular dynamics simulation wasperformed to strengthen the prediction. In silicomolecular cloning was usedto guarantee the efficient clonabilityof the vaccine and translation within suitable vector.

Vaccinomic approach for novel multi epitopes vaccine against severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)

BACKGROUND

The spread of a novel coronavirus termed severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in China and other countries is of great concern worldwide with no effective vaccine. This study aimed to design a novel vaccine construct against SARS-CoV-2 from the spike S protein and orf1ab polyprotein using immunoinformatics tools. The vaccine was designed from conserved epitopes interacted against B and T lymphocytes by the combination of highly immunogenic epitopes with suitable adjuvant and linkers.

RESULTS

The proposed vaccine composed of 526 amino acids and was shown to be antigenic in Vaxigen server (0.6194) and nonallergenic in Allertop server. The physiochemical properties of the vaccine showed isoelectric point of 10.19. The instability index (II) was 31.25 classifying the vaccine as stable. Aliphatic index was 84.39 and the grand average of hydropathicity (GRAVY) was - 0.049 classifying the vaccine as hydrophilic. Vaccine tertiary structure was predicted, refined and validated to assess the stability of the vaccine via Ramachandran plot and ProSA-web servers. Moreover, solubility of the vaccine construct was greater than the average solubility provided by protein sol and SOLpro servers indicating the solubility of the vaccine construct. Disulfide engineering was performed to reduce the high mobile regions in the vaccine to enhance stability. Docking of the vaccine construct with TLR4 demonstrated efficient binding energy with attractive binding energy of - 338.68 kcal/mol and - 346.89 kcal/mol for TLR4 chain A and chain B respectively. Immune simulation significantly provided high levels of immunoglobulins, T-helper cells, T-cytotoxic cells and INF-γ. Upon cloning, the vaccine protein was reverse transcribed into DNA sequence and cloned into pET28a(+) vector to ensure translational potency and microbial expression.

CONCLUSION

A unique vaccine construct from spike S protein and orf1ab polyprotein against B and T lymphocytes was generated with potential protection against the pandemic. The present study might assist in developing a suitable therapeutics protocol to combat SARSCoV-2 infection.

Immunoinformatics analysis to design novel epitope based vaccine candidate targeting the glycoprotein and nucleoprotein of Lassa mammarenavirus (LASMV) using strains from Nigeria

Lassa mammarenavirus (LASMV) is responsible for a specific type of acute viral hemorrhagic fever known as Lassa fever. Lack of effective treatments and counter-measures against the virus has resulted in a high mortality rate in its endemic regions. Therefore, in this study, a novel epitope-based vaccine has been designed using the methods of immunoinformatics targeting the glycoprotein and nucleoprotein of the virus. After numerous robust analyses, two CTL epitopes, eight HTL epitopes and seven B-cell epitopes were finally selected for constructing the vaccine. All these most promising epitopes were found to be antigenic, non-allergenic, nontoxic and non-human homolog, which made them suitable for designing the subunit vaccine. Furthermore, the selected T-cell epitopes which were found to be fully conserved across different isolates of the virus, were also considered for final vaccine construction. After that, numerous validation experiments, i.e. molecular docking, molecular dynamics simulation and immune simulation were conducted, which predicted that our designed vaccine should be stable within the biological environment and effective in combating the LASMV infection. In the end, codon adaptation and in silico cloning studies were performed to design a recombinant plasmid for producing the vaccine industrially. However, further in vitro and in vivo assessments should be done on the constructed vaccine to finally confirm its safety and efficacy.Communicated by Ramaswamy H. Sarma.

Structural Analysis of Avian Encephalomyelitis Virus Polyprotein for Development of Multi Epitopes Vaccine Using Immunoinformatics Approach

Avian Encephalomyelitis (AE) is the disease caused by avian encephalomyelitis virus (AEV). The disease mainly affects young birds nervous system worldwide causing high morbidity and variable mortality rate in chicks and noticed egg dropping and hatchability in mature hens. Vaccination is the only way to control AEV infection since there is no treatment yet to the avian encephalomyelitis. This study aimed to use immunoinformatics approaches to predict multi epitopes vaccine from the AEV polyprotein that could elicit both B and T cells. The vaccine construct comprises 482 amino acids obtained from epitopes predicted against B and T cells by IEDB server, adjuvant, linkers and 6-His-tag. The chimeric vaccine was potentially antigenic and nonallergic and demonstrated thermostability and hydrophilicity in protparam server. The solubility of the vaccine was measured in comparison to E. coli proteins. The stability was also assessed by disulfide bonds engineering to reduce the high mobility regions in the designed vaccine. Furthermore molecular dynamics simulation further strengthen stability of the predicted vaccine. Tertiary structure of the vaccine construct after prediction, refinement was used for molecular docking with chicken alleles BF2*2101 and BF2*0401 and the docking process demonstrated favourable binding energy score of -337.47 kcal/mol and -326.87 kcal/mol, respectively. Molecular cloning demonstrated the potential clonability of the chimeric vaccine in pET28a(+) vector. This could guarantee the efficient translation and expression of the vaccine within suitable expression vector.

Computational Design and Preliminary Serological Analysis of a Novel Multi-Epitope Vaccine Candidate against Onchocerciasis and Related Filarial Diseases

: Onchocerciasis is a skin and eye disease that exerts a heavy socio-economic burden, particularly in sub-Saharan Africa, a region which harbours greater than 96% of either infected or at-risk populations. The elimination plan for the disease is currently challenged by many factors including amongst others; the potential emergence of resistance to the main chemotherapeutic agent, ivermectin (IVM). Novel tools, including preventative and therapeutic vaccines, could provide additional impetus to the disease elimination tool portfolio. Several observations in both humans and animals have provided evidence for the development of both natural and artificial acquired immunity. In this study, immuno-informatics tools were applied to design a filarial-conserved multi-epitope subunit vaccine candidate, (designated Ov-DKR-2) consisting of B-and T-lymphocyte epitopes of eight immunogenic antigens previously assessed in pre-clinical studies. The high-percentage conservation of the selected proteins and epitopes predicted in related nematode parasitic species hints that the generated chimera may be instrumental for cross-protection. Bioinformatics analyses were employed for the prediction, refinement, and validation of the 3D structure of the Ov-DKR-2 chimera. In-silico immune simulation projected significantly high levels of IgG1, T-helper, T-cytotoxic cells, INF-γ, and IL-2 responses. Preliminary immunological analyses revealed that the multi-epitope vaccine candidate reacted with antibodies in sera from both onchocerciasis-infected individuals, endemic normals as well as loiasis-infected persons but not with the control sera from European individuals. These results support the premise for further characterisation of the engineered protein as a vaccine candidate for onchocerciasis.

Multiepitope Subunit Vaccine Design against COVID-19 Based on the Spike Protein of SARS-CoV-2: An In Silico Analysis

The global health crisis caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causal agent of COVID-19, has resulted in a negative impact on human health and on social and economic activities worldwide. Researchers around the globe need to design and develop successful therapeutics as well as vaccines against the novel COVID-19 disease. In the present study, we conducted comprehensive computer-assisted analysis on the spike glycoprotein of SARS-CoV-2 in order to design a safe and potent multiepitope vaccine. In silico epitope prioritization shortlisted six HLA I epitopes and six B-cell-derived HLA II epitopes. These high-ranked epitopes were all connected to each other via flexible GPGPG linkers, and at the N-terminus side, the sequence of Cholera Toxin β subunit was attached via an EAAAK linker. Structural modeling of the vaccine was performed, and molecular docking analysis strongly suggested a positive association of a multiepitope vaccine with Toll-like Receptor 3. The structural investigations of the vaccine-TLR3 complex revealed the formation of fifteen interchain hydrogen bonds, thus validating its integrity and stability. Moreover, it was found that this interaction was thermodynamically feasible. In conclusion, our data supports the proposition that a multiepitope vaccine will provide protective immunity against COVID-19. However, further in vivo and in vitro experiments are needed to validate the immunogenicity and safety of the candidate vaccine.

Engineering a novel subunit vaccine against SARS-CoV-2 by exploring immunoinformatics approach

As the number of infections and deaths caused by the recent COVID-19 pandemic is increasing dramatically day-by-day, scientists are rushing towards developing possible countermeasures to fight the deadly virus, SARS-CoV-2. Although many efforts have already been put forward for developing potential vaccines; however, most of them are proved to possess negative consequences. Therefore, in this study, immunoinformatics methods were exploited to design a novel epitope-based subunit vaccine against the SARS-CoV-2, targeting four essential proteins of the virus i.e., spike glycoprotein, nucleocapsid phosphoprotein, membrane glycoprotein, and envelope protein. The highly antigenic, non-allergenic, non-toxic, non-human homolog, and 100% conserved (across other isolates from different regions of the world) epitopes were used for constructing the vaccine. In total, fourteen CTL epitopes and eighteen HTL epitopes were used to construct the vaccine. Thereafter, several in silico validations i.e., the molecular docking, molecular dynamics simulation (including the RMSF and RMSD studies), and immune simulation studies were also performed which predicted that the designed vaccine should be quite safe, effective, and stable within the biological environment. Finally, in silico cloning and codon adaptation studies were also conducted to design an effective mass production strategy of the vaccine. However, more in vitro and in vivo studies are required on the predicted vaccine to finally validate its safety and efficacy.