TN strain proteome mediated therapeutic target mapping and multi-epitopic peptide-based vaccine development for Mycobacterium leprae

Rational Design of a Multi-epitope Vaccine Using Neoantigen Against Colorectal Cancer Through Structural Immunoinformatics and ML-Enabled Simulation Approach

Colorectal cancer poses a substantial global health burden. Regarding WHO, the global burden of colorectal cancer will be about 3.2 million new cases by the year 2040. Simultaneously, it indicated that this cancer will cause 6 million deaths per year. Despite advancements in chemotherapy and monoclonal antibody therapy, the disease remains a significant challenge due to the resistance of cancer stem cells. This study endeavors to design a multi-epitopic peptide (9-mer epitopes) neoantigen-based vaccine targeting the TLR4/MD2 complex as a potential vaccine candidate. These tumor-specific neoantigens (TSA) are considered novel antigens that can be used for vaccine development against cancer. To develop the neoantigen vaccine candidate, we used the SPENCER database, and 140 lncRNA-derived epitopes were retrieved. From 140 epitopes, we selected seven neoantigens with high antigenic properties for the vaccine construct. A novel vaccine containing epitopes, linkers (EAAAK and CPCPG), and adjuvants (ribosomal [50S] protein L7L12) was formulated utilizing immunoinformatics tools. The vaccine's biophysical properties were evaluated, revealing its antigenicity (0.6469), stability (instability index: 37.05), and potential for immune system interaction. In-depth structural analyses, molecular docking studies, and ML-enabled immune simulation profiling underscored the vaccine's structural integrity, binding affinity with TLR4, and ability to elicit robust immune responses against colorectal cancer antigens. These findings suggest that the multi-epitopic vaccine holds promise as a next-generation approach to combat colorectal cancer. Our in silico studies exhibit potentiality of the vaccine candidate; however, further in vivo and in vitro investigations are crucial to validate immunogenicity, safety, and efficacy before clinical implementation. Our study developed a first-time lncRNA-derived neoantigen-based cancer vaccine.

A Stable mRNA-Based Novel Multi-Epitope Vaccine Designs Against Infectious Heartland Virus by Integrated Immunoinformatics and Reverse Vaccinology Approaches

The Heartland virus (HRTV) is a tick-borne human pathogenic phlebovirus that primarily causes leukopenia and thrombocytopenia. It is transmitted by Amblyomma americanum type of tick, that is, notable for their aggressive biting behavior, affinity for human hosts, and high prevalence. Developing vaccines or immunizations against HRTV is gaining importance as a public-health preventive strategy. The current study was planned to prioritize a multi-epitope stable mRNA vaccine model against HRTV from lead B-cell and T-cell epitopes (with IC50 < 100 nM) of HRTV proteome following advanced immunoinformatics approaches. Model constructs were designed by linking the most potent, nonallergenic epitopes along with incorporation of human ribosomal protein adjuvant for immune response enhancement. The immunogenic potential of the coding vaccine molecule was examined via molecular docking against toll-like receptors immune receptors followed by normal mode analysis and molecular dynamics simulations-based energy minimization, molecular stability, and flexibility assessments. A robust, stable circular mRNA precursor of multi-epitopes vaccine model was designed by incorporating the Kozak consensus sequence, a start codon, and essential elements such as MHC class I trafficking domain (MITD), tPA, Goblin 5' and 3' Untranslated Region (UTRs), and a poly (A) tail. This strategic amalgamation ensures elevated immunogenicity and predicts a promising circular mRNA vaccine model against HRTV. The immune simulation predicted that the designed model vaccine is capable to elicit cell-mediated and humoral immune responses. The predicted circular mRNA vaccine precursor model is promising against HRTV to examine experimentally for its immunogenicity and safety features.

A review on the development of bacterial multi-epitope recombinant protein vaccines via reverse vaccinology

Bacterial vaccines play a crucial role in combating bacterial infectious diseases. Apart from the prevention of disease, bacterial vaccines also help to reduce the mortality rates in infected populations. Advancements in vaccine development technologies have addressed the constraints of traditional vaccine design, providing novel approaches for the development of next-generation vaccines. Advancements in reverse vaccinology, bioinformatics, and comparative proteomics have opened horizons in vaccine development. Specifically, the use of protein structural data in crafting multi-epitope vaccines (MEVs) to target pathogens has become an important research focus in vaccinology. In this review, we focused on describing the methodologies and tools for epitope vaccine development, along with recent progress in this field. Moreover, this article also discusses the challenges in epitope vaccine development, providing insights for the future development of bacterial multi-epitope genetically engineered vaccines.

Mesothelin- and nucleolin-specific T cells from combined short peptides effectively kill triple-negative breast cancer cells

BACKGROUND

Triple-negative breast cancer (TNBC), known for its aggressiveness and limited treatment options, presents a significant challenge. Adoptive cell transfer, involving the ex vivo generation of antigen-specific T cells from peripheral blood mononuclear cells (PBMCs), emerges as a promising approach. The overexpression of mesothelin (MSLN) and nucleolin (NCL) in TNBC samples underscores their potential as targets for T cell therapy. This study explored the efficacy of multi-peptide pulsing of PBMCs to generate MSLN/NCL-specific T cells targeting MSLN+/NCL+ TNBC cells.

METHODS

TNBC patient samples were confirmed for both MSLN and NCL expression via immunohistochemistry. Synthesized MSLN and NCL peptides were combined and administered to activate PBMCs from healthy donors. The cancer-killing ability of the resultant T cells was assessed using crystal violet staining, and their subtypes and cytotoxic cytokines were characterized through flow cytometry and cytokine bead array.

RESULTS

Findings showed that 85.3% (127/149) of TNBC cases were positive for either MSLN or NCL, or both; with single positivity rates for MSLN and NCL of 14.1% and 28.9%, respectively. MSLN and NCL peptides, with high binding affinity for HLA-A*02, were combined and introduced to activated PBMCs from healthy donors. The co-pulsed PBMCs significantly induced TEM and TEMRA CD3+/CD8+ T cells and IFN-γ production, compared to single-peptide pulsed or unpulsed conditions. Notably, MSLN/NCL-specific T cells successfully induced cell death in MSLN+/NCL+ MDA-MB-231 cells, releasing key cytotoxic factors such as perforin, granzymes A and B, Fas ligand, IFN-γ, and granulysin.

CONCLUSIONS

These findings serve as a proof-of-concept for using multiple immunogenic peptides as a novel therapeutic approach in TNBC patients.

A novel mutation-proof, next-generation vaccine to fight against upcoming SARS-CoV-2 variants and subvariants, designed through AI enabled approaches and tools, along with the machine learning based immune simulation: A vaccine breakthrough

Emerging SARS-CoV-2 variants and subvariants are great concerns for their significant mutations, which are also responsible for vaccine escape. Therefore, the study was undertaken to develop a mutation-proof, next-generation vaccine to protect against all upcoming SARS-CoV-2 variants. We used advanced computational and bioinformatics approaches to develop a multi-epitopic vaccine, especially the AI model for mutation selection and machine learning (ML) strategies for immune simulation. AI-enabled and the top-ranked antigenic selection approaches were used to select nine mutations from 835 RBD mutations. We selected twelve common antigenic B cell and T cell epitopes (CTL and HTL) containing the nine RBD mutations and joined them with the adjuvants, PADRE sequence, and suitable linkers. The constructs' binding affinity was confirmed through docking with TLR4/MD2 complex and showed significant binding free energy (-96.67 kcal mol^-1) with positive binding affinity. Similarly, the calculated eigenvalue (2.428517e-05) from the NMA of the complex reveals proper molecular motion and superior residues' flexibility. Immune simulation shows that the candidate can induce a robust immune response. The designed mutation-proof, multi-epitopic vaccine could be a remarkable candidate for upcoming SARS-CoV-2 variants and subvariants. The study method might guide researchers in developing AI-ML and immunoinformatics-based vaccines for infectious disease.

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.

Designing, characterization, and immune stimulation of a novel multi-epitopic peptide-based potential vaccine candidate against monkeypox virus through screening its whole genome encoded proteins: An immunoinformatics approach

BACKGROUND

The current monkeypox virus (MPXV) spread in the non-epidemic regions raises global concern. Presently, the smallpox vaccine is used against monkeypox with several difficulties. Conversely, no next-generation vaccine is available against MPXV. Here, we proposed a novel multi-epitopic peptide-based in-silico potential vaccine candidate against the monkeypox virus.

METHODS

The multi-epitopic potential vaccine construct was developed from antigen screening through whole genome-encoded 176 proteins of MPXV. Afterward, ten common B and T cell epitopes (9-mer) having the highest antigenicity and high population coverage were chosen, and a vaccine construct was developed using peptide linkers. The vaccine was characterized through bioinformatics to understand antigenicity, non-allergenicity, physicochemical properties, and binding affinity to immune receptors (TLR4/MD2-complex). Finally, the immune system simulation of the vaccine was performed through immunoinformatics and machine learning approaches.

RESULTS

The highest antigenic epitopes were used to design the vaccine. The docked complex of the vaccine and TLR4/MD2 had shown significant free binding energy (-98.37 kcal/mol) with a definite binding affinity. Likewise, the eigenvalue (2.428517e-05) from NMA analysis of this docked complex reflects greater flexibility, adequate molecular motion, and reduced protein deformability, and it can provoke a robust immune response.

CONCLUSIONS

The designed vaccine has shown the required effectiveness against MPXV without any side effects, a significant milestone against the neglected disease.

Comparative genomics, evolutionary epidemiology, and RBD-hACE2 receptor binding pattern in B.1.1.7 (Alpha) and B.1.617.2 (Delta) related to their pandemic response in UK and India

Background

The massive increase in COVID-19 infection had generated a second wave in India during May–June 2021 with a critical pandemic situation. The Delta variant (B.1.617.2) was a significant factor during the second wave. Conversely, the UK had passed through the crucial phase of the pandemic from November to December 2020 due to B.1.1.7. The study tried to comprehend the pandemic response in the UK and India to the spread of the B.1.1.7 (Alpha, UK) variant and B.1.617.2 (Delta, India) variant.

Methods

This study was performed in three directions to understand the pandemic response of the two emerging variants. First, we served comparative genomics, such as genome sequence submission patterns, mutational landscapes, and structural landscapes of significant mutations (N501Y, D614G, L452R, E484Q, and P681R). Second, we performed evolutionary epidemiology using molecular phylogenetics, scatter plots of the cluster evaluation, country-wise transmission pattern, and frequency pattern. Third, the receptor binding pattern was analyzed using the Wuhan reference strain and the other two variants.

Results

The study analyzed the country-wise and region-wise genome sequences and their submission pattern, molecular phylogenetics, scatter plot of the cluster evaluation, country-wise geographical distribution and transmission pattern, frequency pattern, entropy diversity, and mutational landscape of the two variants. The structural pattern was analyzed in the N501Y, D614G L452R, E484Q, and P681R mutations. The study found increased molecular interactivity between hACE2-RBD binding of B.1.1.7 and B.1.617.2 compared to the Wuhan reference strain. Our receptor binding analysis showed a similar indication pattern for hACE2-RBD of these two variants. However, B.1.617.2 offers slightly better stability in the hACE2-RBD binding pattern through MD simulation than B.1.1.7.

Conclusion

The increased hACE2-RBD binding pattern of B.1.1.7 and B.1.617.2 might help to increase the infectivity compared to the Wuhan reference strain.