Design of a multi-epitope vaccine against SARS-CoV-2 using immunoinformatics approach

Designing novel multiepitope mRNA vaccine targeting Hendra virus (HeV): An integrative approach utilizing immunoinformatics, reverse vaccinology, and molecular dynamics simulation

Human and animal health is threatened by Hendra virus (HeV), which has few treatments. This in-silico vaccine design study focuses on HeV G (glycoprotein), F (fusion protein), and M (matrix protein). These proteins were computationally assessed for B and T-cell epitopes after considering HeV strain conservation, immunogenicity, and antigenicity. To improve vaccination immunogenicity, these epitopes were selectively ligated into a multiepitope construct. To improve vaccination longevity and immunological response, adjuvants and linkers were ligated. G, F, and M epitopes were used to create an mRNA HeV vaccine. Cytotoxic, helper, and linear B-lymphocytes' epitopes are targeted by this vaccine. The population coverage analysis demonstrates that multi-epitope vaccination covers 91.81 percent of CTL and 98.55 percent of HTL epitopes worldwide. GRAVY evaluated the vaccine's well-characterized physicochemical properties -0.503, indicating solubility and functional stability. Structure analysis showed well-stabilized 2° and 3° structures in the vaccine, with alpha helix, beta sheet, and coil structures (Ramachandran score of 88.5% and Z score of -3.44). There was a strong affinity as shown by docking tests with TLR-4 (central score of -1139.4 KJ/mol) and TLR-2 (center score of -1277.9 KJ/mol). The coupled V-apo, V-TLR2, and V-TLR4 complexes were tested for binding using molecular dynamics simulation where extremely stable complexes were found. The predicted mRNA structures provided significant stability. Codon optimization for Escherichia. coli synthesis allowed the vaccine to attain a GC content of 46.83% and a CAI score of 1.0, which supports its significant expression. Immunological simulations indicated vaccine-induced innate and adaptive immune reactions. Finally, this potential HeV vaccine needs more studies to prove its efficacy and safety.

In Silico Design of a Trans-Amplifying RNA-Based Vaccine against SARS-CoV-2 Structural Proteins

Nucleic acid-based vaccines allow scalable, rapid, and cell-free vaccine production in response to an emerging disease such as the current COVID-19 pandemic. Here, we objected to the design of a multiepitope mRNA vaccine against the structural proteins of SARS-CoV-2. Through an immunoinformatic approach, promising epitopes were predicted for the spike (S), envelope (E), membrane (M), and nucleocapsid (N) proteins. Fragments rich in overlapping epitopes were selected based on binding affinities with HLA classes I and II for the specific presentation to B and T lymphocytes. Two constructs were designed by fusing the fragments in different arrangements via GG linkers. Construct 1 showed better structural properties and interactions with toll-like receptor 2 (TLR-2), TLR-3, and TLR-4 during molecular docking and dynamic simulation. A 50S ribosomal L7/L12 adjuvant was added to its N-terminus to improve stability and immunogenicity. The final RNA sequence was used to design a trans-amplifying RNA (taRNA) vaccine in a split-vector system. It consists of two molecules: a nonreplicating RNA encoding a trans-acting replicase to amplify the second one, a trans-replicon (TR) RNA encoding the vaccine protein. Overall, the immune response simulation detected that activated B and T lymphocytes and increased memory cell formation. Macrophages and dendritic cells proliferated continuously, and IFN-γ and cytokines like IL-2 were released highly.

Precise location of three novel linear epitopes using the generated monoclonal antibodies against the Knob domain of FAdV-4 surface structural protein, fiber1

Background

Fowl adenovirus serotype 4 (FAdV-4) is the main pathogen of hepatitis-hydropericardium syndrome (HHS), which brings huge economic losses to the poultry industry worldwide. Fiber-1 protein plays an important role in viral infection and pathogenesis by binding directly to cellular receptors of FAdV-4. In particular, the knob domain of fiber-1 protein has been reported to induce the production of neutralizing antibodies and arouse protection against the lethal challenge of chickens with FAdV-4.

Methods

The fiber-1 knob (F1K) protein was expressed in a prokaryotic expression system and purified using Ni-NTA affinity chromatography. Monoclonal antibodies (mAbs) against FAdV-4 were generated by immunizing BALB/c mice with the purified F1K protein and screened using a series of immunoassays. Potential B cell epitopes on the knob domain of fiber-1 protein were mapped using enzyme-linked immunosorbent assay (ELISA) and dot-blot. Precious location and crucial amino acids of the identified epitopes were determined using peptide array scanning, truncations and alanine-scanning mutagenesis. The epitopes were analyzed and visualized on the knob trimer of FAdV-4 fiber-1 protein using the PyMOL software.

Results

Water-soluble recombinant fiber-1 knob (F1K) protein was obtained with the assistance of chaperone. Four monoclonal antibodies (5C10, 6F8, 8D8, and 8E8) against FAdV-4 were generated and characterized using indirect ELISA, Western blot, dot-blot, and immunological fluorescence assay (IFA). The mAbs were demonstrated to be from different hybridoma cell lines based on the sequences of the variable regions. Meanwhile, three distinct novel linear B-cell epitopes (319SDVGYLGLPPH329, 328PHTRDNWYV336, and 407VTTGPIPFSYQ417) on the knob domain of fiber-1 protein were identified and the key amino acid residues in the epitopes were determined. Structural analysis showed that the two adjacent epitopes 319SDVGYLGLPPH329 and 328PHTRDNWYV336 were exposed on the surface of the fiber-1 knob trimer, whereas the epitope 407VTTGPIPFSYQ417 was located inside of the spatial structure.

Conclusion

This was the first identification of B-cell epitopes on the knob domain of fiber-1 protein and these findings provided a sound basis for the development of subunit vaccines, therapeutics, and diagnostic methods to control FAdV infections.

Exploring computational approaches to design mRNA Vaccine against vaccinia and Mpox viruses

BACKGROUND

Messenger RNA (mRNA) vaccines emerged as a powerful tool in the fight against infections. Unlike traditional vaccines, this unique type of vaccine elicits robust and persistent innate and humoral immune response with a unique host cell-mediated pathogen gene expression and antigen presentation.

METHODS

This offers a novel approach to combat poxviridae infections. From the genome of vaccinia and Mpox viruses, three key genes (E8L, E7R, and H3L) responsible for virus attachment and virulence were selected and employed for designing the candidate mRNA vaccine against vaccinia and Mpox viral infection. Various bioinformatics tools were employed to generate (B cell, CTL, and HTL) epitopes, of which 28 antigenic and immunogenic epitopes were selected and are linked to form the mRNA vaccine construct. Additional components, including a 5' cap, 5' UTR, adjuvant, 3' UTR, and poly(A) tail, were incorporated to enhance stability and effectiveness. Safety measures such as testing for human homology and in silico immune simulations were implemented to avoid autoimmunity and to mimics the immune response of human host to the designed mRNA vaccine, respectively. The mRNA vaccine's binding affinity was evaluated by docking it with TLR-2, TLR-3, TLR-4, and TLR-9 receptors which are subsequently followed by molecular dynamics simulations for the highest binding one to predict the stability of the binding complex.

RESULTS

With a 73% population coverage, the mRNA vaccine looks promising, boasting a molecular weight of 198 kDa and a molecular formula of C8901H13609N2431O2611S48 and it is said to be antigenic, nontoxic and nonallergic, making it safe and effective in preventing infections with Mpox and vaccinia viruses, in comparison with other insilico-designed vaccine for vaccinia and Mpox viruses.

CONCLUSIONS

However, further validation through in vivo and in vitro techniques is underway to fully assess its potential.

Design of a novel multiepitope vaccine with CTLA-4 extracellular domain against Mycoplasma pneumoniae: A vaccine-immunoinformatics approach

BACKGROUND

Community-acquired pneumonia often stems from the macrolide-resistant strain of Mycoplasma pneumoniae, yet no effective vaccine exists against it.

METHODS

This study proposes a vaccine-immunoinformatics strategy for Mycoplasma pneumoniae and other pathogenic microbes. Specifically, dominant B and T cell epitopes of the Mycoplasma pneumoniae P30 adhesion protein were identified through immunoinformatics method. The vaccine sequence was then constructed by coupling with CTLA-4 extracellular region, a novel molecular adjuvant for antigen-presenting cells. Subsequently, the vaccine's physicochemical properties, antigenicity, and allergenicity were verified. Molecular dynamics modeling was employed to confirm interaction with TLR-2, TLR-4, B7-1, and B7-2. Finally, the vaccine underwent in silico cloning for expression.

RESULTS

The vaccine exhibited both antigenicity and non-allergenicity. Molecular dynamics simulation, post-docking with TLR-2, TLR-4, B7-1, and B7-2, demonstrated stable interaction between the vaccine and these molecules. In silico cloning confirmed effective expression of the vaccine gene in insect baculovirus vectors.

CONCLUSION

This vaccine-immunoinformatics approach holds promise for the development of vaccines against Mycoplasma pneumoniae and other pathogenic non-viral and non-bacterial microbes.

An mRNA vaccine for pancreatic cancer designed by applying in silico immunoinformatics and reverse vaccinology approaches

Pancreatic ductal adenocarcinoma is the most prevalent pancreatic cancer, which is considered a significant global health concern. Chemotherapy and surgery are the mainstays of current pancreatic cancer treatments; however, a few cases are suitable for surgery, and most of the cases will experience recurrent episodes. Compared to DNA or peptide vaccines, mRNA vaccines for pancreatic cancer have more promise because of their delivery, enhanced immune responses, and lower proneness to mutation. We constructed an mRNA vaccine by analyzing S100 family proteins, which are all major activators of receptors for advanced glycation end products. We applied immunoinformatic approaches, including physicochemical properties analysis, structural prediction and validation, molecular docking study, in silico cloning, and immune simulations. The designed mRNA vaccine was estimated to have a molecular weight of 165023.50 Da and was highly soluble (grand average of hydropathicity of -0.440). In the structural assessment, the vaccine seemed to be a well-stable and functioning protein (Z score of -8.94). Also, the docking analysis suggested that the vaccine had a high affinity for TLR-2 and TLR-4 receptors. Additionally, the molecular mechanics with generalized Born and surface area solvation analysis of the "Vaccine-TLR-2" (-141.07 kcal/mol) and "Vaccine-TLR-4" (-271.72 kcal/mol) complexes also suggests a strong binding affinity for the receptors. Codon optimization also provided a high expression level with a GC content of 47.04% and a codon adaptation index score 1.0. The appearance of memory B-cells and T-cells was also observed over a while, with an increased level of helper T-cells and immunoglobulins (IgM and IgG). Moreover, the minimum free energy of the mRNA vaccine was predicted at -1760.00 kcal/mol, indicating the stability of the vaccine following its entry, transcription, and expression. This hypothetical vaccine offers a groundbreaking tool for future research and therapeutic development of pancreatic cancer.

Insights into structural vaccinology harnessed for universal coronavirus vaccine development

Structural vaccinology is pivotal in expediting vaccine design through high-throughput screening of immunogenic antigens. Leveraging the structural and functional characteristics of antigens and immune cell receptors, this approach employs protein structural comparison to identify conserved patterns in key pathogenic components. Molecular modeling techniques, including homology modeling and molecular docking, analyze specific three-dimensional (3D) structures and protein interactions and offer valuable insights into the 3D interactions and binding affinity between vaccine candidates and target proteins. In this review, we delve into the utilization of various immunoinformatics and molecular modeling tools to streamline the development of broad-protective vaccines against coronavirus disease 2019 variants. Structural vaccinology significantly enhances our understanding of molecular interactions between hosts and pathogens. By accelerating the pace of developing effective and targeted vaccines, particularly against the rapidly mutating severe acute respiratory syndrome coronavirus 2 and other prevalent infectious diseases, this approach stands at the forefront of advancing immunization strategies. The combination of computational techniques and structural insights not only facilitates the identification of potential vaccine candidates but also contributes to the rational design of vaccines, fostering a more efficient and targeted approach to combatting infectious diseases.

Integrating 16S rRNA profiling and in-silico analysis for an epitope-based vaccine strategy against Achromobacter xylosoxidans infection

Achromobacter xylosoxidans is an aerobic, catalase-positive, non-pigment-forming, Gram-negative, and motile bacterium. It potentially causes a wide range of human infections in cystic fibrosis and non-cystic fibrosis patients. However, developing a safe preventive or therapeutic solution against A. xylosoxidans remains challenging. This study aimed to construct an epitope-based vaccine candidate using immunoinformatic techniques. A. xylosoxidans was isolated from an auto workshop in Lahore, and its identification was confirmed through 16S rRNA amplification and bioinformatic analysis. Two protein targets with GenBank accession numbers AKP90890.1 and AKP90355.1 were selected for the vaccine construct. Both proteins exhibited antigenicity, with scores of 0.757 and 0.580, respectively and the epitopes were selected based on the IC50 value using the ANN 4.0 and NN-align 2.3 epitope prediction method for MHC I and MHC II epitopes respectively and predicted epitopes were analyzed for antigenicity, allergenicity and pathogenicity. The vaccine construct demonstrated structural stability, thermostability, solubility, and hydrophilicity. The vaccine produced 250 B-memory cells per mm3 and approximately 16,000 IgM + IgG counts, indicating an effective immune response against A. xylosoxidans. Moreover, the vaccine candidate interacted stably with toll-like receptor 5, a pattern recognition receptor, with a confidence score of 0.98. These results highlight the potency of the designed vaccine candidate, suggesting its potential to withstand rigorous in vitro and in vivo clinical trials. This epitope-based vaccine could serve as the first preventive immunotherapy against A. xylosoxidans infections, addressing this bacterium's health and financial burdens. The findings demonstrate the value of employing immunoinformatic tools in vaccine development, paving the way for more precise and tailored approaches to combating microbial threats.

Multi-epitope vaccine against SARS-CoV-2 targeting the spike RBD: an immunoinformatics approach

Aim: We designed a SARS-CoV-2 epitope vaccine based on the receptor-binding domain (RBD) in virus spike protein. Methods: RT-PCR performed on nasopharyngeal swab COVID-19 patients. After registering RBD region in the GenBank, physicochemical parameters, secondary structure, homology modeling, 3D structure of RBD region and antigenicity were determined using ProtParam ExPASy, PSIPRED, MolProbity, IEDB and Vaxijen online tools, respectively. Results: B and T cell epitopes were predicted in terms of non-allergenicity and antigenicity. MolProbity analysis provided a qualitative model for RBD. The homology model showed that most of the residues are in optimal district of energy. Conclusion: High immunogenicity score of epitopes indicates promising candidates for the development of multi-epitope vaccines. It may help to develop an effective vaccine.

Multi-epitopevaccines, from design to expression; an in silico approach

The development of vaccines against a wide range of infectious diseases and pathogens often relies on multi-epitope strategies that can effectively stimulate both humoral and cellular immunity. Immunoinformatics tools play a pivotal role in designing such vaccines, enhancing immune response potential, and minimizing the risk of failure. This review presents a comprehensive overview of practical tools for epitope prediction and the associated immune responses. These immunoinformatics tools facilitate the selection of epitopes based on parameters such as antigenicity, absence of toxic and allergenic sequences, secondary and tertiary structures, sequence conservation, and population coverage. The chosen epitopes can be tailored for B-cells or T-cells, both of which require further assessments covered in this study. We offer a range of suitable linkers that effectively separate cytotoxic T lymphocyte and helper T lymphocyte epitopes while preserving their functionality. Additionally, we identify various adjuvants for specific purposes. We delve into the evaluation of MHC-epitope interactions, MHC clusters, and the simulation of final constructs through molecular docking techniques. We provide diverse linkers and adjuvants optimized for epitope functions to bolster immune responses through epitope attachment. By leveraging these comprehensive tools, the development of multi-epitope vaccines holds the promise of robust immunity and a significant reduction in experimental costs.

Unveiling promising immunogenic targets in Coxiella burnetii through in silico analysis: paving the way for novel vaccine strategies

BACKGROUND

Coxiella burnetii, an intracellular pathogen, serves as the causative agent of zoonotic Q fever. This pathogen presents a significant threat due to its potential for airborne transmission, environmental persistence, and pathogenicity. The current whole-cell vaccine (WCV) utilized in Australia to combat Q fever exhibits notable limitations, including severe adverse reactions and limited regulatory approval for human use. This research employed the reverse vaccinology (RV) approach to uncover antigenic proteins and epitopes of C. burnetii, facilitating the development of more potent vaccine candidates.

METHODS

The potential immunogenic proteins derived from C. burnetii RSA493/Nine Mile phase I (NMI) were extracted through manual, automated RV, and virulence factor database (VFDB) methods. Web tools and bioinformatics were used to evaluate physiochemical attributes, subcellular localization, antigenicity, allergenicity, human homology, B-cell epitopes, MHC I and II binding ratios, functional class scores, adhesion probabilities, protein-protein interactions, and molecular docking.

RESULTS

Out of the 1850 proteins encoded by RSA493/NMI, a subset of 178 demonstrated the potential for surface or membrane localization. Following a series of analytical iterations, 14 putative immunogenic proteins emerged. This collection included nine proteins (57.1%) intricately involved in cell wall/membrane/envelope biogenesis processes (CBU_0197 (Q83EW1), CBU_0311 (Q83EK8), CBU_0489 (Q83E43), CBU_0939 (Q83D08), CBU_1190 (P39917), CBU_1829 (Q83AQ2), CBU_1412 (Q83BU0), CBU_1414 (Q83BT8), and CBU_1600 (Q83BB2)). The CBU_1627 (Q83B86 ) (7.1%) implicated in intracellular trafficking, secretion, and vesicular transport, and CBU_0092 (Q83F57) (7.1%) contributing to cell division. Additionally, three proteins (21.4%) displayed uncharacterized functions (CBU_0736 (Q83DJ4), CBU_1095 (Q83CL9), and CBU_2079 (Q83A32)). The congruent results obtained from molecular docking and immune response stimulation lend support to the inclusion of all 14 putative proteins as potential vaccine candidates. Notably, seven proteins with well-defined functions stand out among these candidates.

CONCLUSIONS

The outcomes of this study introduce promising proteins and epitopes for the forthcoming formulation of subunit vaccines against Q fever, with a primary emphasis on cellular processes and the virulence factors of C. burnetii.

Immunodominant conserved moieties on spike protein of SARS-CoV-2 renders virulence factor for the design of epitope-based peptide vaccines

The outbreak of novel SARS-CoV-2 virion has wreaked havoc with a high prevalence of respiratory illness and high transmission due to a vague understanding of the viral antigenicity, augmenting the dire challenge to public health globally. This viral member necessitates the expansion of diagnostic and therapeutic tools to track its transmission and confront it through vaccine development. Therefore, prophylactic strategies are mandatory. Virulent spike proteins can be the most desirable candidate for the computational design of vaccines targeting SARS-CoV-2, followed by the meteoric development of immune epitopes. Spike protein was characterized using existing bioinformatics tools with a unique roadmap related to the immunological profile of SARS-CoV-2 to predict immunogenic virulence epitopes based on antigenicity, allergenicity, toxicity, immunogenicity, and population coverage. Applying in silico approaches, a set of twenty-four B lymphocyte-based epitopes and forty-six T lymphocyte-based epitopes were selected. The predicted epitopes were evaluated for their intrinsic properties. The physico-chemical characterization of epitopes qualifies them for further in vitro and in vivo analysis and pre-requisite vaccine development. This study presents a set of screened epitopes that bind to HLA-specific allelic proteins and can be employed for designing a peptide vaccine construct against SARS-CoV-2 that will confer vaccine-induced protective immunity due to its structural stability.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13337-023-00852-9.

A new candidate epitope-based vaccine against PspA PhtD of Streptococcus pneumoniae: a computational experimental approach

Introduction

Pneumococcus is an important respiratory pathogen that is associated with high rates of death in newborn children and the elderly. Given the disadvantages of current polysaccharide-based vaccines, the most promising alternative for developing improved vaccines may be to use protein antigens with different roles in pneumococcus virulence. PspA and PhtD, highly immunogenic surface proteins expressed by almost all pneumococcal strains, are capable of eliciting protective immunity against lethal infections.

Methods

In this study using immunoinformatics approaches, we constructed one fusion construct (called PAD) by fusing the immunodominant regions of PspA from families 1 & 2 (PA) to the immunodominant regions of PhtD (PD). The objective of this project was to test the immunogenicity of the fusion protein PAD and to compare its protective activity against S. pneumoniae infection with PA or PD alone and a combination of PA and PD. The prediction of physicochemical properties, antigenicity, allergenicity, toxicity, and 3D-structure of the constructs, as well as molecular docking with HLA receptor and immune simulation were performed using computational tools. Finally, mice were immunized and the serum levels of antibodies/cytokines and functionality of antibodies in vitro were evaluated after immunization. The mice survival rates and decrease of bacterial loads in the blood/spleen were examined following the challenge.

Results

The computational analyses indicated the proposed constructs could be antigenic, non-allergenic, non-toxic, soluble and able to elicit robust immune responses. The results of actual animal experiments revealed the candidate vaccines could induce the mice to produce high levels of antibodies and cytokines. The complement-mediated bactericidal activity of antibodies was confirmed and the antibodies provided favorable survival in immunized mice after bacterial challenge. In general, the experimental results verified the immunoinformatics studies.

Conclusion

For the first time this report presents novel peptide-based vaccine candidates consisting of immunodominant regions of PspA and PhtD antigens. The obtained findings confirmed that the fusion formulation could be relatively more efficient than the individual and combination formulations. The results propose that the fusion protein alone could be used as a serotype-independent pneumococcal vaccine or as an effective partner protein for a conjugate polysaccharide vaccine.

Integrated immunoinformatics and subtractive proteomics approach for multi-epitope vaccine designing to combat S. pneumoniae TIGR4

Streptococcus pneumoniae is one of the major precarious pathogens accountable for over 1.2 million fatalities annually. The key drivers for pneumococcal vaccine development involve high morbidity and mortality in over one million cases, especially in very young children and the elderly. In this study, immunoinformatics was integrated with subtractive proteomics to find antigenic proteins for designing a multi-epitope vaccine against S. pneumoniae. As prospective vaccine targets, the developed pipeline identified two antigenic proteins, i.e., penicillin-binding protein and ATP synthase subunit. Several immunoinformatics and bioinformatics resources were used to forecast T- and B-cell epitopes from specific proteins. By employing a mixture of five cytotoxic T-cell lymphocytes, six helper T-cell lymphocytes, and seven linear B-cell lymphocyte epitopes, a 392 amino acid-long vaccine was designed. To enhance immune responses, the designed vaccine was coupled with a cholera enterotoxin subunit B adjuvant. The designed vaccine was highly antigenic, non-allergenic, and stable for human usage. The stability of the vaccine with toll-like receptor-4 was evaluated by molecular docking and molecular dynamic simulation. In addition, immunological simulation was performed to test its real-world potency. The vaccine codon was then cloned in silico. Overall, this study paves the way for the development of a multi-epitope S. pneumoniae vaccine under laboratory conditions. Furthermore, the current findings warrant for the experimental validation of the final multi-epitope vaccine construct to demonstrate its immunological reinforcing capability and clinical applicability.

Structural immunoinformatics approach for rational design of a multi-epitope vaccine against triple negative breast cancer

TNBC is a highly malignant breast cancer known for its aggressive behavior affecting young female adults. The standard treatment for TNBC includes surgery, chemotherapy, and radiotherapy, which often have significant side effects. Therefore, novel preventive methods are required to combat TNBC effectively. In this study, we utilized immunoinformatics to construct an in-silico vaccine against TNBC using the TRIM25 molecule via the reverse vaccinology method. Four vaccines were designed by generating T and B-cell epitopes linked with four different linkers. The modeled vaccine was docked and the results showed that vaccine-3 exhibited the highest affinity with the immune receptors. The molecular dynamics results revealed that the binding affinity and stability of Vaccine-3 were greater than those of Vaccine 2 complexes. This study has great potential preventive measures for TNBC, and further research is warranted to evaluate its efficacy in preclinical settings. This study presents an innovative preventive strategy for triple-negative breast cancer (TNBC) through immunoinformatics and reverse vaccinology to develop an in-silico vaccine. Leveraging these innovative techniques offers a novel avenue for combating the complex challenges associated with TNBC. This approach demonstrates considerable potential as a significant breakthrough in preventive measures for this particularly aggressive and malignant form of breast cancer.

Recent trends in next generation immunoinformatics harnessed for universal coronavirus vaccine design

The ongoing pandemic of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has globally devastated public health, the economies of many countries and quality of life universally. The recent emergence of immune-escaped variants and scenario of vaccinated individuals being infected has raised the global concerns about the effectiveness of the current available vaccines in transmission control and disease prevention. Given the high rate mutation of SARS-CoV-2, an efficacious vaccine targeting against multiple variants that contains virus-specific epitopes is desperately needed. An immunoinformatics approach is gaining traction in vaccine design and development due to the significant reduction in time and cost of immunogenicity studies and increasing reliability of the generated results. It can underpin the development of novel therapeutic methods and accelerate the design and production of peptide vaccines for infectious diseases. Structural proteins, particularly spike protein (S), along with other proteins have been studied intensively as promising coronavirus vaccine targets. Numbers of promising online immunological databases, tools and web servers have widely been employed for the design and development of next generation COVID-19 vaccines. This review highlights the role of immunoinformatics in identifying immunogenic peptides as potential vaccine targets, involving databases, and prediction and characterization of epitopes which can be harnessed for designing future coronavirus vaccines.

Immunoinformatics-aided design of a new multi-epitope vaccine adjuvanted with domain 4 of pneumolysin against Streptococcus pneumoniae strains

BACKGROUND

Streptococcus pneumoniae (Pneumococcus) has remained a leading cause of fatal infections such as pneumonia, meningitis, and sepsis. Moreover, this pathogen plays a major role in bacterial co-infection in patients with life-threatening respiratory virus diseases such as influenza and COVID-19. High morbidity and mortality in over one million cases, especially in very young children and the elderly, are the main motivations for pneumococcal vaccine development. Due to the limitations of the currently marketed polysaccharide-based vaccines, non-serotype-specific protein-based vaccines have received wide research interest in recent years. One step further is to identify high antigenic regions within multiple highly-conserved proteins in order to develop peptide vaccines that can affect various stages of pneumococcal infection, providing broader serotype coverage and more effective protection. In this study, immunoinformatics tools were used to design an effective multi-epitope vaccine in order to elicit neutralizing antibodies against multiple strains of pneumococcus.

RESULTS

The B- and T-cell epitopes from highly protective antigens PspA (clades 1-5) and PhtD were predicted and immunodominant peptides were linked to each other with proper linkers. The domain 4 of Ply, as a potential TLR4 agonist adjuvant candidate, was attached to the end of the construct to enhance the immunogenicity of the epitope vaccine. The evaluation of the physicochemical and immunological properties showed that the final construct was stable, soluble, antigenic, and non-allergenic. Furthermore, the protein was found to be acidic and hydrophilic in nature. The protein 3D-structure was built and refined, and the Ramachandran plot, ProSA-web, ERRAT, and Verify3D validated the quality of the final model. Molecular docking analysis showed that the designed construct via Ply domain 4 had a strong interaction with TLR4. The structural stability of the docked complex was confirmed by molecular dynamics. Finally, codon optimization was performed for gene expression in E. coli, followed by in silico cloning in the pET28a(+) vector.

CONCLUSION

The computational analysis of the construct showed acceptable results, however, the suggested vaccine needs to be experimentally verified in laboratory to ensure its safety and immunogenicity.

In-silico design and evaluation of an epitope-based serotype-independent promising vaccine candidate for highly cross-reactive regions of pneumococcal surface protein A

BACKGROUND

The pathogenicity of pneumococcus with high morbidity, mortality, and multi-drug resistance patterns has been increasing. The limited coverage of the licensed polysaccharide-based vaccines and the replacement of the non-vaccine serotypes are the main reasons for producing a successful serotype-independent vaccine. Pneumococcal surface protein A (PspA) is an extremely important virulence factor and an interesting candidate for conserved protein-based pneumococcal vaccine classified into two prominent families containing five clades. PspA family-elicited immunity is clade-dependent, and the level of the PspA cross-reactivity is restricted to the same family.

METHODS

To cover and overcome the clade-dependent immunity of the PspAs in this study, we designed and tested a PspA_1-5c+p vaccine candidate composed of the highest immunodominant coverage of B- and T-cell epitope truncated domain of each clade focusing on two cross-reactive B and C regions of the PspAs. The antigenicity, toxicity, physicochemical properties, 3D structure prediction, stability and flexibility of the designed protein using molecular dynamic (MD) simulation, molecular docking of the construct withHLADRB1*(01:01) and human lactoferrin N-lop, and immune simulation were assessed using immunoinformatics tools. In the experimental section, after intraperitoneal immunization of the mice with Alum adjuvanted recombinant PspA_1-5c+p, we evaluated the immune response, cross-reactivity, and functionality of the Anti-PspA_1-5c+p antibody using ELISA, Opsonophagocytic killing activity, and serum bactericidal assay.

RESULTS

For the first time, this work suggested a novel PspA-based vaccine candidate using immunoinformatics tools. The designed PspA_1-5c+p protein is predicted to be highly antigenic, non-toxic, soluble, stable with low flexibility in MD simulation, and able to stimulate both humoral and cellular immune responses. The designed protein also could interact strongly with HLADRB1*(01:01) and human lactoferrin N-lop in the docking study. Our immunoinformatics predictions were validated using experimental data. Results showed that the anti-PspA_1-5c+p IgG not only had a high titer with strong and same cross-reactivity coverage against all pneumococcal serotypes used but also had high and effective bioactivity for pneumococcal clearance using complement system and phagocytic cells.

CONCLUSION

Our findings elucidated the potential application of the PspA_1-5c+p vaccine candidate as a serotype-independent pneumococcal vaccine with a strong cross-reactivity feature. Further in-vitro and in-vivo investigations against other PspA clades should be performed to confirm the full protection of the PspA_1-5c+p vaccine candidate.

Current Update on Rotavirus in-Silico Multiepitope Vaccine Design

Rotavirus gastroenteritis is one of the leading causes of pediatric morbidity and mortality worldwide in infants and under-five populations. The World Health Organization (WHO) recommended global incorporation of the rotavirus vaccine in national immunization programs to alleviate the burden of the disease. Implementation of the rotavirus vaccination in certain regions of the world brought about a significant and consistent reduction of rotavirus-associated hospitalizations. However, the efficacy of licensed vaccines remains suboptimal in low-income countries where the incidences of rotavirus gastroenteritis continue to happen unabated. The problem of low efficacy of currently licensed oral rotavirus vaccines in low-income countries necessitates continuous exploration, design, and development of new rotavirus vaccines. Traditional vaccine development is a complex, expensive, labor-intensive, and time-consuming process. Reverse vaccinology essentially utilizes the genome and proteome information on pathogens and has opened new avenues for in-silico multiepitope vaccine design for a plethora of pathogens, promising time reduction in the complete vaccine development pipeline by complementing the traditional vaccinology approach. A substantial number of reviews on licensed rotavirus vaccines and those under evaluation are already available in the literature. However, a collective account of rotavirus in-silico vaccines is lacking in the literature, and such an account may further fuel the interest of researchers to use reverse vaccinology to expedite the vaccine development process. Therefore, the main focus of this review is to summarize the research endeavors undertaken for the design and development of rotavirus vaccines by the reverse vaccinology approach utilizing the tools of immunoinformatics.

Design of a multi-epitope-based vaccine consisted of immunodominant epitopes of structural proteins of SARS-CoV-2 using immunoinformatics approach

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has shown rapid global spread and has resulted in a significant death toll worldwide. In this study, we aimed to design a multi-epitope vaccine against SARS-CoV-2 based on structural proteins S, M, N, and E. We identified B- and T-cell epitopes and then the antigenicity, toxicity, allergenicity, and similarity of predicted epitopes were analyzed. T-cell epitopes were docked with corresponding HLA alleles. Consequently, the selected T- and B-cell epitopes were included in the final construct. All selected epitopes were connected with different linkers and flagellin and pan-HLA DR binding epitopes (PADRE) as an adjuvant were used in the vaccine construct. Furthermore, molecular docking was used to evaluate the complex between the final vaccine construct and two alleles, HLA-A*02:01 and HLA-DRB1*01:01. Finally, codons were optimized for in silico cloning into pET28a(+) vector using SnapGene. The final vaccine construct comprised 11 CTL, HTL, and B-cell epitopes corresponding to 394 amino acid residues. In silico evaluation showed that the designed vaccine might potentially promote an immune response. Further in vivo preclinical and clinical testing is required to determine the safety and efficacy of the designed vaccine.

Identification and design of a multi-epitope subunit vaccine against the opportunistic pathogen Staphylococcus epidermidis: An immunoinformatics approach

Staphylococcus epidermidis is one of the major causes of nosocomial infections around the globe that leads to a high rate of mortality and morbidity in both immunocompromised patients and preterm infants. Despite the alarming increase in multi-drug resistance, no promising vaccines are readily available against this pathogen. Thus, the present study is focused on designing a multi-epitope subunit vaccine using five antigenic proteins of S. epidermidis through an immunoinformatics approach. The final vaccine comprised B-cell, HTL, and CTL binding epitopes followed by Lipoprotein LprA adjuvant added at N-terminal to augment the immunogenicity. Physicochemical assessment of the vaccine reveals the antigenic and non-allergic nature. The vaccine structure was designed, refined, validated, and disulfide engineered to obtain the best model. Molecular docking and dynamics simulation of the proposed vaccine with toll-like receptors (TLR-2 and TLR-4) showed strong and stable interactions. MM-PBSA analysis was implemented as an efficient tool to determine the intermolecular binding free energies of the system. The vaccine was subjected to immune simulation to predict its immunogenic profile. In silico cloning suggested that the proposed vaccine can be expressed efficiently in E.coli. Furthermore, in vivo animal experiment is needed to determine the effectiveness of the in silico designed vaccine.Communicated by Ramaswamy H. Sarma.

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

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

Immunoinformatics approach to epitope-based vaccine design against the SARS-CoV-2 in Bangladeshi patients

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the ongoing coronavirus disease 2019 (COVID-19) pandemic which has brought a great challenge to public health. After the first emergence of novel coronavirus SARS-CoV-2 in the city of Wuhan, China, in December 2019. As of March 2020, SARS-CoV-2 was first reported in Bangladesh and since then the country has experienced a steady rise in infections, resulting in 13,355,191 cases and 29,024 deaths as of 27 February 2022. Bioinformatics techniques are used to predict B cell and T cell epitopes from the new SARS-CoV-2 spike glycoprotein in order to build a unique multiple epitope vaccine. The immunogenicity, antigenicity scores, and toxicity of these epitopes were evaluated and chosen based on their capacity to elicit an immune response.

RESULT

The best multi-epitope of the possible immunogenic property was created by combining epitopes. EAAAK, AAY, and GPGPG linkers were used to connect the epitopes. In several computer-based immune response analyses, this vaccine design was found to be efficient, as well as having high population coverage.

CONCLUSION

This research is entirely reliant on the development of epitope-based vaccines, and these in silico findings would represent a major step forward in the development of a vaccine that might eradicate SARS-CoV-2 in Bangladeshi patients.

Design, construction and in vivo functional assessment of a hinge truncated sFLT01

Gene therapy for the treatment of ocular neovascularization has reached clinical trial phases. The AAV2-sFLT01 construct was already evaluated in a phase 1 open-label trial administered intravitreally to patients with advanced neovascular age-related macular degeneration. SFLT01 protein functions by binding to VEGF and PlGF molecules and inhibiting their activities simultaneously. It consists of human VEGFR1/Flt-1 (hVEGFR1), a polyglycine linker, and the Fc region of human IgG1. The IgG1 upper hinge region of the sFLT01 molecule makes it vulnerable to radical attacks and prone to causing immune reactions. This study pursued two goals: (i) minimizing the immunogenicity and vulnerability of the molecule by designing a truncated molecule called htsFLT01 (hinge truncated sFLT01) that lacked the IgG1 upper hinge and lacked 2 amino acids from the core hinge region; and (ii) investigating the structural and functional properties of the aforesaid chimeric molecule at different levels (in silico, in vitro, and in vivo). Molecular dynamics simulations and molecular mechanics energies combined with Poisson-Boltzmann and surface area continuum solvation calculations revealed comparable free energy of binding and binding affinity for sFLT01 and htsFLT01 to their cognate ligands. Conditioned media from human retinal pigment epithelial (hRPE) cells that expressed htsFLT01 significantly reduced tube formation in HUVECs. The AAV2-htsFLT01 virus suppressed vascular development in the eyes of newborn mice. The htsFLT01 gene construct is a novel anti-angiogenic tool with promising improvements compared to existing treatments.

Pan-Genome-Assisted Computational Design of a Multi-Epitopes-Based Vaccine Candidate against Helicobacter cinaedi

Helicobacter cinaedi is a Gram-negative bacterium from the family Helicobacteraceae and genus Helicobacter. The pathogen is a causative agent of gastroenteritis, cellulitis, and bacteremia. The increasing antibiotic resistance pattern of the pathogen prompts the efforts to develop a vaccine to prevent dissemination of the bacteria and stop the spread of antibiotic resistance (AR) determinants. Herein, a pan-genome analysis of the pathogen strains was performed to shed light on its core genome and its exploration for potential vaccine targets. In total, four vaccine candidates (TonB dependent receptor, flagellar hook protein FlgE, Hcp family type VI secretion system effector, flagellar motor protein MotB) were identified as promising vaccine candidates and subsequently subjected to an epitopes' mapping phase. These vaccine candidates are part of the pathogen core genome: they are essential, localized at the pathogen surface, and are antigenic. Immunoinformatics was further applied on the selected vaccine proteins to predict potential antigenic, non-allergic, non-toxic, virulent, and DRB*0101 epitopes. The selected epitopes were then fused using linkers to structure a multi-epitopes' vaccine construct. Molecular docking simulations were conducted to determine a designed vaccine binding stability with TLR5 innate immune receptor. Further, binding free energy by MMGB/PBSA and WaterSwap was employed to examine atomic level interaction energies. The designed vaccine also stimulated strong humoral and cellular immune responses as well as interferon and cytokines' production. In a nutshell, the designed vaccine is promising in terms of immune responses' stimulation and could be an ideal candidate for experimental analysis due to favorable physicochemical properties.

Mechanistic insights into phenanthrene acropetal translocation via wheat xylem: Separation and identification of transfer proteins

Polycyclic aromatic hydrocarbons (PAHs) have the potential to cause cancer, teratogenicity, and mutagenesis in humans. Long-term plant safe production relies on how PAHs are transported and coordinated across organs. However, the acropetal transfer mechanism of PAHs in staple crop stems, particularly in xylem, a critical path, is unknown. Herein, we first confirmed the presence of specific interaction between the proteins and phenanthrene by employing the magnetic phenanthrene-bound bead immunoassay and label free liquid chromatograph mass spectrometer (LC-MS/MS), suggesting that peroxidase (uniprot accession: A0A3B5XXD0) and unidentified proteins (uniprot accession: A0A3B6LUC6) may function as the carriers to load and acropetally translocate phenanthrene (a model PAH) in wheat xylem. This specified binding of protein-phenanthrene may form through hydrophobic interactions in the conservative binding region, as revealed by protein structural investigations and molecular docking. To further investigate the role of these proteins in phenanthrene solubilization, phenanthrene exposure was conducted: a substantial quantity of peroxidase was produced; an unusually high expression of uncharacterized proteins was observed, indicating their positive effects in the acropetal transfer of phenanthrene in wheat xylem. These data confirmed that the two proteins are crucial in the solubilization of phenanthrene in wheat xylem sap. Our findings provide fresh light on the molecular mechanism of PAH loading in plant xylem and techniques for ensuring the security of staple crops and improving the efficacy of phytoremediation in a PAH-contaminated environment.

Molecular modelling on multiepitope-based vaccine against SARS-CoV-2 using immunoinformatics, molecular docking, and molecular dynamics simulation

The pandemic of COVID-19 caused by SARS-CoV-2 has made a worldwide health emergency. Despite the fact that current vaccines are readily available, several SARSCoV-2 variants affecting the existing vaccine are to be less effective due to the mutations in the structural proteins. Furthermore, the appearance of the new variants cannot be easily predicted in the future. Therefore, the attempts to construct new vaccines or to modify the current vaccines are still pivotal works for preventing the spread of the virus. In the present investigation, the computational analysis through immunoinformatics, molecular docking, and molecular dynamics (MD) simulation is employed to construct an effective vaccine against SARS-CoV2. The structural proteins of SARS-CoV2 are utilized to create a multiepitope-based vaccine (MEV). According to our findings presented by systematic procedures in the current investigation, the MEV construct may be able to trigger a strong immunological response against the virus. Therefore, the designed MEV could be a potential vaccine candidate against SARS-CoV-2, and also it is expected to be effective for other variants.

Reverse vaccinology approach to identify novel and immunogenic targets against Porphyromonas gingivalis: An in silico study

Porphyromonas gingivalis is a primary causative agent of chronic periodontitis. Moreover, it leads to several systemic diseases, including rheumatoid arthritis, cardiovascular, neurodegenerative, and Alzheimer’s diseases. It seems that the development of a vaccine against this bacterium is necessary. Thus, this study decided to identify novel immunogenic targets and developed multiple epitope-based vaccines against P. gingivalis. For this purpose, the pan/core-proteome of this bacterium was studied, and the suitable vaccine targets were selected based on different properties, including exposed localization of proteins, antigenicity, non-allergenicity, non-similarity to host proteome, stability, B-cell epitopes and MHC II binding sites, sequence conservation, molecular docking, and immune simulation. Through the quartile scoring method, 12 proteins with ≥ 20 scores were considered as suitable immunogenic targets. The results of the protein domain and functional class search showed that most of the immunogenic proteins were involved in the transport and metabolism of inorganic ions and lipids. In addition, two unknown function proteins, including WP_004584259.1 and WP_099780539.1 were detected as immunogenic targets. Three constructions carrying multi-epitopes were generated including Naked, LCL, and as chimeric structures. Among them, FliC chimeric protein had the strongest affinity to the human TLR2, 4, and 6, while the LCL platform represented the highest level of immune stimulation response. The obtained results from this study revealed new insights into prophylactic routes against P. gingivalis by introducing novel immunogenic targets. However, further investigations, including site-directed mutation and immunoassay are needed to confirm the pathogenic role and protectivity of these novel proteins.

Immunoinformatics-guided designing of epitope-based subunit vaccine from Pilus assembly protein of Acinetobacter baumannii bacteria

Acinetobacter baumannii, a prominent pathogen responsible for chronic infections in the blood, urinary tract, and lungs, has a high mortality due to its virulence and limited preventive methods. The present study aims to characterize the pilus assembly protein of A. baumannii to offer leads for epitope-based vaccine development. FilF is the putative pilus assembly protein that reportedly plays a supreme character in the virulence of this WHO-listed ESKAPE bacterium. Implementing various bioinformatics tools, led to the recognition of many antigenic B and T cell epitopes. Most promising B and T-cell epitopes were selected based on their binding efficiency with commonly occurring MHC alleles. Finally, we stepped down to fourteen protective antigenic peptides. These epitopes were also revealed to be non-allergenic and non-toxic. As a result, a vaccine chimera was created by linking these epitopes with appropriate linkers and adjuvant such as β-defensins. Furthermore, homology modeling and validation were carried out, with the modeled structure being employed for molecular docking with the immunological receptor (TLR-4) found on lymphocyte cells. As a result of the molecular dynamics simulation, the interaction between human TLR-4 and the multi-epitope vaccine sequence was stable. Finally, in silico cloning and immune simulation were carried out to see the efficacy of the construct vaccine. This is the first study targeting the pilus assembly protein from A. baumannii to identify novel epitopes that hold potential for further experimental design of multi-peptide vaccine construct against the pathogen.

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

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

Role of genomics in combating COVID-19 pandemic

The coronavirus disease 2019 (COVID-19) quickly swept over the world, becoming one of the most devastating outbreaks in human history. Being the first pandemic in the post-genomic era, advancements in genomics contributed significantly to scientific understanding and public health response to COVID-19. Genomic technologies have been employed by researchers all over the world to better understand the biology of SARS-CoV-2 and its origin, genomic diversity, and evolution. Worldwide genomic resources have greatly aided in the investigation of the COVID-19 pandemic. The pandemic has ushered in a new era of genomic surveillance, wherein scientists are tracking the changes of the SARS-CoV-2 genome in real-time at the international and national levels. Availability of genomic and proteomic information enables the rapid development of molecular diagnostics and therapeutics. The advent of high-throughput sequencing and genome editing technologies led to the development of modern vaccines. We briefly discuss the impact of genomics in the ongoing COVID-19 pandemic in this review.

Partial sequence conservation of SARS-CoV-2 NSP-2, NSP-12, and Spike in stool samples from Abadan, Iran

Since the onset of the coronavirus disease 2019 (COVID-19) pandemic, the clinical manifestations of the virus have undergone many changes. Recently, there have been many reports on gastrointestinal symptoms in COVID-19 patients. This study is aimed to perform a detailed phylogenetic study and assessment of different SNVs in the RNA genome of viruses isolated from fecal samples of patients with COVID-19 who have gastrointestinal symptoms, which can help better understand viral pathogenesis. In the present study, 20 fecal samples were collected by written consent from COVID-19 patients. According to the manufacturer's protocol, virus nucleic acid was extracted from stool samples and the SARS-CoV-2 genome presence in stool samples was confirmed by RT-PCR assay. Three viral genes, S, nsp12, and nsp2, were amplified using the reverse transcription polymerase chain reaction (RT-PCR) method and specific primers. Multiple sequencing alignment (MSA) was performed in the CLC word bench, and a phylogenetic tree was generated by MEGA X based on the neighbor-joining method. Of all cases, 11 (55%) were males. The mean age of the patients was 33.6 years. Diabetes (70%) and blood pressure (55%) were the most prevalent comorbidities. All 20 patients were positive for SARS-CoV-2 infection in respiratory samples. Molecular analysis investigation among 20 stool samples revealed that the SARS-CoV-2 genome was found among 10 stool samples; only three samples were used for sequencing. The polymorphism and phylogenetic analysis in SARS-CoV-2 showed great similarity among all of the evaluated genes with the Wuhan reference sequence and all of the current variants of concern (VOCs). The current study represents a great similarity in polymorphism and phylogenetic analysis of the SARS-CoV-2 isolates with the Wuhan reference sequence and all of the current VOC in the particular evaluated partial sequences of S, nsp12, and nsp2.

Immmunoinformatics-based design of a multi-epitope vaccine with CTLA-4 extracellular domain to combat Helicobacter pylori

In view of the high infection rate of Helicobacter pylori, a safe and effective vaccine is urgently needed. Recent trends in vaccine design have shifted toward safe and specific epitope-based vaccines. In this study, by using different immunoinformatics approaches, a total of eight linear B cell epitopes, four HTL and three CTL epitopes of FlaA and UreB proteins of H. pylori G27 strain were screened out, we also predicted the conformational epitopes of the two proteins. Then, the dominant epitopes were sequentially linked by appropriate linkers, and the cytotoxic T lymphocyte-associated antigen 4 extracellular domain was attached to the N-terminal of the epitope sequence. Meanwhile, molecular docking, molecular dynamics simulations and principal component analysis were performed to show that the multi-epitope vaccine structure had strong interactions with B7 (B7-1, B7-2) and Toll-like receptors (TLR-2, -4). Eventually, the effectiveness of the vaccine was validated using in silico cloning. These analyses suggested that the designed vaccine could target antigen-presenting cells and had high potency against H. pylori, which could provide a reference for the future development of efficient H. pylori vaccines.

Designing a Recombinant Vaccine against Providencia rettgeri Using Immunoinformatics Approach

Antibiotic resistance (AR) is the resistance mechanism pattern in bacteria that evolves over some time, thus protecting the bacteria against antibiotics. AR is due to bacterial evolution to make itself fit to changing environmental conditions in a quest for survival of the fittest. AR has emerged due to the misuse and overuse of antimicrobial drugs, and few antibiotics are now left to deal with these superbug infections. To combat AR, vaccination is an effective method, used either therapeutically or prophylactically. In the current study, an in silico approach was applied for the design of multi-epitope-based vaccines against Providencia rettgeri, a major cause of traveler’s diarrhea. A total of six proteins: fimbrial protein, flagellar hook protein (FlgE), flagellar basal body L-ring protein (FlgH), flagellar hook-basal body complex protein (FliE), flagellar basal body P-ring formation protein (FlgA), and Gram-negative pili assembly chaperone domain proteins, were considered as vaccine targets and were utilized for B- and T-cell epitope prediction. The predicted epitopes were assessed for allergenicity, antigenicity, virulence, toxicity, and solubility. Moreover, filtered epitopes were utilized in multi-epitope vaccine construction. The predicted epitopes were joined with each other through specific GPGPG linkers and were joined with cholera toxin B subunit adjuvant via another EAAAK linker in order to enhance the efficacy of the designed vaccine. Docking studies of the designed vaccine construct were performed with MHC-I (PDB ID: 1I1Y), MHC-II (1KG0), and TLR-4 (4G8A). Findings of the docking study were validated through molecular dynamic simulations, which confirmed that the designed vaccine showed strong interactions with the immune receptors, and that the epitopes were exposed to the host immune system for proper recognition and processing. Additionally, binding free energies were estimated, which highlighted both electrostatic energy and van der Waals forces to make the complexes stable. Briefly, findings of the current study are promising and may help experimental vaccinologists to formulate a novel multi-epitope vaccine against P. rettgeri.

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

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

Data processing algorithms for the in silico SARS-CoV-2 epitope prediction and vaccine development

Based on literature analysis and own bioinformatics and virology research experience, authors propose multistep data processing algorithms, designed for the objectives of assisting the SARS-CoV-2 epitope vaccine production. Epitope vaccines are expected to provoke a weaker but safer response of the vaccinated person. Methodologies of reverse bioengineering, vaccinology and synthetic peptide manufacturing have a promising future to combat COVID-19 brutal disease. The significant mutational variability and evolution of the SARS-CoV-2, which is more typical for natural animal-borne viruses, are the hurdle for the effective and robust vaccine application and therefore require multidisciplinary research and prevention measures on the international level of cooperation. However, we can expect that other viruses with different nature and content may be labelled as SARS-CoV-2. In this case metagenomics is an important discipline for COVID-19 discovery. High quality reliable virus detection is still an unresolved question for improvement and optimization. It is of upmost importance to develop the in silico and in vitro methods for the vaccine recipient reaction prediction and monitoring as techniques of the so-called modern personalized medicine. Many questions can`t be solved applying exclusively in silico techniques and only can be discovered in vitro and in vivo, demanding significant time and money investments. Future experiments also should be directed at the discovery of optimal vaccine adjuvants, vectors and epitope ensembles, as well as the personal characteristics of citizens of a certain region. This research would require several more years of meticulous large-scale laboratory and clinical work in various centers of biomedical institutions worldwide

In Silico Modeling as a Perspective in Developing Potential Vaccine Candidates and Therapeutics for COVID-19

The potential of computational models to identify new therapeutics and repurpose existing drugs has gained significance in recent times. The current ‘COVID-19’ pandemic caused by the new SARS CoV2 virus has affected over 200 million people and caused over 4 million deaths. The enormity and the consequences of this viral infection have fueled the research community to identify drugs or vaccines through a relatively expeditious process. The availability of high-throughput datasets has cultivated new strategies for drug development and can provide the foundation towards effective therapy options. Molecular modeling methods using structure-based or computer-aided virtual screening can potentially be employed as research guides to identify novel antiviral agents. This review focuses on in-silico modeling of the potential therapeutic candidates against SARS CoVs, in addition to strategies for vaccine design. Here, we particularly focus on the recently published SARS CoV main protease (Mpro) active site, the RNA-dependent RNA polymerase (RdRp) of SARS CoV2, and the spike S-protein as potential targets for vaccine development. This review can offer future perspectives for further research and the development of COVID-19 therapies via the design of new drug candidates and multi-epitopic vaccines and through the repurposing of either approved drugs or drugs under clinical trial.

Computational Design and Analysis of a Multi-epitope Against Influenza A virus

Influenza A viruses are among the most studied viruses, however no effective prevention against influenza infection has been developed. So, designing an effective vaccine against Influenza A virus is a critical issue in the field of medical biotechnology. For this reason, to combat this disease, we have designed a novel multi-epitope vaccine candidate based on the several conserved and potential linear B-cell and T-cell binding epitopes by using the in silico approach. This vaccine consists of an ER signal conserved sequence, the PADRE conserved epitope and two conserved epitopes of Influenza matrix protein 2. T-cell binding epitopes from Matrix protein 2 were predicted by in silico tools of epitope prediction. The selected epitopes were joined by flexible linkers and physicochemical properties, toxicity, and allergenecity were investigated. The designed vaccine was antigenic, immunogenic, and non-allergenic with suitable physicochemical properties and has higher solubility. The final multi-epitope construct was modeled, confirmed by different programs and the molecular interactions with immune receptors were considered. The molecular docking assay indicated the interactions with immune-stimulatory toll-like receptor 3 (TLR3) and major histocompatibility complex class I (MHCI). The HADDOCK and H DOCK servers were used to make docking analysis, respectively. The docking analysis indicated a strong and stable binding interaction between the vaccine construct with major histocompatibility complex (MHC) class I and toll-like receptor 3. Overall, the findings suggest that the current vaccine may be a promising vaccine to prevent Influenza infection.

An immunogenetic view of COVID-19

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

Homology between SARS CoV-2 and human proteins

An extremely high contagiousness of SARS CoV-2 indicates that the virus developed the ability to deceive the innate immune system. The virus could have included in its outer protein domains some motifs that are structurally similar to those that the potential victim's immune system has learned to ignore. The similarity of the primary structures of the viral and human proteins can provoke an autoimmune process. Using an open-access protein database Uniprot, we have compared the SARS CoV-2 proteome with those of other organisms. In the SARS CoV-2 spike (S) protein molecule, we have localized more than two dozen hepta- and octamers homologous to human proteins. They are scattered along the entire length of the S protein molecule, while some of them fuse into sequences of considerable length. Except for one, all these n-mers project from the virus particle and therefore can be involved in providing mimicry and misleading the immune system. All hepta- and octamers of the envelope (E) protein, homologous to human proteins, are located in the viral transmembrane domain and form a 28-mer protein E14-41 VNSVLLFLAFVVFLLVTLAILTALRLCA. The involvement of the protein E in provoking an autoimmune response (after the destruction of the virus particle) seems to be highly likely. Some SARS CoV-2 nonstructural proteins may also be involved in this process, namely ORF3a, ORF7a, ORF7b, ORF8, and ORF9b. It is possible that ORF7b is involved in the dysfunction of olfactory receptors, and the S protein in the dysfunction of taste perception.

An overview on the seven pathogenic human coronaviruses

To date, seven human coronaviruses (HCoVs) have been detected: HCoV-NL63, HCoV-229E, HCoV-HKU1, HCoV-OC43, severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV) and SARS-CoV-2. Four of these viruses, including HCoV-NL63, -229E, -HKU1 and -OC43, usually cause mild-to-moderate respiratory diseases with a seasonal pattern. Since 2000, three new HCoVs have emerged with a significant mortality rate. Although SARS-CoV and MERS-CoV caused an epidemic in some countries, SARS-CoV-2 escalated into a pandemic. All HCoVs can cause severe complications in the elderly and immunocompromised individuals. The bat origin of HCoVs, the presence of intermediate hosts and the nature of their viral replication suggest that other new coronaviruses may emerge in the future. Despite the fact that all HCoVs share similarities in viral replication, they differ in their accessory proteins, incubation period and pathogenicity. This study aims to review these differences between the seven HCoVs.

Future developments in biosensors for field-ready SARS-CoV-2 virus diagnostics

According to the evidence, the coronavirus disease 19 (COVID-19) is caused by a zoonotic pathogen named respiratory syndrome coronavirus 2 (SARS-CoV-2). This virus can spread through personal contact, respiratory droplets, and also through airborne transmission. A rapid, low-cost, and effective biosensor platform is essential to diagnose patients with COVID-19 infection, predominantly the asymptomatic individuals, and prevent the spread of the SARS-CoV-2 via transmission routes. The objective of this review is to provide a comparative view among current diagnostic methods, focusing on recently suggested biosensors for the detection of SARS-CoV2 in clinical samples. A capable SARS-CoV-2 biosensor can be designed by the holistic insights of various biosensor studies.

Lessons Learned from Cutting-Edge Immunoinformatics on Next-Generation COVID-19 Vaccine Research

Presently, immunoinformatics and bioinformatics approaches are contributing actively to COVID-19 vaccine research. The first immunoinformatics-based vaccine construct against SARS-CoV-2 was published in February 2020. Following this, immunoinformatics and bioinformatics approaches have created a new direction in COVID-19 vaccine research. Several researchers have designed the next-generation COVID-19 vaccines using these approaches. Presently, immunoinformatics has accelerated immunology research immensely in the area of COVID-19. Hence, we have tried to depict the current scenario of immunoinformatics and bioinformatics in COVID-19 vaccine research.

Identification of HLA-A2 restricted CD8+ T cell epitopes in SARS-CoV-2 structural proteins

The outbreak of coronavirus disease 2019 (COVID‐19) has now become a pandemic, and the etiologic agent is the severe acute respiratory syndrome‐coronavirus 2 (SARS‐CoV‐2). T cell mediated immune responses play an important role in virus controlling; however, the understanding of the viral protein immunogenicity and the mechanisms of the induced responses are still limited. So, identification of specific epitopes and exploring their immunogenic properties would provide valuable information. In our study, we utilized the Immune Epitope Database and Analysis Resource and NetMHCpan to predict HLA‐A2 restricted CD8⁺ T cell epitopes in structural proteins of SARS‐CoV‐2, and screened out 23 potential epitopes. Among them, 18 peptides showed strong or moderate binding with HLA‐A2 with a T2A2 cell binding model. Next, the mixed peptides induced the increased expression of CD69 and highly expressed levels of IFN‐γ and granzyme B in CD8⁺ T cells, indicating effective activation of specific CD8⁺ T cells. In addition, the peptide‐activated CD8⁺ T cells showed significantly increased killing to the target cells. Furthermore, tetramer staining revealed that the activated CD8⁺ T cells mainly recognized seven epitopes. All together, we identified specific CD8⁺ T cell epitopes in SARS‐CoV‐2 structural proteins, which could induce the production of specific immune competent CD8⁺ T cells. Our work contributes to the understanding of specific immune responses and vaccine development for SARS‐CoV‐2.

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

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

Multi-Epitope Vaccine Design Using an Immunoinformatic Approach for SARS-CoV-2

Through 4 June 2021, COVID-19 has caused over 172.84 million cases of infection and 3.71 million deaths worldwide. Due to its rapid dissemination and high mutation rate, it is essential to develop a vaccine harboring multiple epitopes and efficacious against multiple variants to prevent the immune escape of SARS-CoV-2. An in silico approach based on the viral genome was applied to identify 19 high-immunogenic B-cell epitopes and 499 human leukocyte antigen (HLA)-restricted T-cell epitopes. Thirty multi-epitope peptide vaccines were designed by iNeo-Suite and manufactured by solid-phase synthesis. Docking analysis confirmed stable hydrogen bonds of epitopes with their corresponding HLA alleles. When four peptide candidates derived from the spike protein of SARS-CoV-2 were selected to immunize mice, a significantly larger amount of total IgG in serum, as well as an increase of CD19+ cells in the inguinal lymph nodes, were observed in the peptide-immunized mice compared to the control. The ratios of IFN-γ-secreting lymphocytes in CD4+ or CD8+ T-cells in the peptide-immunized mice were higher than those in the control mice. There were also a larger number of IFN-γ-secreting T-cells in the spleens of peptide-immunized mice. The peptide vaccines in this study successfully elicited antigen-specific humoral and cellular immune responses in mice. To further validate the safety and efficacy of this vaccine, animal studies using a primate model, as well as clinical trials in humans, are required.

The role of miRNAs in COVID-19 disease

Nowadays, the SARS Coronavirus 2 (SARS-CoV-2) infection is recognized as the primary cause of mortality in humans. SARS-CoV-2 is transmitted through human-to-human contact and is asymptomatic in most patients. In addition to approved vaccines against SARS-CoV-2 infection, miRNAs may also be promising options against this new virus. miRNAs are small and noncoding RNAs 18–25 nucleotides in length that target the mRNAs to degrade them or obstruct their translation miRNAs act as an observer in cells. This study reviewed the literature on the potential role of cellular miRNAs in the SARS-CoV-2-host interplay as a therapeutic option in COVID-19 patients.

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

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

Identification of promiscuous T cell epitopes on Mayaro virus structural proteins using immunoinformatics, molecular modeling, and QM:MM approaches

The Mayaro virus (MAYV) belongs to genus Alphavirus (family Togaviridae) and has been reported in several countries, especially in tropical regions of America. Due to its outbreaks and potential lack of medication, an effective vaccine formulation is strongly required. This study aimed to predict promiscuous T cell epitopes from structural polyproteins of MAYV using an immunoinformatics approach. For this purpose, consensus sequences were used to identify short protein sequences capable of binding to MHC class I and class II alleles. Our analysis pointed out 4 MHC-I/TCD8+ and 21 MHC-II/TCD4+ epitopes on capside (1;3), E1 (2;5), E2 (1;10), E3 (0;2), and 6 K (0;1) proteins. These predicted epitopes were characterized by high antigenicity, immunogenicity, conservancy, non-allergenic, non-toxic, and good population coverage rate values for North and South American geographical areas. Afterwards, we used the crystal structure of human toll-like receptor 3 (TLR3) ectodomain as a template to predict, through docking essays, the placement of a vaccine prototype at the TLR3 receptor binding site. Finally, classical and quantum mechanics/molecular mechanics (QM:MM) computations were employed to improve the quality of docking calculations, with the QM part of the simulations being accomplished by using the density functional theory (DFT) formalism. These results provide important insights into the advancement of diagnostic platforms, the development of vaccines, and immunotherapeutic interventions.