Peptide Vaccine Construct Research Articles

Novel toxin-based mRNA vaccine against Clostridium perfringens using in silico approaches

Clostridium perfringens is a bacterium that causes gastrointestinal diseases in humans and animals. The several powerful toxins such as alpha toxin (CPA), beta toxin (CPB), enterotoxin (CPE), Epsilon toxin (ETX), and theta toxin, play a major role in its pathogenesis. Traditional vaccine development methods are time-consuming and costly. In silico approaches offer an alternative strategy for designing vaccines by analyzing biological data and predicting immunogenic peptides. In this study, computational tools were utilized to design a RNA vaccine targeting C. perfringens toxins. Toxin protein sequences were retrieved and their linear B-cell, MHCI, and MHCII binding epitopes were predicted. Allergenicity, toxigenicity, and IFN-γ induction were assessed to select non-allergenic, non-toxic, and IFN-γ-inducing epitopes. Molecular docking was performed to identify epitopes that fit within the binding cleft of MHC alleles. A final peptide vaccine construct was designed with selected epitopes separated by a linker sequence. The antigenicity and physicochemical properties of the vaccine were evaluated. Immune response simulation showed enhanced secondary and tertiary immune responses, increased levels of immunoglobulins, cytotoxic T lymphocytes, helper T lymphocytes, macrophage activity, and elevated levels IFN-γ and interleukin-2. Docking analysis was done to assess interactions between the vaccine structure and Toll-like receptors. Codon optimization was performed, and a final RNA vaccine construct was designed. The secondary structure of the RNA vaccine was predicted and validated. Overall, this study demonstrates the potential of in silico approaches for designing an RNA vaccine against C. perfringens toxins, contributing to improved prevention and control of associated diseases.

MRNA Vaccine Designing Using Chikungunya Virus E Glycoprotein through Immunoinformatics-Guided Approaches.

Chikungunya virus is an alphavirus transmitted by mosquitos that develops into chikungunya fever and joint pain in humans. This virus’ name originated from a Makonde term used to describe an illness that changes the joints and refers to the posture of afflicted patients who are affected by excruciating joint pain. There is currently no commercially available drug or vaccine for chikungunya virus infection and the treatment is performed by symptom reduction. Herein, we have developed a computationally constructed mRNA vaccine construct featuring envelope glycoprotein as the target molecule to aid in the treatment process. We have utilized the reverse vaccinology approach to determine epitopes that would generate adaptive immune reactions. The resulting T and B lymphocytes epitopes were screened by various immunoinformatic tools and a peptide vaccine construct was designed. It was validated by proceeding to docking and MD simulation studies. The following design was then back-translated in nucleotide sequence and codons were optimized according to the expression host system (H. sapiens). Various sequences, including 3′ and 5′ UTR regions, Kozak sequence, poly (A) tail, etc., were introduced into the sequence for the construction of the final mRNA vaccine construct. The secondary structure was generated for validation of the mRNA vaccine construct sequence. Additionally, in silico cloning was also performed to design a vector for proceeding towards in vitro experimentation. The proposed designed vaccine construct may proceed with experimental testing for further efficacy verification and the final development of a vaccine against chikungunya virus infection.

Computational Design of a Multi-Epitope Vaccine Against Porphyromonas gingivalis.

Porphyromonas gingivalis is a Gram-negative pathogenic bacterium associated with chronic periodontitis. The development of a chimeric peptide-based vaccine targeting this pathogen could be highly beneficial in preventing oral bone loss as well as other severe gum diseases. We applied a computational framework to design a multi-epitope-based vaccine candidate against P. gingivalis. The vaccine comprises epitopes from subunit proteins prioritized from the P. gingivalis reference strain (P. gingivalis ATCC 33277) using several reported vaccine properties. Protein-based subunit vaccines were prioritized through genomics techniques. Epitope prediction was performed using immunoinformatic servers and tools. Molecular modeling approaches were used to build a putative three-dimensional structure of the vaccine to understand its interactions with host immune cells through biophysical techniques such as molecular docking simulation studies and binding free energy methods. Genome subtraction identified 18 vaccine targets: six outer-membrane, nine cytoplasmic membrane-, one periplasmic, and two extracellular proteins. These proteins passed different vaccine checks required for the successful development of a vaccine candidate. The shortlisted proteins were subjected to immunoinformatic analysis to map B-cell derived T-cell epitopes, and antigenic, water-soluble, non-toxic, and good binders of DRB1*0101 were selected. The epitopes were then modeled into a multi-epitope peptide vaccine construct (linked epitopes plus adjuvant) to enhance immunogenicity and effectively engage both innate and adaptive immunity. Further, the molecular docking approach was used to determine the binding conformation of the vaccine to TLR2 innate immune receptor. Molecular dynamics simulations and binding free energy calculations of the vaccine–TLR2 complex were performed to highlight key intermolecular binding energies. Findings of this study will be useful for vaccine developers to design an effective vaccine for chronic periodontitis pathogens, specifically P. gingivalis.

Pan-vaccinomics approach towards a universal vaccine candidate against WHO priority pathogens to address growing global antibiotic resistance.

Antimicrobial resistance (AMR) in bacterial pathogens is a major global distress. Due to the slow progress of antibiotics development and the fast pace of resistance acquisition, there is an urgent need for effective vaccines against such bacterial pathogens. In-silico approaches including pan-genomics, subtractive proteomics, reverse vaccinology, immunoinformatics, molecular docking, and dynamics simulation studies were applied in the current study to identify a universal potential vaccine candidate against the 18 multi-drug resistance (MDRs) bacterial pathogenic species from a WHO priority list. Ten non-redundant, non-homologous, virulent, and antigenic vaccine candidates were filtered against all targeted species. Nine B-cell-derived T-cell antigen epitopes which show a great affinity to the dominant HLA allele (DRB1*0101) in the human population were screened from selected vaccine candidates using immunoinformatics approaches. Screened epitopes were then used to design a multi-epitope peptide vaccine construct (MEPVC) along with β-defensin adjuvant to improve the immunogenic properties of the proposed vaccine construct. Molecular docking and MD simulation were carried out to study the binding affinity and molecular interaction of MEPVC with human immune receptors (TLR2, TLR3, TLR4, and TLR6). The final MEPVC construct was reverse translated and in-silico cloned in the pET28a(+) vector to ensure its effectiveness. This in silico construct is expected to be helpful for vaccinologists to assess its immune protection effectiveness in vivo and in vitro to counter rising antibiotic resistance worldwide.

A Next-Generation Vaccine Candidate Using Alternative Epitopes to Protect against Wuhan and All Significant Mutant Variants of SARS-CoV-2: An Immunoinformatics Approach.

Newly emerging significant SARS-CoV-2 variants such as B.1.1.7, B.1.351, and B.1.1.28 are the variant of concern (VOC) for the human race. These variants are getting challenging to contain from spreading worldwide. Because of these variants, the second wave has started in various countries and is threatening human civilization. Thus, we require efficient vaccines that can combat all emerging variants of SARS-CoV-2. Therefore, we took the initiative to develop a peptide-based next-generation vaccine using four variants (Wuhan variant, B.1.1.7, B.1.351, and B.1.1.28) that could potentially combat SARS-CoV-2 variants. We applied a series of computational tools, servers, and software to identify the most significant epitopes present on the mutagenic regions of SARS-CoV-2 variants. The immunoinformatics approaches were used to identify common B cell derived T cell epitopes, influencing the host immune system. Consequently, to develop a novel vaccine candidate, the antigenic epitopes were linked with a flexible and stable peptide linker, and the adjuvant was added at the N-terminal end. 3D vaccine candidate structure was refined, and quality was assessed using web servers. The physicochemical properties and safety parameters of the vaccine construct were assessed through bioinformatics and immunoinformatics tools. The molecular docking analysis between TLR4/MD2 and the proposed vaccine candidate demonstrated a satisfactory interaction. The molecular dynamics studies confirmed the stability of the vaccine candidate. Finally, we optimized the proposed vaccine through codon optimization and in silico cloning to study the expression. Our multi-epitopic next-generation peptide vaccine construct can boost immunity against the Wuhan variant and all significant mutant variants of SARS-CoV-2.

Immunoinformatics characterization of SARS-CoV-2 spike glycoprotein for prioritization of epitope based multivalent peptide vaccine

The COVID-19 pandemic caused by SARS-CoV-2 is a public health emergency of international concern and thus calling for the development of effective and safe therapeutics and prophylactics particularly a vaccine to protect against the infection. SARS-CoV-2 spike glycoprotein is an attractive candidate for a vaccine, antibodies, and inhibitors development because of the many roles it plays in attachment, fusion and entry into the host cell. In the present investigation, we characterized the SARS-CoV-2 spike glycoprotein by immunoinformatics techniques to put forward potential B and T cell epitopes, followed by the use of epitopes in construction of a multi-epitope peptide vaccine construct (MEPVC). The MEPVC revealed robust host immune system simulation with high production of immunoglobulins, cytokines and interleukins. Stable conformation of the MEPVC with a representative innate immune TLR3 receptor was observed involving strong hydrophobic and hydrophilic chemical interactions, along with enhanced contribution from salt-bridges towards inter-molecular stability. Molecular dynamics simulation in aqueous milieu aided further in interpreting strong affinity of the MEPVC for TLR3. This stability is the attribute of several vital residues from both TLR3 and MEPVC as shown by radial distribution function (RDF) and a novel axial frequency distribution (AFD) analytical tool. Comprehensive binding free energies estimation was provided at the end that concluded major domination by electrostatic and minor from van der Waals. Summing all, the designed MEPVC has tremendous potential of providing protective immunity against COVID-19 and thus could be considered in experimental studies.

Vaccinomics to design a novel single chimeric subunit vaccine for broad-spectrum immunological applications targeting nosocomial Enterobacteriaceae pathogens

Healthcare associated infections (HAIs) are major cause of elevated mortality, morbidity, and high healthcare costs. Development of a vaccine targeting these pathogens could benefit in reducing HAIs count and excessive use of antibiotics. This work aimed to design a multi-epitope based prophylactic/ therapeutic vaccine directing against carbapenem resistant Enterobacter cloacae and other leading nosocomial members of Enterobacteriaceae group. Based on subtractive proteomics and immunoinformatics in-depth investigation of E. cloacae reference proteome, we prioritize four targets: outer membrane usher protein-lpfC, putative outer membrane protein A-OmpA, putative outer membrane protein-FimD, and arginine transporter fulfilling criteria of vaccine candidacy. A multi-epitope peptide vaccine construct is then formulated comprising predicted epitopes with potential to evoke both innate and adaptive immunity and B-subunit of cholera toxin as an adjuvant. The construct is modelled, loop refined, improved for stability via disulfide engineering and optimized for codon usage as per Escherichia coli expression system to ensure its maximum expression. Cross-conservation analysis carried out to evaluate broad-spectrum applicability by providing cross protection against nosocomial pathogens. A blind docking method is applied further to predict predominant binding mode of the construct with TLR4 innate immune receptor, followed by molecular dynamics simulation protocol to probe complex dynamics and exposed topology of the construct epitopes for recognition and immune processing by the host. Towards the end, binding free energies of the vaccine construct-TLR4 receptor were estimated to test docking predictions and affirm complex stability. We believe these findings to be highly useful for vaccinologists in making a highly effective vaccine for E. cloacae specifically, and other notorious Enterobacteriaceae nosocomial pathogens in general.

Immunoinformatics Design of Novel Multi-Epitope Subunit Vaccine for SARS-CoV-2 by Exploring Virus Conserved Sequences of the Spike Glycoproteins

Sars-CoV-2 infection also called COVID-19 is characterized by fever and signs of acute respiratory distress syndrome (ARDS). It is currently a global pandemic with high mortality rate in those with severe disease. Lack of effective vaccine and approved drug for treatment created a disastrous condition among the global communities. This study was designed as a step ahead in the path of protein-based subunit vaccine development. The primary amino acid sequence of SARS-CoV-2 spike glycoprotein was used to design a protein subunit vaccine construct. The molecular weight of vaccine protein was 58.4 kDa with a total number of 8170 atoms and 584 amino acid residues. The theoretical pI was found to be 8.54 showing its slightly basic nature while the total number of negative and positive charged residues were 29 and 33 respectively. The peptide vaccine construct has 147 (25.17%) polar residues and 375 (64.21%) hydrophobic residues. The vaccine construct has cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL) and B cell epitopes of varying lengths having great potential to stimulate high levels of IFN-γ production. It has potent antigenic properties but lacked allergenicity. It is stable and have a good binding affinity for the TLR-4 receptor. In general, this modelling applied a series of immunoinformatics tools in a sequential manner to find an effective vaccine that may be used effectively in fighting against the COVID-19 pandemic. This modelling, however, needs real life experimental validation to prove the workability of the computational work.

In Silico Analysis of Synaptonemal Complex Protein 1 (SYCP1) and Acrosin Binding Protein (ACRBP) Antigens to Design Novel Multiepitope Peptide Cancer Vaccine Against Breast Cancer

Multiepitope cancer vaccines are manifesting as the future of breast cancer immunotherapy. In the present study, high immunogenic fragments of synaptonemal complex protein 1 (SYCP1) and acrosin binding protein (ACRBP) antigens were selected according to MHCs binding affinity and CD8+ cytotoxic T lymphocytes’ (CTL) epitopes by various immunoinformatic servers. (RCQHKIAEMVALMEKHKHQYDKI) residue from p702–724 SYCP1 and the (YIQYPNYCSFKSQQCL) residue from p481–496 ACRBP were selected as the immunodominant fragments. Then, the selected fragments were fused together with a furin-sensitive linker to form the final peptide vaccine construct. The cleavage sites, TAP transport efficiency, CTL epitopes, post-translational modifications, and B cells epitopes were predicted for the final construct. The final construct contained appropriate CTLs epitopes and also, several linear and conformational B cell epitopes. Also, it exhibited 90.37% HLA population coverage in the world. Therefore, these preliminary results require validation by in vitro and in vivo experiments.

From Immunity and Vaccines to Mammalian Regeneration

Our current understanding of major histocompatibility complex (MHC)-mediated antigen presentation in self and nonself immune recognition was derived from immunological studies of autoimmunity and virus-host interactions, respectively. The trimolecular complex of the MHC molecule, antigen, and T-cell receptor accounts for the phenomena of immunodominance and MHC degeneracy in both types of responses and constrains vaccine development. Out of such considerations, we developed a simple peptide vaccine construct that obviates immunodominance, resulting in a broadly protective T-cell response in the absence of antibody. In the course of autoimmunity studies, we identified the MRL mouse strain as a mammalian model of amphibian-like regeneration. A significant level of DNA damage in the cells from this mouse pointed to the role of the cell cycle checkpoint gene CDKN1a, or p21(cip1/waf1). The MRL mouse has highly reduced levels of this molecule, and a genetic knockout of this single gene in otherwise nonregenerating strains led to an MRL-type regenerative response, indicating that the ability to regenerate has not been lost during evolution.

Repeat region of Brugia malayi sheath protein (Shp-1) carries Dominant B epitopes recognized in filarial endemic population.

Transmission of lymphatic filariasis is mediated through microfilariae (L1 stage of the parasite) which is encased in an eggshell called sheath. The sheath protein Shp-1 stabilizes the structure due to the unique repeat region with Met-Pro-Pro-Gln-Gly sequences. Microfilarial proteins could be used as transmission blocking vaccines. Since the repeat region of Shp-1 was predicted to carry putative B epitopes, this region was used to analyze its reactivity with clinical samples towards construction of peptide vaccine. In silico analysis of Shp-1 showed the presence of B epitopes in the region 49-107. The polypeptide epitopic region Shp-149-107 was cloned and expressed in Escherichia coli. Antibody reactivity of the Shp-149-107 construct was evaluated in filarial endemic population by ELISA. Putatively immune endemic normals (EN) showed significantly high reactivity (P < 0.05) when compared to all the other categories. Antibody reactivity of Shp-1 repeat region was similar to that of whole protein proving that this region carries B epitopes responsible for its humoral response in humans. Thus this can be employed for inducing anti-microfilarial immunity in the infected population that may lead to reduction in transmission intensity and also it could be used along with other epitopes from different stages of the parasite in order to manage the disease effectively.