Designing a novel multiepitope peptide vaccine against melanoma using immunoinformatics approach

Revolutionizing Chikungunya Vaccines: mRNA Breakthroughs With Molecular and Immune Simulations

With the ability to cause massive epidemics that have consequences on millions of individuals globally, the Chikungunya virus (CHIKV) emerges as a severe menace. Developing an effective vaccine is urgent as no effective therapeutics are available for such viral infections. Therefore, we designed a novel mRNA vaccine against CHIKV with a combination of highly antigenic and potential MHC-I, MHC-II, and B-cell epitopes from the structural polyprotein. The vaccine demonstrated well-characterized physicochemical properties, indicating its solubility and potential functional stability within the body (GRAVY score of -0.639). Structural analyses of the vaccine revealed a well-stabilized secondary and tertiary structure (Ramachandran score of 82.8% and a Z-score of -4.17). Docking studies of the vaccine with TLR-2 (-1027.7 KJ/mol) and TLR-4 (-1212.4 KJ/mol) exhibited significant affinity with detailed hydrogen bond interactions. Molecular dynamics simulations highlighted distinct conformational dynamics among the vaccine, "vaccine-TLR-2" and "vaccine-TLR-4" complexes. The vaccine's ability to elicit both innate and adaptive immune responses, including the presence of memory B-cells and T-cells, persistent B-cell immunity for a year, and the activation of TH cells leading to the release of IFN-γ and IL-2, has significant implications for its potential effectiveness. The CHIKV vaccine developed in this study shows promise as a potential candidate for future vaccine production against CHIKV, suggesting its suitability for further clinical advancement, including in vitro and in vivo experiments.

Immunoinformatic approach to design an efficient multi-epitope peptide vaccine against melanoma

Melanoma is known to be the most hazardous and life-threatening type of skin cancer. Although numerous treatments have been authorized in recent years, they often result in severe side effects and may not fully cure the disease. To combat this issue, immunotherapy has emerged as a promising approach for the prevention and treatment of melanoma. Specifically, the use of epitope melanoma vaccine, a subset of immunotherapy, has recently gained attention. The aim of this study was to create a multi-epitope melanoma vaccine using immunoinformatic methods. Two well-known antigens, NYESO-1 and MAGE-C2, were selected due to their strong immunogenicity and high expression in melanoma. To enhance the immunogenicity of the peptide vaccine, Brucella cell-surface protein 31 (BCSP31), the G5 domain of resuscitation-promoting factor B (RpfB) adjuvants, and the helper epitope of pan HLADR-binding epitope (PADRE) were incorporated to vaccine construct. These different segments were connected with suitable linkers and the resulting vaccine structure was evaluated for its physicochemical, structural, and immunological properties using computational tools. The designed vaccine was found to have satisfactory allergenicity, antigenicity, and physicochemical parameters. Additionally, a high-quality tertiary structure of the vaccine was achieved through modeling, refinement, and validation. Docking and molecular dynamics studies showed that the vaccine had a stable and appropriate interaction with the cognate TLR2 and TLR4 receptors during the simulation period. Finally, in silico immune simulation analysis revealed a significant increase in the levels of helper and cytotoxic T cells, as well as the cytokines interferon-gamma and interleukin-2, after repeated exposure to the melanoma vaccine. These results suggest that the designed vaccine has the potential to be an effective therapeutic option for melanoma. However, additional in vitro and in vivo validations are crucial to assess real-world efficacy and safety.

Leveraging mRNA technology for antigen based immuno-oncology therapies

The application of messenger RNA (mRNA) technology in antigen-based immuno-oncology therapies represents a significant advancement in cancer treatment. Cancer vaccines are an effective combinatorial partner to sensitize the host immune system to the tumor and boost the efficacy of immune therapies. Selecting suitable tumor antigens is the key step to devising effective vaccinations and amplifying the immune response. Tumor neoantigens are de novo epitopes derived from somatic mutations, avoiding T-cell central tolerance of self-epitopes and inducing immune responses to tumors. The identification and prioritization of patient-specific tumor neoantigens are based on advanced computational algorithms taking advantage of the profiling with next-generation sequencing considering factors involved in human leukocyte antigen (HLA)-peptide-T-cell receptor (TCR) complex formation, including peptide presentation, HLA-peptide affinity, and TCR recognition. This review discusses the development and clinical application of mRNA vaccines in oncology, with a particular focus on recent clinical trials and the computational workflows and methodologies for identifying both shared and individual antigens. While this review centers on therapeutic mRNA vaccines targeting existing tumors, it does not cover preventative vaccines. Preclinical experimental validations are crucial in cancer vaccine development, but we emphasize the computational approaches that facilitate neoantigen selection and design, highlighting their role in advancing mRNA vaccine development. The versatility and rapid development potential of mRNA make it an ideal platform for personalized neoantigen immunotherapy. We explore various strategies for antigen target identification, including tumor-associated and tumor-specific antigens and the computational tools used to predict epitopes capable of eliciting strong immune responses. We address key design considerations for enhancing the immunogenicity and stability of mRNA vaccines, as well as emerging trends and challenges in the field. This comprehensive overview highlights the therapeutic potential of mRNA-based cancer vaccines and underscores ongoing research efforts aimed at optimizing these therapies for improved clinical outcomes.

Developing a chimeric multiepitope vaccine against Nipah virus (NiV) through immunoinformatics, molecular docking and dynamic simulation approaches

Nipah virus (NiV) is a highly lethal zoonotic pathogen that poses a significant threat to human and animal health. Unfortunately, no effective treatments have been developed for this deadly zoonotic disease. Therefore, we designed a chimeric multiepitope vaccine targeting the Nipah virus (NiV) glycoprotein and fusion protein through immunoinformatic approaches. Therefore, the vaccine was developed by combining promising and potential antigenic MHC-I, MHC-II, and B-cell epitopes obtained from the selected proteins. When combined, the MHC-I and MHC-II epitopes offered 100 % global population coverage. The physicochemical characterization also exhibited favorable properties, including solubility and potential functional stability of the vaccine within the body (GRAVY score of -0.308). Structural analyses unveiled a well-stabilized secondary and tertiary structure with a Ramachandran score of 84.4 % and a Z score of -5.02. Findings from docking experiments with TLR-2 (-1089.3 kJ/mol) and TLR-4 (-1016.7 kJ/mol) showed a strong affinity of the vaccine towards the receptor. Molecular dynamics simulations revealed unique conformational dynamics among the "vaccine-apo," "vaccine-TLR-2," and "vaccine-TLR-4″ complexes. Consequently, the complexes exhibited significant compactness, flexibility, and exposure to solvents. The results of the codon optimization were remarkable, as the vaccine showed a significant amount of expression in the E. coli vector (GC content of 45.36 % and a CAI score of 1.0). The results of immune simulations, however, showed evidence of both adaptive and innate immune responses induced by the vaccine. Therefore, we highly recommend further research on this chimeric multiepitope vaccine to establish its efficacy and safety against the Nipah virus (NiV).

Multi-Epitopic Peptide Vaccine Against Newcastle Disease Virus: Molecular Dynamics Simulation and Experimental Validation

BACKGROUND

Newcastle disease virus (NDV) is a highly contagious and economically devastating pathogen affecting poultry worldwide, leading to significant losses in the poultry industry. Despite existing vaccines, outbreaks continue to occur, highlighting the need for more effective vaccination strategies. Developing a multi-epitopic peptide vaccine offers a promising approach to enhance protection against NDV.

OBJECTIVES

Here, we aimed to design and evaluate a multi-epitopic vaccine against NDV using molecular dynamics (MD) simulation.

METHODOLOGY

We retrieved NDV sequences for the fusion (F) protein and hemagglutinin-neuraminidase (HN) protein. Subsequently, B-cell and T-cell epitopes were predicted. The top potential epitopes were utilized to design the vaccine construct, which was subsequently docked against chicken TLR4 and MHC1 receptors to assess the immunological response. The resulting docked complex underwent a 1 microsecond (1000 ns) MD simulation. For experimental evaluation, the vaccine's efficacy was assessed in mice and chickens using a controlled study design, where animals were randomly divided into groups receiving either a local ND vaccine or the peptide vaccine or a control treatment.

RESULTS

The 40 amino acid peptide vaccine demonstrated strong binding affinity and stability within the TLR4 and MHC1 receptor-peptide complexes. The root mean square deviation of peptide vaccine and TLR4 receptor showed rapid stabilization after an initial repositioning. The root mean square fluctuation revealed relatively low fluctuations (below 3 Å) for the TLR4 receptor, while the peptide exhibited higher fluctuations. The overall binding energy of the peptide vaccine with TLR4 and MHC1 receptors amounted to -15.7 kcal·mol-1 and -36.8 kcal·mol-1, respectively. For experimental evaluations in mice and chicken, the peptide vaccine was synthesized using services of GeneScript Biotech® (Singapore) PTE Limited. Experimental evaluations showed a significant immune response in both mice and chickens, with the vaccine eliciting robust antibody production, as evidenced by increasing HI titers over time. Statistical analysis was performed using an independent t-test with Type-II error to compare the groups, calculating the p-values to determine the significance of the immune response between different groups.

CONCLUSIONS

Multi-epitopic peptide vaccine has demonstrated a good immunological response in natural hosts.

Designing novel peptides for detecting the Omicron variant, specifying SARS-CoV-2, and simultaneously screening coronavirus infections

In this study in silico a candidate diagnostic peptide-based tool was designed in four stages including diagnosis of coronavirus diseases, simultaneously identifying of COVID-19 and SARS from other members of this family, specific identification of SARS-CoV2, and diagnosis of COVID-19 Omicron. Designed candidate peptides consist of four immunodominant peptides from the proteins of the SARS-CoV-2 spike (S) and membrane (M). The tertiary structure of each peptide was predicted. The stimulation ability of the humoral immunity for each peptide was evaluated. Finally, in silico cloning was performed to develop an expression strategy for each peptide. These four peptides have suitable immunogenicity, appropriate construct, and the ability to be expressed in E.coli. These results must be experimentally validated in vitro and in vivo to ensure the immunogenicity of the kit.Communicated by Ramaswamy H. Sarma.

Current knowledge about immunotherapy resistance for melanoma and potential predictive and prognostic biomarkers

Melanoma still reaches thousands of new diagnoses per year, and its aggressiveness makes recovery challenging, especially for those with stage III/IV unresectable melanoma. Immunotherapy, emerging as a beacon of hope, stands at the forefront of treatments for advanced melanoma. This review delves into the various immunotherapeutic strategies, prominently featuring cytokine immunotherapy, adoptive cell therapy, immune checkpoint inhibitors, and vaccinations. Among these, immune checkpoint inhibitors, notably anti-programmed cell death-1 (PD-1) and anti-cytotoxic T lymphocyte antigen-4 (CTLA-4) antibodies, emerge as the leading strategy. However, a significant subset of melanoma patients remains unresponsive to these inhibitors, underscoring the need for potent biomarkers. Efficient biomarkers have the potential to revolutionize the therapeutic landscape by facilitating the design of personalized treatments for patients with melanoma. This comprehensive review highlights the latest advancements in melanoma immunotherapy and potential biomarkers at the epicenter of recent research endeavors.

Novel multi-epitope vaccine against bovine brucellosis: approach from immunoinformatics to expression

Brucellosis is a zoonotic caused by the Brucella which is a well-known infectious disease agent in domestic animals and if transmitted, it can cause infection in humans. Because brucellosis is contagious, its control depends on the eradication of the animal disease in farms. There are two vaccines based on the killed and/or weakened bacteria against B. melitensis and B. abortus, but no recombinant vaccine is available for preventing the disease. The present study was designed to develop a multi-epitope vaccine against of B. melitensis and B. abortus using virB10, Omp31 and Omp16 antigens by the prediction of T lymphocytes, T cell cytotoxicity and IFN-γ epitopes. 50S L7/L12 Ribosomal protein from Mycobacterium tuberculosis was used as a bovine TLR4 and TLR9 agonist. GPGPG, AAY and KK linkers were used as a linker. Brucella construct was well-integrated in the pET-32a Shuttle vector with BamHI and HindIII restriction enzymes. The final construct contained 769 amino acids, that it was soluble protein of about ∼82 kDa after expression in the Escherichia coli SHuffle host. Modeled protein analysis based on the tertiary structure validation, molecular docking studies, molecular dynamics simulations results like RMSD, Gyration and RMSF as well as MM/PBSA analysis showed that this protein has a stable construct and is capable being in interaction with bovine TLR4 and TLR9. Analysis of the data obtained suggests that the proposed vaccine can induce the immune response by stimulating T- and B-cells, and may be used for prevention and remedial purposes, against B. melitensis and B. abortus.Communicated by Ramaswamy H. Sarma.

Towards the First Multiepitope Vaccine Candidate against Neospora caninum in Mouse Model: Immunoinformatic Standpoint

Neospora caninum is an economically significant parasite among livestock, particularly in dairy cattle herds, causing storm abortions. Vaccination seems necessary to limit the infection and its harsh consequences. This is the first steps towards developing a multiepitope vaccine candidate against N. caninum using in silico approaches. High-ranked mouse MHC-binding and shared linear B-cell epitopes from six proteins (SRS2, MIC3, MIC6, GRA1, IMP-1, and profilin) as well as IFN-γ-inducing epitopes (from SAG1) were predicted, screened, and connected together through appropriate linkers. Finally, RS-09 protein (TLR4 agonist) and histidine tag were added to N- and C-terminal of the vaccine sequence, yielding 486 residues in length. Physicochemical properties showed a stable (instability index: 27.23), highly soluble, antigenic (VaxiJen score: 0.9554), and nonallergenic candidate. Secondary structure of the multiepitope protein included 58.85% random coil, 20.99% extended strand, and 20.16% alpha helix. Also, the tertiary structure was predicted, and further analyses validated a stable interaction between the vaccine model and mouse TLR4 (binding score: -1261.6). Virtual simulation of immune profile demonstrated potently stimulated humoral (IgG+IgM) and cell-mediated (IFN-γ) responses upon multiepitope vaccine injection. Altogether, a potentially immunogenic vaccine candidate was developed using several N. caninum proteins, with the capability to elicit IFN-γ upsurge and other components of cellular immunity, and can be used in prophylactic purposes against neosporosis.

Peptide-Based Vaccines for Tuberculosis

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis. As a result of the coronavirus disease 2019 (COVID-19) pandemic, the global TB mortality rate in 2020 is rising, making TB prevention and control more challenging. Vaccination has been considered the best approach to reduce the TB burden. Unfortunately, BCG, the only TB vaccine currently approved for use, offers some protection against childhood TB but is less effective in adults. Therefore, it is urgent to develop new TB vaccines that are more effective than BCG. Accumulating data indicated that peptides or epitopes play essential roles in bridging innate and adaptive immunity and triggering adaptive immunity. Furthermore, innovations in bioinformatics, immunoinformatics, synthetic technologies, new materials, and transgenic animal models have put wings on the research of peptide-based vaccines for TB. Hence, this review seeks to give an overview of current tools that can be used to design a peptide-based vaccine, the research status of peptide-based vaccines for TB, protein-based bacterial vaccine delivery systems, and animal models for the peptide-based vaccines. These explorations will provide approaches and strategies for developing safer and more effective peptide-based vaccines and contribute to achieving the WHO's End TB Strategy.

Screening of potential antigens from whole proteome and development of multi-epitope vaccine against Rhizopus delemar using immunoinformatics approaches

Mucormycosis is a deadly fungal disease mainly caused by Rhizopus oryzae (strain 99-880), also known as Rhizopus delemar. Previously, mucormycosis occurs in immunocompromised patients of diabetes mellitus, cancer, organ transplant, etc. But there was a drastic increase in mucormycosis cases in the ongoing COVID-19 pandemic. Despite several available therapies and antifungal treatments, the mortality rate of mucormycosis is about more than 50%. Currently, there is no vaccine available in the market for mucormycosis that urgently needs to develop a potential vaccine against mucormycosis with high efficacy. In the present study, we have screened 4 genome-derived predicted antigens (GDPA) through sequential filtration of the whole proteome of R. delemar using different benchmarked bioinformatics tools. These 4 GDPA along with 4 randomly selected experimentally reported antigens (ERA) were sourced for prediction of B- and T- cell epitopes and utilized in designing of two potential multi-epitope vaccine candidates which can induce both innate and adaptive immunity against R. delemar. Besides these, comparative immune simulation studies and in silico cloning were performed using L. lactis as an expression system for their possible uses as oral vaccines. This is the first multi-epitope vaccine designed against R. delemar through systematic pipelined reverse vaccinology and immunoinformatic approaches. Although the wet-lab based experimental validation of designed vaccines is required before testing in the preclinical model, the current study will significantly help in reducing the cost of experimentation as well as improving the efficacy of vaccine therapy against mucormycosis and other pathogenic diseases.Communicated by Ramaswamy H. Sarma.

Development of a chimeric vaccine candidate based on Toxoplasma gondii major surface antigen 1 and apicoplast proteins using comprehensive immunoinformatics approaches

This study was aimed at designing and evaluation of a multimeric vaccine construct against Toxoplasma gondii via utilization of SAG1 along with apicoplast ribosomal proteins (S2, S5 and L11). Top-ranked MHC-I and MHC-II binding as well as shared, immunodominant linear B-cell epitopes were predicted and joined together via appropriate linkers. Also, TLR-4 agonist (RS-09 synthetic protein) and His-tag were added to the N- and C-terminal of the vaccine sequence. The finally-engineered chimeric vaccine had a length of 291 amino acids with a molecular weight of 31.46 kDa. Physico-chemical features showed a soluble, highly-antigenic and non-allergenic candidate. Secondary and tertiary structures were predicted, and subsequent analyses confirmed the construct stability that was capable to properly interact with human TLR-4. Immunoinformatics-based simulation displayed potent stimulation of T- and B-cell mediated immune responses upon vaccination with the proposed multi-epitope candidate. In conclusion, obtained information demonstrated a highly antigenic vaccine candidate, which could develop high levels of IFN-γ and other components of cellular immune profile, and can be directed for toxoplasmosis prophylactic purposes.