Designing of a multi-epitopes based vaccine against Haemophilius parainfluenzae and its validation through integrated computational approaches

Haemophilus parainfluenzae is a Gram-negative opportunist pathogen within the mucus of the nose and mouth without significant symptoms and has an ability to cause various infections ranging from ear, eye, and sinus to pneumonia. A concerning development is the increasing resistance of H. parainfluenzae to beta-lactam antibiotics, with the potential to cause dental infections or abscesses. The principal objective of this investigation is to utilize bioinformatics and immuno-informatic methodologies in the development of a candidate multi-epitope Vaccine. The investigation focuses on identifying potential epitopes for both B cells (B lymphocytes) and T cells (helper T lymphocytes and cytotoxic T lymphocytes) based on high non-toxic and non-allergenic characteristics. The selection process involves identifying human leukocyte antigen alleles demonstrating strong associations with recognized antigenic and overlapping epitopes. Notably, the chosen alleles aim to provide coverage for 90% of the global population. Multi-epitope constructs were designed by using suitable linker sequences. To enhance the immunological potential, an adjuvant sequence was incorporated using the EAAAK linker. The final vaccine construct, comprising 344 amino acids, was achieved after the addition of adjuvants and linkers. This multi-epitope Vaccine demonstrates notable antigenicity and possesses favorable physiochemical characteristics. The three-dimensional conformation underwent modeling and refinement, validated through in-silico methods. Additionally, a protein-protein molecular docking analysis was conducted to predict effective binding poses between the multi-epitope Vaccine and the Toll-like receptor 4 protein. The Molecular Dynamics (MD) investigation of the docked TLR4-vaccine complex demonstrated consistent stability over the simulation period, primarily attributed to electrostatic energy. The docked complex displayed minimal deformation and enhanced rigidity in the motion of residues during the dynamic simulation. Furthermore, codon translational optimization and computational cloning was performed to ensure the reliability and proper expression of the multi-Epitope Vaccine. It is crucial to emphasize that despite these computational validations, experimental research in the laboratory is imperative to demonstrate the immunogenicity and protective efficacy of the developed vaccine. This would involve practical assessments to ascertain the real-world effectiveness of the multi-epitope Vaccine.

Immunoinformatic based designing of potential immunogenic novel mRNA and peptide-based prophylactic vaccines against H5N1 and H7N9 avian influenza viruses

Influenza viruses are the most common cause of serious respiratory illnesses worldwide and are responsible for a significant number of annual fatalities. Therefore, it is crucial to look for new immunogenic sites that might trigger an effective immune response. In the present study, bioinformatics tools were used to design mRNA and multiepitope-based vaccines against H5N1 and H7N9 subtypes of avian influenza viruses. Several Immunoinformatic tools were employed to extrapolate T and B lymphocyte epitopes of HA and NA proteins of both subtypes. The molecular docking approach was used to dock the selected HTL and CTL epitopes with the corresponding MHC molecules. Eight (8) CTL, four (4) HTL, and Six (6) linear B cell epitopes were chosen for the structural arrangement of mRNA and of peptide-based prophylactic vaccine designs. Different physicochemical characteristics of the selected epitopes fitted with suitable linkers were analyzed. High antigenic, non-toxic, and non-allergenic features of the designed vaccines were noted at a neutral physiological pH. Codon optimization tool was used to check the GC content and CAI value of constructed MEVC-Flu vaccine, which were recorded to be 50.42% and 0.97 respectively. the GC content and CAI value verify the stable expression of vaccine in pET28a + vector. In-silico immunological simulation the MEVC-Flu vaccine construct revealed a high level of immune responses. The molecular dynamics simulation and docking results confirmed the stable interaction of TLR-8 and MEVC-Flu vaccine. Based on these parameters, vaccine constructs can be regarded as an optimistic choice against H5N1 and H7N9 strains of the influenza virus. Further experimental testing of these prophylactic vaccine designs against pathogenic avian influenza strains may clarify their safety and efficacy.Communicated by Ramaswamy H. Sarma.

Immuno-bioinformatic approach for designing of multi-epitope merozoite surface antigen of Babesia bigemina and evaluation of its immunogenicity in inoculated calves

Babesiosis is a parasitic disease caused by intraerythrocytic parasites of the genus Babesia, which infect both wild and domestic animals. Merozoite surface antigens (MSAs) have been identified as efficient immunogens in Babesia-infected animals. MSAs play a key role in the invasion process and have been proposed as potential targets for vaccine development. Epitope-based vaccines offer several advantages over whole protein vaccines as the immunogenic proteins are small and can induce both Th1 and Th2 immune responses, which are desirable for protection. However, the MSA, particularly gp45, is polymorphic in Babesia bigemina, posing a challenge to vaccine development. The purpose of this study was to develop a recombinant gpME (gp45-multi-epitope) for a vaccine against Babesia bigemina. B-cell, T-cell, and HLA epitope predictions were used to synthesize the gpME sequence from the consensus sequence of gp45. The gpME sequence was synthesized and cloned in the pET28α vector through the commercial biotechnology company to get pET28-gpME. The plasmid cloned with the gpME sequence comprising 1068 bp was expressed in a bacterial expression system. A band of 39 kDa of rec-gpME was obtained via SDS-PAGE and Western blotting. Rec-gpME @200ng was injected in calves 3 times at 2 weeks interval. The humoral response was evaluated through the indirect ELISA method. The ELISA with rec-gp45 protein showed a significant value of optical density. The recombinant protein containing multiple epitopes from the MSA gp45 may represent a promising candidate for a vaccine against Babesia bigemina.

Computational Design of a Chimeric Vaccine against Plesiomonas shigelloides Using Pan-Genome and Reverse Vaccinology

The swift emergence of antibiotic resistance (AR) in bacterial pathogens to make themselves adaptable to changing environments has become an alarming health issue. To prevent AR infection, many ways can be accomplished such as by decreasing the misuse of antibiotics in human and animal medicine. Among these AR bacterial species, Plesiomonas shigelloides is one of the etiological agents of intestinal infection in humans. It is a gram-negative rod-shaped bacterium that is highly resistant to several classes of antibiotics, and no licensed vaccine against the aforementioned pathogen is available. Hence, substantial efforts are required to screen protective antigens from the pathogen whole genome that can be subjected easily to experimental evaluations. Here, we employed a reverse vaccinology (RV) approach to design a multi-antigenic epitopes based vaccine against P. shigelloides. The complete genomes of P. shigelloides were retrieved from the National Center for Biotechnological Information (NCBI) that on average consist of 5226 proteins. The complete proteomes were subjected to different subtractive proteomics filters, and in the results of that analysis, out of total proteins, 2399 were revealed as non-redundant and 2827 as redundant proteins. The non-redundant proteins were further checked for subcellular localization analysis, in which three were localized in the extracellular matrix, eight were outer membrane, and 13 were found in the periplasmic membrane. All surface localized proteins were found to be virulent. Out of a total of 24 virulent proteins, three proteins (flagellar hook protein (FlgE), hypothetical protein, and TonB-dependent hemoglobin/transferrin/lactoferrin family receptor protein) were considered as potential vaccine targets and subjected to epitopes prediction. The predicted epitopes were further examined for antigenicity, toxicity, and solubility. A total of 10 epitopes were selected (GFKESRAEF, VQVPTEAGQ, KINENGVVV, ENKALSQET, QGYASANDE, RLNPTDSRW, TLDYRLNPT, RVTKKQSDK, GEREGKNRP, RDKKTNQPL). The selected epitopes were linked with each other via specific GPGPG linkers in order to design a multi-epitopes vaccine construct, and linked with cholera toxin B subunit adjuvant to make the designed vaccine construct more efficient in terms of antigenicity. The 3D structure of the vaccine construct was modeled ab initio as no appropriate template was available. Furthermore, molecular docking was carried out to check the interaction affinity of the designed vaccine with major histocompatibility complex (MHC-)I (PDB ID: 1L1Y), MHC-II (1KG0), and toll-like receptor 4 ((TLR-4) (PDB: 4G8A). Molecular dynamic simulation was applied to evaluate the dynamic behavior of vaccine-receptor complexes. Lastly, the binding free energies of the vaccine with receptors were estimated by using MMPB/GBSA methods. All of the aforementioned analyses concluded that the designed vaccine molecule as a good candidate to be used in experimental studies to disclose its immune protective efficacy in animal models.

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.

Vaccine Design from the Ensemble of Surface Glycoprotein Epitopes of SARS-CoV-2: An Immunoinformatics Approach

The present study aimed to work out a peptide-based multi-epitope vaccine against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We predicted different B-cell and T-cell epitopes by using the Immune Epitopes Database (IEDB). Homology modeling of the construct was done using SWISS-MODEL and then docked with different toll-like-receptors (TLR4, TLR7, and TLR8) using PatchDock, HADDOCK, and FireDock, respectively. From the overlapped epitopes, we designed five vaccine constructs C1–C5. Based on antigenicity, allergenicity, solubility, different physiochemical properties, and molecular docking scores, we selected the vaccine construct 1 (C1) for further processing. Docking of C1 with TLR4, TLR7, and TLR8 showed striking interactions with global binding energy of −43.48, −65.88, and −60.24 Kcal/mol, respectively. The docked complex was further simulated, which revealed that both molecules remain stable with minimum RMSF. Activation of TLRs induces downstream pathways to produce pro-inflammatory cytokines against viruses and immune system simulation shows enhanced antibody production after the booster dose. In conclusion, C1 was the best vaccine candidate among all designed constructs to elicit an immune response SARS-CoV-2 and combat the coronavirus disease (COVID-19).

Designing of a multi-epitope vaccine candidate against Nipah virus by in silico approach: a putative prophylactic solution for the deadly virus

Nipah virus (NPV) is one of the most notorious viruses with a very high fatality rate. Because of the recurrent advent of this virus and its severe neurological implications, often leading to high mortality, the WHO R&D Blueprint, 2018 has listed the Nipah virus as one of the emerging infectious diseases requiring urgent research and development effort. Yet there is a major layback in the development of effective vaccines or drugs against NPV. In this study, we have designed a stable multivalent vaccine combining several T-cell and B-cell epitopes of the essential Nipah viral proteins with the help of different ligands and adjuvants which can effectively induce both humoral and cellular immune responses in human. Different advanced immune-informatic tools confirm the stability, high immunogenicity and least allergenicity of the vaccine candidate. The standard molecular dynamic cascade analysis validates the stable interaction of the vaccine construct with the human Toll-like receptor 3 (TLR3) complex. Later, codon optimization and in silico cloning in a known pET28a vector system shows the possibility for the expression of this vaccine in a simple organism like E.coli. It is believed that with further in vitro and in vivo validation, this vaccine construct can pose to be a better prophylactic solution to the Nipah viral disease. Communicated by Ramaswamy H. Sarma.

DNA plasmid vaccine carrying Chlamydia trachomatis (Ct) major outer membrane and human papillomavirus 16L2 proteins for anti-Ct infection

Chlamydia trachomatis (Ct) is one of the most frequently encountered sexual infection all over the world, yielding tremendous reproductive problems (e.g. infertility and ectopic pregnancy) in the women. This work described the design of a plasmid vaccine that protect mice from Ct infection, and reduce productive tract damage by generating effective antibody and cytotoxic T cell immunity. The vaccine, s was composed of MOMP multi-epitope and HPV16L2 genes carried in pcDNA plasmid (i.e. pcDNA3.1/MOMP/HPV16L). In transfection, the vaccine expressed the chimeric genes (i.e. MOMP and HPV16L2), as demonstrated via western blot, RT-PCR and fluorescence imaging. In vitro, the vaccine transfected COS-7 cells and expressed the proteins corresponding to the genes carried in the vaccine. Through intramuscular immunization in BALB/c mice, the vaccine induced higher levels of anti-Ct IgG titer, anti-HPV16L2 IgG titer in serum and IgA titer in local mucosal secretions, compared to plasmid vaccines that carry only Ct MOMP multi-epitope or HPV16L2 chimeric component only. In mice intravaginally challenged with Ct, the vaccines pcDNA3.1/MOMP/HPV16L2 generated a higher level of genital protection compared to other vaccine formulations. Additionally, histochemical staining indicated that pcDNA3.1/MOMP/HPV16L2 eliminated mouse genital tract tissue pathologies induced by Ct infection. This work demonstrated that pcDNA/MOMP/HPV16L2 vaccine can protect against Ct infection by regulating antibody production, cytotoxic T cell killing functions and reducing pathological damage in mice genital tract. This work can potentially offer us a new vaccine platform against Ct infection.