The Advantage of Using Immunoinformatic Tools on Vaccine Design and Development for Coronavirus

In silico design of Ebola virus Glycoprotein antigenic peptides as vaccine candidates

Ebola virus (EBOV) is a filovirus that causes severe hemorrhagic fever and has a fatality rate between 50 and 90%. The vaccines were developed against the Ebola Zaire species; therefore, it is necessary to develop vaccines against other species to control future outbreaks. The objective of this work was to obtain vaccine candidate peptides against different EBOV species through the use of bioinformatics programs and servers that allow glycoprotein (GP) to be analyzed. GP sequences of various EBOV species that did not present gaps or unspecified amino acids or that were repeated (same year, region and laboratory) were downloaded from the NCBI database. A consensus sequence was generated and used to determine vaccine candidate peptides, which were evaluated, through a combination of servers and molecular dynamics, for their ability to interact with B and T lymphocytes, toxicity, allergenicity, solvent exposure, glycosylation, antigenicity, and presence in mature GP. Five vaccine candidate peptides were identified, of which PEP4 had the best characteristics evaluated in this study. PEP4 may be a potential candidate for the development of an EBOV vaccine.

Bioinformatics analysis of the in silico engineered protein vaccine with and without Escherichia coli heat labile enterotoxin adjuvant on the model of Klebsiella pneumoniae

Klebsiella pneumoniae (K. pneumoniae) has been identified as a major cause of nosocomial infections with multidrug-resistant phenotypes. Vaccination is one of the most effective methods to prevent infectious diseases. We aim to design a vaccine candidate based on the epitope-rich domains of the OmpA, OMPK17, and fimb proteins of K. pneumoniae that could protect against this infection. A vaccine structure was constructed by selecting five epitope-rich domains from three proteins. We decided to add the heat-labile toxin (LT) of Escherichia coli as an adjuvant to the designed protein structure. The evaluation of the vaccine candidates' interaction with the immune system's receptors showed an appropriate interaction of the specially adjuvated protein with TLR2 and TLR4. The stability of the interactions was also studied by molecular dynamics (MD) for to 100 ns. All parameters showed that the structure of the candidate proteins alone and in complex with TLR2 and TLR4 are stable, especially the adjuvanted protein. Immune response simulations showed that both candidates induce acceptable protective immune responses. Overall, the LT-adjuvanted design protein may have the potential to induce more favorable protective immune responses. However, further in vitro and in vivo studies are required to obtain more definitive results.

Molecular and Immunological Properties of a Chimeric Glycosyl Hydrolase 18 Based on Immunoinformatics Approaches: A Design of a New Anti-Leishmania Vaccine

Leishmaniasis is a chronic inflammatory zoonotic illness caused by protozoan flagellates belonging to the Leishmania genus. Current data suggest that over 1 billion people worldwide are susceptible to infection, primarily in tropical and subtropical countries, where up to 2 million new cases are reported annually. Therefore, the development of a vaccine is crucial to combating this disease. This study employed immunoinformatics approaches to design a multiepitope anti-Leishmania vaccine, GH18-cpLeish, based on a cluster of six glycosyl hydrolases 18. We identified six helper T lymphocyte (HTL) epitopes and twenty-six cytotoxic T lymphocyte (CTL) epitopes with IC50 values <50 nM, indicating high affinity. Additionally, we also identified 20 continuous and twenty-six discontinuous B-cell epitopes. Analysis for allergenicity and toxicity showed no potential to induce these phenomena. All data obtained from in silico tools suggest that physicochemical and biological studies indicate that the GH18-cpLeish chimeric protein is a promising candidate for an anti-Leishmania vaccine. Docking analysis showed that the Pep1-cpLeish::TLR1, Pep1-cpLeish::TLR2, Pep1-cpLeish::/TLR3, and Pep1-cpLeish::/TLR4 complexes maintained a stable form. The best interaction cluster score was observed in the complex Pep1-cpLeish::TLR2 (center = -622.6 and lowest energy = -841.7 kcal.mol-1) followed by the complexes Pep1-cpLeish::TLR4 (center = -590.3 and lowest energy = -590.3 kcal.mol-1), Pep1-cpLeish::TLR3 (center = -589.1 and lowest energy = -657.0 kcal.mol-1), and Pep1-cpLeish::TLR1 (center = -504.1 and lowest energy = -602.9 kcal.mol-1), respectively. This study suggests that GH18-cpLeish may be suitable for constructing second-generation anti-Leishmania and even third-generation vaccines, given that its gene sequence is optimized for this purpose.

Immunoinformatic design of a multivalent vaccine against Brucella abortus and its evaluation in a murine model using a DNA prime-protein boost strategy

Introduction

The development of effective vaccines against Brucella abortus is critical due to its significant impact on human and animal health. The objective of this study was to design and evaluate in silico and in vivo a multivalent vaccine based on the immunogenic potential of three selected open reading frames (ORFs) of Brucella.

Methods

The designed construct, named S22, was analyzed in silico to evaluate its physicochemical properties, antigenicity, allergenicity and toxicity. This construct was modeled and subjected to molecular dynamics analysis. Additionally, the antigenicity and protection induced by this construct was evaluated through In vivo assays immunizing BALB/c mice with protein (S22), DNA (pVS22) and combining both vaccine formats using a prime boost immunization strategy.

Results

All bioinformatics analyses showed safe and high quality structural features, revealing favorable interactions between S22 and the TLR4/MD2 complex. Moreover, results from in vivo assays indicated that the S22 protein induced robust levels of IgG1 and IgG2a, suggesting a balanced Th1 and Th2 immune response. The DNA construct (pVS22) elicited primarily a Th1 response, whereas the use of a prime boost strategy, which combines both formats resulted in a balanced immune response with significant induction of lymphoproliferation and elevated.

Discussion

Although our assays did not demonstrate the induction of a substantial protective response against B. abortus, this construct was capable of inducing immunogenicity. This study highlights the utility of in silico design for predicting and optimizing candidate vaccines and underscores the potential of using strategies such as prime boost, which incorporate antigens of different biological nature to modulate the immune response, while balancing parameters such as stability of the antigens and the cost of production.

Design of multivalent-epitope vaccine models directed toward the world's population against HIV-Gag polyprotein: Reverse vaccinology and immunoinformatics

Significant progress has been made in HIV-1 research; however, researchers have not yet achieved the objective of eradicating HIV-1 infection. Accordingly, in this study, eucaryotic and procaryotic in silico vaccines were developed for HIV-Gag polyproteins from 100 major HIV subtypes and CRFs using immunoinformatic techniques to simulate immune responses in mice and humans. The epitopes located in the conserved domains of the Gag polyprotein were evaluated for allergenicity, antigenicity, immunogenicity, toxicity, homology, topology, and IFN-γ induction. Adjuvants, linkers, CTLs, HTLs, and BCL epitopes were incorporated into the vaccine models. Strong binding affinities were detected between HLA/MHC alleles, TLR-2, TLR-3, TLR-4, TLR-7, and TLR-9, and vaccine models. Immunological simulation showed that innate and adaptive immune cells elicited active and consistent responses. The human vaccine model was matched with approximately 93.91% of the human population. The strong binding of the vaccine to MHC/HLA and TLR molecules was confirmed through molecular dynamic stimulation. Codon optimization ensured the successful translation of the designed constructs into human cells and E. coli hosts. We believe that the HIV-1 Gag vaccine formulated in our research can reduce the challenges faced in developing an HIV-1 vaccine. Nevertheless, experimental verification is necessary to confirm the effectiveness of these vaccines in these models.

Design of multi-epitope chimeric vaccine against Monkeypox virus and SARS-CoV-2: A vaccinomics perspective

The current era we experience is full with pandemic infectious agents that no longer threatens the major local source but the whole globe. Almost the most emerging infectious agents are severe acute respiratory syndrome coronavirus-2 (SARS CoV-2), followed by monkeypox virus (MPXV). Since no approved antiviral drugs nor licensed active vaccines are yet available, we aimed to utilize immunoinformatics approach to design chimeric vaccine against the two mentioned viruses. This is the first study to deal with design divalent vaccine against SARS-CoV-2 and MPXV. ORF8, E and M proteins from Omicron SARS-CoV-2 and gp182 from MPXV were used as the protein precursor from which multi-epitopes (inducing B-cell, helper T cells, cytotoxic T cells and interferon-ɣ) chimeric vaccine was contrived. The structure of the vaccine construct was predicted, validated, and docked to toll-like receptor-2 (TLR-2). Moreover, its sequence was also used to examine the immune simulation profile and was then inserted into the pET-28a plasmid for in silico cloning. The vaccine construct was probable antigen (0.543) and safe (non-allergen) with strong binding energy to TLR-2 (-1169.8 kcal/mol) and found to have significant immune simulation profile. In conclusion, the designed chimeric vaccine was potent and safe against SARS-CoV-2 and MPXV, which deserves further consideration.

Epitope mapping and a candidate vaccine design from canine distemper virus

Background

Canine distemper (CD) is a worldwide spread disease that has been described in 12 families of mammals, especially in the Carnivora order, being better studied in domestic canines where vaccination represents the best means of control. CD is controlled by vaccination, but many cases of the disease still occur in vaccinated animals.

Aim

The aim of this work was to study antigen-specific epitopes that can subsidize the development of a new vaccine approach.

Methods

Mapping of T cell reactive epitopes for CD virus (CDV) was carried out through enzyme-linked immunospot assays using 119 overlapped synthetic peptides from the viral hemagglutinin protein, grouped in 22 pools forming a matrix to test the immune response of 32 animals.

Results

Evaluations using the criteria established to identify reactive pools, demonstrated that 26 animals presented at least one reactive pool, that one pool was not reactive to any animal, and six pools were the most frequent among the reactive peptides. The crisscrossing of the most reactive pools in the matrix revealed nine peptides considered potential candidate epitopes for T cell stimulation against the CDV and those were used to design an in-silico protein, containing also predicted epitopes for B cell stimulation, and further analyzed using immune epitope databases to ensure protein quality and stability.

Conclusion

The final in silico optimized protein presents characteristics that qualify it to be used to develop a new prototype epitope-based anti-CDV vaccine.

A comprehensive approach to developing a multi-epitope vaccine against Mycobacterium tuberculosis: from in silico design to in vitro immunization evaluation

Introduction

The Bacillus Calmette-Guérin (BCG) vaccine, currently used against tuberculosis (TB), exhibits inconsistent efficacy, highlighting the need for more potent TB vaccines.

Materials and methods

In this study, we employed reverse vaccinology techniques to develop a promising multi-epitope vaccine (MEV) candidate, called PP13138R, for TB prevention. PP13138R comprises 34 epitopes, including B-cell, cytotoxic T lymphocyte, and helper T lymphocyte epitopes. Using bioinformatics and immunoinformatics tools, we assessed the physicochemical properties, structural features, and immunological characteristics of PP13138R.

Results

The vaccine candidate demonstrated excellent antigenicity, immunogenicity, and solubility without any signs of toxicity or sensitization. In silico analyses revealed that PP13138R interacts strongly with Toll-like receptor 2 and 4, stimulating innate and adaptive immune cells to produce abundant antigen-specific antibodies and cytokines. In vitro experiments further supported the efficacy of PP13138R by significantly increasing the population of IFN-γ+ T lymphocytes and the production of IFN-γ, TNF-α, IL-6, and IL-10 cytokines in active tuberculosis patients, latent tuberculosis infection individuals, and healthy controls, revealing the immunological characteristics and compare the immune responses elicited by the PP13138R vaccine across different stages of Mycobacterium tuberculosis infection.

Conclusion

These findings highlight the potential of PP13138R as a promising MEV candidate, characterized by favorable antigenicity, immunogenicity, and solubility, without any toxicity or sensitization.

Permafrost viremia and immune tweening

The immune system, an exquisitely regulated physiological system, utilizes a wide spectrum of soluble factors and multiple cell populations and subpopulations at diverse states of maturation to monitor and protect the organism against foreign organisms. Immune surveillance is ensured by distinguishing self-antigens from self-associated with non-self (e.g., viral) peptides presented by major histocompatibility complexes (MHC). Pathology is often identified as unregulated inflammatory responses (e.g., cytokine storm), or recognizing self as a non-self entity (i.e., auto-immunity). Artificial intelligence (AI), and in particular specific machine learning (ML) paradigms (e.g., Deep Learning [DL]) proffer powerful algorithms to better understand and more accurately predict immune responses, immune regulation and homeostasis, and immune reactivity to challenges (i.e., immune allostasis) by their intrinsic ability to interpret immune parameters, pathways and events by analyzing large amounts of complex data and drawing predictive inferences (i.e., immune tweening). We propose here that DL models play an increasingly significant role in better defining and characterizing immunological surveillance to ancient and novel virus species released by thawing permafrost.

Nanotechnology in the COVID-19 era: Carbon-based nanomaterials as a promising solution

The Coronavirus Disease 2019 (COVID-19) pandemic has led to collaboration between nanotechnology scientists, industry stakeholders, and clinicians to develop solutions for diagnostics, prevention, and treatment of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infections. Nanomaterials, including carbon-based materials (CBM) such as graphene and carbon nanotubes, have been studied for their potential in viral research. CBM unique effects on microorganisms, immune interaction, and sensitivity in diagnostics have made them a promising subject of SARS-CoV-2 research. This review discusses the interaction of CBM with SARS-CoV-2 and their applicability, including CBM physical and chemical properties, the known interactions between CBM and viral components, and the proposed prevention, treatment, and diagnostics uses.