Designing of Complex Multi-epitope Peptide Vaccine Based on Omps of Klebsiella pneumoniae: An In Silico Approach

Designing of multi-epitope peptide vaccine against Acinetobacter baumannii through combined immunoinformatics and protein interaction-based approaches

Acinetobacter baumannii is one of the major pathogenic ESKAPE bacterium, which is responsible for about more than 722,000 cases in a year, globally. Despite the alarming increase in multidrug resistance, a safe and effective vaccine for Acinetobacter infections is still not available. Hence in the current study, a multiepitope vaccine construct was developed using linear B cell, cytotoxic T cell, and helper T cell epitopes from the antigenic and well-conserved lipopolysaccharide assembly proteins employing systematic immunoinformatics and structural vaccinology strategies. The multi-peptide vaccine was predicted to be highly antigenic, non-allergenic, non-toxic, and cover maximum population coverage worldwide. Further, the vaccine construct was modeled along with adjuvant and peptide linkers and validated to achieve a high-quality three-dimensional structure which was subsequently utilized for cytokine prediction, disulfide engineering, and docking analyses with Toll-like receptor (TLR4). Ramachandran plot showed 98.3% of the residues were located in the most favorable and permitted regions, thereby corroborating the feasibility of the modeled vaccine construct. Molecular dynamics simulation for a 100 ns timeframe further confirmed the stability of the binding vaccine-receptor complex. Finally, in silico cloning and codon adaptation were also performed with the pET28a (+) plasmid vector to determine the efficiency of expression and translation of the vaccine. Immune simulation studies demonstrated that the vaccine could trigger both B and T cell responses and can elicit strong primary, secondary, and tertiary immune responses. The designed multi-peptide subunit vaccine would certainly expedite the experimental approach for the development of a vaccine against A. baumannii infection.

Bioinformatics analysis of structural protein to approach a vaccine candidate against Vibrio cholerae infection

The bacteria Vibrio cholerae causes cholera, an acute diarrheal infection that can lead to dehydration and even death. Over 100,000 people die each year as a result of epidemic diseases; vaccination has emerged as a successful strategy for combating cholera. This study uses bioinformatics tools to create a multi-epitope vaccine against cholera infection using five structural polyproteins from the V. cholerae (CTB, TCPA, TCPF, OMPU, and OMPW). The antigenic retrieved protein sequence were analyzed using BCPred and IEDB bioinformatics tools to predict B cell and T cell epitopes, respectively, which were then linked with flexible linkers together with an adjuvant to boost it immunogenicity. The construct has a theoretical PI of 6.09, a molecular weight of 53.85 kDa, and an estimated half-life for mammalian reticulocytes in vitro of 4.4 h. These results demonstrate the construct's longevity. The vaccine design was docked against the human toll-like receptor (TLR) to evaluate compatibility and effectiveness; also other additional post-vaccination assessments were carried out on the designed vaccine. Through in silico cloning, its expression was determined. The results show that it has a CAI value of 0.1 and GC contents of 58.97% which established the adequate expression and downstream processing of the vaccine construct, and our research demonstrated that the multi-epitope subunit vaccine exhibits antigenic characteristics. Additionally, we carried out an in silico immunological simulation to examine the immune reaction to an injection. Our results strongly suggest that the vaccine candidate on further validation would induce immune response against the V. cholerae infection.

Integration of immunoinformatics and cheminformatics to design and evaluate a multitope vaccine against Klebsiella pneumoniae and Pseudomonas aeruginosa coinfection

Introduction: Klebsiella pneumoniae (K. pneumoniae) and Pseudomonas aeruginosa (P. aeruginosa) are the most common Gram-negative bacteria associated with pneumonia and coinfecting the same patient. Despite their high virulence, there is no effective vaccine against them. Methods: In the current study, the screening of several proteins from both pathogens highlighted FepA and OmpK35 for K. pneumonia in addition to HasR and OprF from P. aeruginosa as promising candidates for epitope mapping. Those four proteins were linked to form a multitope vaccine, that was formulated with a suitable adjuvant, and PADRE peptides to finalize the multitope vaccine construct. The final vaccine's physicochemical features, antigenicity, toxicity, allergenicity, and solubility were evaluated for use in humans. Results: The output of the computational analysis revealed that the designed multitope construct has passed these assessments with satisfactory scores where, as the last stage, we performed a molecular docking study between the potential vaccine construct and K. pneumonia associated immune receptors, TLR4 and TLR2, showing affinitive to both targets with preferentiality for the TLR4 receptor protein. Validation of the docking studies has proceeded through molecular dynamics simulation, which estimated a strong binding and supported the nomination of the designed vaccine as a putative solution for K. pneumoniae and P. aeruginosa coinfection. Here, we describe the approach for the design and assessment of our potential vaccine.

In silico design of a multi-epitope vaccine against HPV16/18

BACKGROUND

Cervical cancer is the fourth most common cancer affecting women and is caused by human Papillomavirus (HPV) infections that are sexually transmitted. There are currently commercially available prophylactic vaccines that have been shown to protect vaccinated individuals against HPV infections, however, these vaccines have no therapeutic effects for those who are previously infected with the virus. The current study's aim was to use immunoinformatics to develop a multi-epitope vaccine with therapeutic potential against cervical cancer.

RESULTS

In this study, T-cell epitopes from E5 and E7 proteins of HPV16/18 were predicted. These epitopes were evaluated and chosen based on their antigenicity, allergenicity, toxicity, and induction of IFN-γ production (only in helper T lymphocytes). Then, the selected epitopes were sequentially linked by appropriate linkers. In addition, a C-terminal fragment of Mycobacterium tuberculosis heat shock protein 70 (HSP70) was used as an adjuvant for the vaccine construct. The physicochemical parameters of the vaccine construct were acceptable. Furthermore, the vaccine was soluble, highly antigenic, and non-allergenic. The vaccine's 3D model was predicted, and the structural improvement after refinement was confirmed using the Ramachandran plot and ProSA-web. The vaccine's B-cell epitopes were predicted. Molecular docking analysis showed that the vaccine's refined 3D model had a strong interaction with the Toll-like receptor 4. The structural stability of the vaccine construct was confirmed by molecular dynamics simulation. Codon adaptation was performed in order to achieve efficient vaccine expression in Escherichia coli strain K12 (E. coli). Subsequently, in silico cloning of the multi-epitope vaccine was conducted into pET-28a ( +) expression vector.

CONCLUSIONS

According to the results of bioinformatics analyses, the multi-epitope vaccine is structurally stable, as well as a non-allergic and non-toxic antigen. However, in vitro and in vivo studies are needed to validate the vaccine's efficacy and safety. If satisfactory results are obtained from in vitro and in vivo studies, the vaccine designed in this study may be effective as a therapeutic vaccine against cervical cancer.

Multi-epitope-based vaccine design by exploring antigenic potential among leptospiral lipoproteins using comprehensive immunoinformatics and structure-based approaches

Leptospirosis is a tropical and globally neglected zoonotic disease caused by pathogenic spirochetes, leptospira. Although the disease has been studied for decades, a potent or effective vaccine is not available so far. Efforts are being made to design an efficient vaccine candidate using different approaches. Immunoinformatics approaches have been proven to be promising in terms of time and cost. Here, we used immunoinformatics and structure-based approaches to evaluate antigenic B and T-cell epitopes present on the Leptospiral lipoproteins (LipL). The promiscuous overlapping epitopes (B-cell, T-cell, IFN- γ positive and non-allergens), which can induce humoral, cell-mediated, and innate immunity, were selected to generate a multi-epitope chimeric vaccine. To enhance the vaccine immunogenicity, a TLR agonist was fused to the vaccine with a suitable linker. The chimeric vaccine structure was predicted for molecular docking studies with immune receptors. Moreover, the stability of the vaccine-immune receptor complexes was analyzed by normal mode analysis (NMA). The potency of the vaccine construct was predicted by the immune simulation tool. The study provides additional information towards constructing a peptide-based chimeric vaccine effort against Leptospira. This article is protected by copyright. All rights reserved.

Immuno-Informatics Based Peptides: An Approach for Vaccine Development Against Outer Membrane Proteins of Pseudomonas Genus

Pseudomonas genus is among the top nosocomial pathogens known to date. Being highly opportunistic, members of pseudomonas genus are most commonly connected with nosocomial infections of urinary tract and ventilator-associated pneumonia. Nevertheless, vaccine development for this pathogenic genus is slow because of no information regarding immunity correlated functional mechanism. In this present work, an immunoinformatics pipeline is used for vaccine development based on epitope-based peptide design, which can result in crucial immune response against outer membrane proteins of pseudomonas genus. A total of 127 outer membrane proteins were analysed, studied and out of them three sequences were obtained to be the producer of non-allergic, highly antigenic T-cell and B-cell epitopes which show good binding affinity towards class II HLA molecules. After performing rigorous screening utilizing docking, simulation, modelling techniques, we had one nonameric peptide (WLLATGIFL)as a good vaccine candidate. The predicted epitopes needs to be further validated for its apt use as vaccine. This work paves a new way with extensive therapeutic application against Pseudomonas genus and their associated diseases.

Immunoinformatics-Based Designing of a Multi-Epitope Chimeric Vaccine From Multi-Domain Outer Surface Antigens of Leptospira

Accurate information on antigenic epitopes within a multi-domain antigen would provide insights into vaccine design and immunotherapy. The multi-domain outer surface Leptospira immunoglobulin-like (Lig) proteins LigA and LigB, consisting of 12–13 homologous bacterial Ig (Big)-like domains, are potential antigens of Leptospira interrogans. Currently, no effective vaccine is available against pathogenic Leptospira. Both the humoral immunity and cell-mediated immunity of the host play critical roles in defending against Leptospira infection. Here, we used immunoinformatics approaches to evaluate antigenic B-cell lymphocyte (BCL) and cytotoxic T-lymphocyte (CTL) epitopes from Lig proteins. Based on certain crucial parameters, potential epitopes that can stimulate both types of adaptive immune responses were selected to design a chimeric vaccine construct. Additionally, an adjuvant, the mycobacterial heparin-binding hemagglutinin adhesin (HBHA), was incorporated into the final multi-epitope vaccine construct with a suitable linker. The final construct was further scored for its antigenicity, allergenicity, and physicochemical parameters. A three-dimensional (3D) modeled construct of the vaccine was implied to interact with Toll-like receptor 4 (TLR4) using molecular docking. The stability of the vaccine construct with TLR4 was predicted with molecular dynamics simulation. Our results demonstrate the application of immunoinformatics and structure biology strategies to develop an epitope-specific chimeric vaccine from multi-domain proteins. The current findings will be useful for future experimental validation to ratify the immunogenicity of the chimera.

Detecting the Dominant T and B Epitopes of Klebsiella pneumoniae Ferric Enterobactin Protein (FepA) and Introducing a Single Epitopic Peptide as Vaccine Candidate

Klebsiella pneumoniae causes various human infections. Ferric enterobactin protein (FepA) is a conserved protein of K. pneumoniae with high immunogenicity. In the present study, using comprehensive in silico approaches the T and B cell-specific epitopes of K. pneumoniae FepA were identified. The T (both class I and class II) and B (both linear and conformational) epitopes of FepA were predicted using prediction tools. The predicted epitopes were screened for human similarity, immunogenicity, antigenicity, allergenicity, toxicity, conservancy, structural and physicochemical suitability, and in case of T epitopes binding to HLA alleles, using numerous immune-informatics, homology modeling, and molecular docking approaches. These analyses led to introduce the most dominant FepA epitopes that are appropriate for vaccine development. Furthermore, we introduced an antigenic peptide containing both T and B epitopes which comprises suitable structural and physiochemical properties needed for vaccine development and it is conserved in many bacteria. Altogether, here the highly immunogenic T and B epitopes of FepA as well as a final epitopic peptide containing both T and B epitopes were found and introduced for future vaccine development studies. It is suggested that the actual efficiency and efficacy of our final epitopic peptide be investigated by in vitro/in vivo testing.

B Cell Epitopes of Four Fimbriae Antigens of Klebsiella pneumoniae: A Comprehensive In Silico Study for Vaccine Development

Klebsiella pneumoniae is one of the major causes of nosocomial infections worldwide which can cause several diseases in children and adults. The globally dissemination of hyper-virulent strains of K. pneumoniae and the emergence of antibiotics-resistant isolates of this pathogen narrows down the treatment options and has renewed interest in its vaccines. Vaccine candidates of Klebsiella pneumoniae have not been adequately protective, safe and globally available yet. In K. pneumoniae infection, it is well known that B cells that induce robust humoral immunity are necessary for the host complete protection. Identifying the B cell epitopes of antigens is valuable to design novel vaccine candidates. In the present study using immunoinformatics approaches we found B cell epitopes of four K. pneumoniae type 1 fimbriae antigens namely FimA, FimF, FimG, and FimH. Linear and conformational B cell epitopes of each antigen were predicted using different programs. Subsequently, many bioinformatics assays were applied to choose the best epitopes including prediction antigenicity, toxicity, human similarity and investigation on experimental records. These assays resulted in final four epitopes (each for one Fim protein). These final epitopes were modeled and their physiochemical properties were estimated to be used as potential vaccine candidates. Altogether, we found four B cell epitopes of K. pneumoniae Fim antigens that are immunogen, antigenic, not similar to human peptides, not allergen and not toxic. Also, they have suitable physiochemical properties to administrate as vaccine, although their complete efficacy should be also shown in vitro and in vivo.

Immunoinformatics and molecular dynamics studies to predict T-cell-specific epitopes of four Klebsiella pneumoniae fimbriae antigens

Klebsiella pneumoniae (K. pneumoniae) is a causative agent of severe infections in humans. There is no publically available vaccine for K. pneumoniae infections yet. Here, using comprehensive immunoinformatics methods, T-cell-specific epitopes of four type 1 fimbriae antigens of K. pneumoniae were predicted and evaluated as potential vaccine candidates. Both CD8+ (class I) and CD4+ (class II) T-cell-specific epitopes were predicted and the epitopes similar to human proteome were excluded. Subsequently, the windows of class-II epitopes containing class-I epitopes were determined. The immunogenicity, IFN-γ production and population coverage were also estimated. Using the 3D structure of HLA and epitopes, molecular docking was carried out. Two best epitopes were selected for molecular dynamics studies. Our prediction and analyses resulted in the several dominant epitopes for each antigen. The docking results showed that all selected epitopes can bind to their restricted HLA molecules with high affinity. The molecular dynamics results indicated the stability of system with minimum possible deviation, suggesting the selected epitopes can be promising candidates for stably binding to HLA molecules. Altogether, our results suggest that the selected T-cell-specific epitopes of K. pneumoniae fimbriae antigens, particularly the two epitopes confirmed by molecular dynamics, can be applied for vaccine development. However, the in vitro and in vivo studies are required to authenticate the results of the present study.Communicated by Ramaswamy H. Sarma.

Designing a novel mRNA vaccine against SARS-CoV-2: An immunoinformatics approach

SARS-CoV-2 is the deadly virus behind COVID-19, the disease that went on to ravage the world and caused the biggest pandemic 21st century has witnessed so far. On the face of ongoing death and destruction, the urgent need for the discovery of a vaccine against the virus is paramount. This study resorted to the emerging discipline of immunoinformatics in order to design a multi-epitope mRNA vaccine against the spike glycoprotein of SARS-CoV-2. Various immunoinformatics tools were utilized to predict T and B lymphocyte epitopes. The epitopes were channeled through a filtering pipeline comprised of antigenicity, toxicity, allergenicity, and cytokine inducibility evaluation with the goal of selecting epitopes capable of generating both T and B cell-mediated immune responses. Molecular docking simulation between the epitopes and their corresponding MHC molecules was carried out. 13 epitopes, a highly immunogenic adjuvant, elements for proper sub-cellular trafficking, a secretion booster, and appropriate linkers were combined for constructing the vaccine. The vaccine was found to be antigenic, almost neutral at physiological pH, non-toxic, non-allergenic, capable of generating a robust immune response and had a decent worldwide population coverage. Based on these parameters, this design can be considered a promising choice for a vaccine against SARS-CoV-2.

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SARS-CoV-2, the causative agent for COVID-19, has caused the biggest pandemic 21st century has witnessed so far.

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Here, immunoinformatics was used for designing a muti-epitope mRNA vaccine against the spike glycoprotein of SARS-CoV-2.

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Through stringent selection of T and B cell epitopes and other necessary elements, a vaccine was constructed in silico.

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Proposed mechanism of its synthesis, delivery and action has also been presented.

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The vaccine was found to be immunogenic, almost neutral, non-toxic, non-allergenic and has a decent worldwide coverage.

Design, synthesis and biological evaluation of novel 2-(5-aryl-1H-imidazol-1-yl) derivatives as potential inhibitors of the HIV-1 Vpu and host BST-2 protein interaction

Novel ethyl 2-(5-aryl-1H-imidazol-1-yl)-acetates 17 and propionates 18, together with their acetic acid 19 and acetohydrazide 20 derivatives, were designed and synthesized using TosMIC chemistry. Biological evaluation of these newly synthesized scaffolds in the HIV-1 Vpu- Host BST-2 ELISA assay identified seven hits (17a, 17b, 17c, 17g, 18a, 20f and 20g) with greater than 50% inhibitory activity. These hits were validated in the HIV-1 Vpu- Host BST-2 AlphaScreen™ and six of the seven compounds were found to have comparable percentage inhibitory activities to those of the ELISA assay. Compounds 17b and 20g, with consistent percentage inhibitory activities across the two assays, had IC₅₀ values of 11.6 ± 1.1 μM and 17.6 ± 0.9 μM in a dose response AlphaScreen™ assay. In a cell-based HIV-1 antiviral assay, compound 17b exhibited an EC₅₀ = 6.3 ± 0.7 μM at non-toxic concentrations (CC₅₀ = 184.5 ± 0.8 μM), whereas compound 20g displayed antiviral activity roughly equivalent to its toxicity (CC₅₀ = 159.5 ± 0.9 μM). This data suggests that compound 17b, active in both cell-based and biochemical assays, provides a good starting point for the design of possible lead compounds for prevention of HIV-1 Vpu and host BST-2 protein binding in new anti-HIV therapeutics.

Interaction of Human Herpesvirus 8 Viral Interleukin-6 with Human Interleukin-6 Receptor Using In Silico Approach: The Potential Role in HHV-8 Pathogenesis

Introduction:

Human Herpesvirus 8 (HHV-8) causes classical, endemic (African), and Acquired Immunodeficiency Syndrome (AIDS)-related Kaposi’s Sarcoma (KS), Body Cavity-Based Primary Effusion Lymphomas (BCBL), HHV-8-associated peritoneal Primary Effusion Lymphoma (PEL), and Multicentric Castleman’s Disease (MCD). HHV8 genome encodes several structural and non-structural proteins, among which vIL6 is a functional homologue of Interleukin-6 (IL-6). It has been established that vIL6 plays a vital role in HHV8 infections; also, it has been suggested that its function was mediated through gp130, rather than the gp80 (IL-6 receptor [IL-6R]). This study aimed to investigate the physicochemical and structural properties as well as the immunological features, and finally the interaction between vIL6 and IL6 receptor (IL6R) by using several bioinformatics tools which could provide both valuable insight into vIL6 protein and advantageous data for further studies on HHV8 inhibitors and new vaccines.

Material and Methods:

vIL6, human IL6 (hIL6), and IL6R were obtained from NCBI GenBank and Uniport, which were aligned by The CLC Genomics Workbench. "Signal-BLAST" and “predisi" were employed to define signal peptide; also, “Expasy’sProtParam” was used to predict physicochemical properties as well as "DiANNA", and "SCRATCH" predicted the disulfide bonds. “NetPhosK”, “DISPHOS”, “NetPhos”, ”NetNGlyc”, and ”GlycoEP” were involved to determine post-modification sites. To define immunoinformatics analysis, “BcePred”, “ABCpred”, “Bepipred”, “AlgPred”, and "VaxiJen" were used. “SOPMA”, “I-TASSER”, “GalaxyRefine”, and “3D-Refine” predicted and refined the secondary and tertiary structures. TM-align server was used to align 3D structures. In addition, docking analysis was done by “Hex 5.0.”, and finally the results were illustrated by “Discovery Studio”.

Results:

A signal peptide (1-22) was defined in the vIL6 sequences and analysis has shown that vIL6 is an acidic protein which is significantly stable in all organisms. Three Disulfide bonds were predicted and immunoinformatics analysis showed 5 distinct B-cell epitopes. vIL6 is predicted as a non-allergen protein and the majority of its structure consists of Alpha helix. TM-align pointed the significant similarity between vIL6 and hIL6 in protein folding. The high energy value between vIL6 protein and IL6R was calculated and further analysis illustrated 5 conserved regions as well as 4 conserved amino acids which had a significant role in vIL6 and IL6R interaction.

Discussion:

An in silico study by numerous software determined the possible interaction between vIL6 and IL6R and the possible role of this interaction in HHV8 pathogenesis and the progress of infection. These have been overlooked by previous studies and will be beneficial to gain a more comprehensive understanding of vIL6 function during HHV8 lifecycle and infections. Structural analysis showed the significant similarity between vIL6 and hIL6 folding which can describe the similarity of the functions or interactions of both proteins. Furthermore, several conserved regions in the interaction site which interestingly were highly conserved among all vIL6 sequences can be used as new target for vIL6 inhibitors. Moreover, our results could predict immunological properties of vIL6 which suggested the ability of this protein in induction of the humoral immune response. Such a protein may be used for further studies on therapeutic vaccine fields.

Novel Chimeric Multiepitope Vaccine for Streptococcosis Disease in Nile Tilapia (Oreochromis niloticus Linn.)

Streptococcus agalactiae is a causative agent of streptococcosis disease in various fish species, including Nile tilapia (Oreochromis niloticus Linn.). Vaccination is an effective disease prevention and control method, but limitations remain for protecting against catastrophic mortality of fish infected with different strains of streptococci. Immunoproteomics analysis of S. agalactiae was used to identify antigenic proteins and construct a chimeric multiepitope vaccine. Epitopes from five antigenic proteins were shuffled in five helices of a flavodoxin backbone, and in silico analysis predicted a suitable RNA and protein structure for protein expression. 45F2 and 42E2 were identified as the best candidates for a chimeric multiepitope vaccine. Recombinant plasmids were constructed to produce a recombinant protein vaccine and DNA vaccine system. Overexpressed proteins were determined to be 30 kDa and 25 kDa in the E. coli and TK1 systems, respectively. The efficacy of the chimeric multiepitope construct as a recombinant protein vaccine and DNA vaccine was evaluated in Nile tilapia, followed by S. agalactiae challenge at 1 × 107 CFU/mL. Relative percentage survival (RPS) and cumulative mortality were recorded at approximately 57-76% and 17-30%, respectively. These chimeric multiepitope vaccines should be applied in streptococcosis disease control and developed into a multivalent vaccine to control multiple diseases.

Designing self-assembled peptide nanovaccine against Streptococcus pneumoniae: An in silico strategy

Streptococcus pneumoniae is the main cause of diseases such as meningitis, pneumoniae and sepsis, especially in children and old people. Due to costly antibiotic treatment, and increasing resistance of pneumococcus, developing high-efficient protective vaccine against this pathogen is an urgent need. Although the pneumoniae polysaccharide vaccine (PPV) and pneumonia conjugate vaccines (PCV) are the efficient pneumococcal vaccine in children and adult groups, but the serotype replacement of S. pneumoniae strains causes the reduction in efficacy of such vaccines. For overcoming the aforesaid drawbacks epitope-based vaccines are introduced as the relevant alternative. In our previous research, the epitope vaccine was designed based on immunodominant epitopes from PspA, CbpA antigens as cellular stimulants and PhtD, PiuA as humoral stimulants. Because the low immunogenicity is the main disadvantage of epitope vaccine, in the current study, we applied coiled-coil self-assembled structures for developing our vaccine. Recently, self-assembled peptide nanoparticles (SAPNs) have gained much attention in the field of vaccine development due to their multivalency, self-adjuvanticity, biocompatibility, and size similarity to pathogen. In this regard, the final designed vaccine is comprised of cytotoxic T lymphocytes (CTL) epitopes from PspA and CbpA, helper T lymphocytes (HTL) epitopes from PhtD and PiuA, the pentamer and trimmer oligomeric domains form 5-stranded and 3-stranded coiled-coils as self-assembled scaffold, Diphtheria toxoids (DTD) as a universal T-helper, which fused to each other with appropriate linkers. The four different arrangements based on the order of above-mentioned compartments were constructed, and each of them were modeled, and validated to find the 3D structure. The structural, physicochemical, and immunoinformatics analyses of final vaccine construct represented that our vaccine could stimulate potent immune response against S. pneumoniae; however, the potency of that should be approved via various in vivo and in vitro immunological tests.

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Stimulating cellular and especially humoral immunities are essential for protection against Streptococcus Pneumoniae.

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Immunodominant epitopes were selected from highly protective antigens of S. pneumoniae: PspA, CbpA, PiuA, PhtD.

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In order to bypass the low immunogenicity of epitope-based peptide vaccine the self-assembled motifs, coiled-coil structure, was applied as the vaccine scaffold.

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The structural, physicochemical, and immunoinformatics results indicate that the designed vaccine can incite strong immune response against S. pneumoniae.

Epitope Prediction by Novel Immunoinformatics Approach: A State-of-the-art Review

Immunoinformatics is a science that helps to create significant immunological information using bioinformatics softwares and applications. One of the most important applications of immunoinformatics is the prediction of a variety of specific epitopes for B cell recognition and T cell through MHC class I and II molecules. This method reduces costs and time compared to laboratory tests. In this state-of-the-art review, we review about 50 papers to find the latest and most used immunoinformatic tools as well as their applications for predicting the viral, bacterial and tumoral structural and linear epitopes of B and T cells. In the clinic, the main application of prediction of epitopes is for designing peptide-based vaccines. Peptide-based vaccines are a considerably potential alternative to low-cost vaccines that may reduce the risks related to the production of common vaccines.

Reverse vaccinology approach to design a novel multi-epitope subunit vaccine against avian influenza A (H7N9) virus

H7N9, a novel strain of avian origin influenza was the first recorded incidence where a human was transited by a N9 type influenza virus. Effective vaccination against influenza A (H7N9) is a major concern, since it has emerged as a life threatening viral pathogen. Here, an in silico reverse vaccinology strategy was adopted to design a unique chimeric subunit vaccine against avian influenza A (H7N9). Induction of humoral and cell-mediated immunity is the prime concerned characteristics for a peptide vaccine candidate, hence both T cell and B cell immunity of viral proteins were screened. Antigenicity testing, transmembrane topology screening, allergenicity and toxicity assessment, population coverage analysis and molecular docking approach were adopted to generate the most antigenic epitopes of avian influenza A (H7N9) proteome. Further, a novel subunit vaccine was designed by the combination of highly immunogenic epitopes along with suitable adjuvant and linkers. Physicochemical properties and secondary structure of the designed vaccine were assessed to ensure its thermostability, h ydrophilicity, theoretical PI and structural behavior. Homology modeling, refinement and validation of the designed vaccine allowed to construct a three dimensional structure of the predicted vaccine, further employed to molecular docking analysis with different MHC molecules and human immune TLR8 receptor present on lymphocyte cells. Moreover, disulfide engineering was employed to lessen the high mobility region of the designed vaccine in order to extend its stability. Furthermore, we investigated the molecular dynamic simulation of the modeled subunit vaccine and TLR8 complexed molecule to strengthen our prediction. Finally, the suggested vaccine was reverse transcribed and adapted for E. coli strain K12 prior to insertion within pET28a(+) vector for checking translational potency and microbial expression.

Designing of an epitope-based peptide vaccine against walking pneumonia: an immunoinformatics approach

Mycoplasma pneumoniae is a substantial respiratory pathogen that develops not only pneumonia but also other respiratory diseases, which mimic viral respiratory syndromes. Nevertheless, vaccine development for this pathogen delays behind as immunity correlated with protection is now predominantly unknown. In the present study, an immunoinformatics pipeline is utilized for epitope-based peptide vaccine design, which can trigger a critical immune response against M. pneumoniae. A total of 105 T-cell epitopes from 12 membrane associated proteins and 7 T-cell epitopes from 5 cytadherence proteins of M. pneumoniae were obtained and validated. Thus, 18 peptides with 9-mer core sequence were identified as best T-cell epitopes by considering the number of residues with > 75% in favored region. Further, the crucial screening studies predicted three peptides with good binding affinity towards HLA molecules as best T-cell and B-cell epitopes. Based on this result, visualization, and dynamic simulation for the three epitopes (WIHGLILLF, VILLFLLLF, and LLAWMLVLF) were assessed. The predicted epitopes needs to be further validated for their adept use as vaccine. Collectively, the study opens up a new horizon with extensive therapeutic application against M. pneumoniae and its associated diseases.

Immunoinformatics-aided design of a potential multi-epitope peptide vaccine against Leishmania infantum

Visceral leishmaniasis (VL) or kala-azar, the most severe form of the disease, is endemic in more than eighty countries across the world. To date, there is no approved vaccine against VL in the market. Recent advances in reverse vaccinology could be promising approach in designing the efficient vaccine for VL treatment. In this study, an efficient multi-epitope vaccine against Leishmania infantum, the causative agent of VL, was designed using various computational vaccinology methods. Potential immunodominant epitopes were selected from four antigenic proteins, including histone H1, sterol 24-c-methyltransferase (SMT), Leishmania-specific hypothetical protein (LiHy), and Leishmania-specific antigenic protein (LSAP). To enhance vaccine immunogenicity, two resuscitation-promoting factor of Mycobacterium tuberculosis, RpfE and RpfB, were employed as adjuvants. All the aforesaid segments were joined using proper linkers. Homology modeling, followed by refinement and validation was performed to obtain a high-quality 3D structure of designed vaccine. Docking analyses and molecular dynamics (MD) studies indicated vaccine/TLR4 complex was in the stable form during simulation time. In sum, we expect our designed vaccine is able to induce humoral and cellular immune responses against L. infantum, and may be promising medication for VL, after in vitro and in vivo immunological assays.

Proteome-scale identification of Leishmania infantum for novel vaccine candidates: A hierarchical subtractive approach

Vaccines are one of the most significant achievements in medical science. However, vaccine design is still challenging at all stages. The selection of antigenic peptides as vaccine candidates is the first and most important step for vaccine design. Experimental selection of antigenic peptides for the design of vaccines is a time-consuming, labor-intensive and expensive procedure. More recently, in the light of computer-aided biotechnology and reverse vaccinology, the precise selection of antigenic peptides and rational vaccine design against many pathogens have developed. In this study, the whole proteome of Leishmania infantum was analyzed using a pipeline of algorithms. From the set of 8045 proteins of L. infantum, sixteen novel antigenic proteins were derived using a hierarchical proteome subtractive analysis. These novel vaccine targets can be utilized as top candidates for designing the new prophylactic or therapeutic vaccines against visceral leishmaniasis. Significantly, all the sixteen novel vaccine candidates are non-allergen antigenic proteins that have not been used for the design of vaccines against visceral leishmaniasis until now.

Harnessing self-assembled peptide nanoparticles in epitope vaccine design

Vaccination has been one of the most successful breakthroughs in medical history. In recent years, epitope-based subunit vaccines have been introduced as a safer alternative to traditional vaccines. However, they suffer from limited immunogenicity. Nanotechnology has shown value in solving this issue. Different kinds of nanovaccines have been employed, among which virus-like nanoparticles (VLPs) and self-assembled peptide nanoparticles (SAPNs) seem very promising. Recently, SAPNs have attracted special interest due to their unique properties, including molecular specificity, biodegradability, and biocompatibility. They also resemble pathogens in terms of their size. Their multivalency allows an orderly repetitive display of antigens on their surface, which induces a stronger immune response than single immunogens. In vaccine design, SAPN self-adjuvanticity is regarded an outstanding advantage, since the use of toxic adjuvants is no longer required. SAPNs are usually composed of helical or β-sheet secondary structures and are tailored from natural peptides or de novo structures. Flexibility in subunit selection opens the door to a wide variety of molecules with different characteristics. SAPN engineering is an emerging area, and more novel structures are expected to be generated in the future, particularly with the rapid progress in related computational tools. The aim of this review is to provide a state-of-the-art overview of self-assembled peptide nanoparticles and their use in vaccine design in recent studies. Additionally, principles for their design and the application of computational approaches to vaccine design are summarized.

Virtual Screening for Potential Inhibitors of CTX-M-15 Protein of Klebsiella pneumoniae

The Gram-negative bacterium Klebsiella pneumoniae, responsible for a wide variety of nosocomial infections in immuno-deficient patients, involves the respiratory, urinary and gastrointestinal tract infections and septicemia. Extended spectrum β-lactamases (ESBL) belong to β-lactamases capable of conferring antibiotic resistance in Gram-negative bacteria. CTX-M-15, a prevalent ESBL reported from Enterobacteriaceae including K. pneumoniae, was selected as a potent anti-bacterial target. To identify the novel drug-like compounds, structure-based screening procedure was employed against downloaded drug-like compounds from ZINC database. An acronym for "ZINC" is not commercial. The docking free energy values were investigated and compared to the known inhibitor Avibactam. Six best novel drug-like compounds were selected and their hydrogen bindings with the receptor were determined. Based on the binding efficiency mode, three among these six identified most potential inhibitors, ZINC21811621, ZINC93091917 and ZINC19488569, were predicted as potential competitive inhibitors against CTX-M-15 compared to Avibactam. These three inhibitors may provide a framework for the experimental studies to develop anti-Klebsiella novel drug candidates targeting CTX-M-15.

In Silico Analysis of Glutaminase from Different Species of Escherichia and Bacillus

BACKGROUND

Glutaminase (EC 3.5.1.2) catalyzes the hydrolytic degradation of L-glutamine to L-glutamic acid and has been introduced for cancer therapy in recent years. The present study was an in silico analysis of glutaminase to further elucidate its structure and physicochemical properties.

METHODS

Forty glutaminase protein sequences from different species of Escherichia and Bacillus obtained from the UniProt Protein Database were characterized for homology search, physiochemical properties, phylogenetic tree construction, motif, superfamily search, and multiple sequence alignment.

RESULTS

The sequence level homology was obtained among different groups of glutaminase enzymes, which belonged to superfamily serine-dependent β-lactamases and penicillin-binding proteins. The phylogenetic tree constructed indicated 2 main clusters for the glutaminases. The distribution of common β-lactamase motifs was also observed; however, various non-common motifs were also observed.

CONCLUSION

Our results showed that the existence of a conserved motif with a signature amino-acid sequence of β-lactamases could be considered for the genetic engineering of glutaminases in view of their potential application in cancer therapy. Nonetheless, further research is needed to improve the stability of glutaminases and decrease their immunogenicity in both medical and food industrial applications.