Designing an efficient multi-epitope peptide vaccine against Vibrio cholerae via combined immunoinformatics and protein interaction based approaches

Exploring dengue proteome to design an effective epitope-based vaccine against dengue virus

Dengue, a mosquito-borne disease, is caused by four known dengue serotypes. This infection causes a range of symptoms from a mild fever to a sever homorganic fever and death. It is a serious public health problem in subtropical and tropical countries. There is no specific vaccine currently available for clinical use and study on this issue is ongoing. In this study, bioinformatics approaches were used to predict antigenic, immunogenic, non-allergenic, and conserved B and T-cell epitopes as promising targets to design an effective peptide-based vaccine against dengue virus. Molecular docking analysis indicated the deep binding of the identified epitopes in the binding groove of the most popular human MHC I allele (human leukocyte antigens [HLA] A*0201). The final vaccine construct was created by conjugating the B and T-cell identified epitopes using proper linkers and adding an appropriate adjuvant at the N-terminal. The characteristics of the new subunit vaccine demonstrated that the epitope-based vaccine was antigenic, non-toxic, stable, and soluble. Other physicochemical properties of the new designed construct including isoelectric point value, aliphatic index, and grand average of hydropathicity were biologically considerable. Molecular docking of the engineered vaccine with Toll-like receptor 2 (TLR2) model revealed the hydrophobic interaction between the adjuvant and the ligand binding regions in the hydrophobic channel of TLR2. The study results indicated the high potential capability of the new multi-epitope vaccine to induce cellular and humoral immune responses against the dengue virus. Further experimental tests are required to investigate the immune protection capacity of the new vaccine construct in animal models. Communicated by Ramaswamy H. Sarma.

Immuno-informatics based approaches to design a novel multi epitope-based vaccine for immune response reinforcement against Leptospirosis

Leptospirosis is known as a zoonotic disease of global importance originated from infection with the spirochete bacterium Leptospira. Although several leptospirosis vaccines have been tested, the vaccination is relatively unsuccessful in clinical application despite decades of research. Therefore, this study was conducted to construct a novel multi-epitope based vaccine against leptospirosis by using Hap1, LigA, LAg42, SphH and HSP58 antigens. T cell and IFN gamma epitopes were predicted from these antigens. In addition, to induce strong CD4⁺ helper T lymphocytes (HTLs) responses, Pan HLA DR-binding epitope (PADRE) and helper epitopes selected from Tetanus toxin fragment C (TTFrC) were applied. Moreover, for boosting immune response, Heparin-Binding Hemagglutinin (HBHA), a novel TLR4 agonist was added to the construct as an adjuvant. Finally, selected epitopes were linked together using EAAAK, GPGPG, AAY and HEYGAEALERAG linkers. Based on the predicted epitopes, a multi-epitope vaccine was construct with 490 amino acids. Physico-chemical properties, secondary and tertiary structures, stability, intrinsic protein disorder, solubility, and allergenicity of this vaccine construct were assessed by applying immunoinformatics analyses. A soluble, and non-allergic protein with a molecular weight of 53.476 kDa was obtained. Further analyses validated the stability of the chimeric protein and the predicted epitopes in the chimeric vaccine indicated strong potential to induce B-cell and T-cell mediated immune response. Therefore, immunoinformatics analysis showed that the modeled multi-epitope vaccine can properly stimulate the both T and B cells immune responses and could potentially be used for prophylactic or therapeutic usages.

Decreasing the immunogenicity of arginine deiminase enzyme via structure-based computational analysis

The clinical applications of therapeutic enzymes are often limited due to their immunogenicity. B-cell epitope removal is an effective approach to solve this obstacle. The identification of hot spot epitopic residues is a critical step in the removal of protein B-cell epitope. Hereof, computational approaches are a suitable alternative to costly and labor-intensive experimental approaches. Arginine deiminase, a Mycoplasma arginine-catabolizing enzyme, is in the clinical trial for treating arginine auxotrophic cancers, especially hepatocellular carcinomas and melanomas through depleting plasma arginine and causing cell starvation. In this study, arginine deiminase from Mycoplasma hominis (MhADI) was computationally analyzed for recognizing and locating its immune-reactive regions. The 3D structure of the bioactive form of MhADI was modeled. The B-cell epitope mapping of protein was performed using various servers with different algorithms. Six segments: 31-40, 48-55, 131-140, 196-206, 294-314, and 331-344 were predicted to be the consensus immunogenic regions. The modification of epitopic hot spot residue was performed to reduce immune-reactiveness. The hot spot residue was selected considering a high B-cell epitope score, convexity index, surface accessibility, flexibility, and hydrophilicity. The structure stability of native and mutant proteins was evaluated through molecular dynamics simulation. The E304L mutein was suggested as a lower antigenic and stable enzyme derivative.

Deep analysis of N-cadherin/ADH-1 interaction: a computational survey

Due to the considerable role of N-cadherin in cancer metastasis, tumor growth, and progression, inhibition of this protein has been highly regarded in recent years. Although ADH-1 has been known as an appropriate inhibitor of N-cadherin in clinical trials, its chemical nature and binding mode with N-cadherin have not been precisely specified yet. Accordingly, in this study, quantum mechanics calculations were used to investigate the chemical nature of ADH-1. These calculations clarify the molecular properties of ADH-1 and determine its reactive sites. Based on the results, the oxygen atoms are suitable for electrophilic reactivity, while the hydrogen atoms that are connected to nitrogen atoms are the favorite sites for nucleophilic reactivity. The higher electronegativity of the oxygen atoms makes them the most reactive portions in this molecule. Molecular docking and molecular dynamics (MD) simulation have also been applied to specify the binding mode of ADH-1 with N-cadherin and determine the important residues of N-cadherin involving in the interaction with ADH-1. Moreover, the verified model by MD simulation has been studied to extract the free energy value and find driving forces. These calculations and molecular electrostatic potential map of ADH-1 indicated that hydrophobic and electrostatic interactions are almost equally involved in the implantation of ADH-1 in the N-cadherin binding site. The presented results not only enable a closer examination of N-cadherin in complex with ADH-1 molecule, but also are very beneficial in designing new inhibitors for N-cadherin and can help to save time and cost in this field.

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.

A novel in silico minigene vaccine based on CD4+ T-helper and B-cell epitopes of EG95 isolates for vaccination against cystic echinococcosis

EG95 oncospheral antigen plays a crucial role in Echinococcus granulosus pathogenicity. Considering the diversity of antigen among different EG95 isolates, it seems to be an ideal antigen for designing a universal multivalent minigene vaccine, so-called multi-epitope vaccine. This is the first in silico study to design a construct for the development of global EG95-based hydatid vaccine against E. granulosus in intermediate hosts. After antigen sequence selection, the three-dimensional structure of EG95 was modeled and multilaterally validated. The preliminary parameters for B-cell epitope prediction were implemented such as the possible transmembrane helix, signal peptide, post-translational modifications and allergenicity. The high ranked linear and conformational B-cell epitopes derived from several online web-servers (e.g., ElliPro, BepiPred v1.0, BcePred, ABCpred, SVMTrip, IEDB algorithms, SEPPA v2.0 and Discotope v2.0) were utilized for multiple sequence alignment and then for engineering the vaccine construct. T-helper based epitopes were predicted by molecular docking between the high frequent ovar class II allele (Ovar-DRB1*1202) and hexadecamer fragments of the EG95 protein. Having used the immune-informatics tools, we formulated the first EG95-based minigene vaccine based on T-helper epitope with high-binding affinity to the ovar MHC allele. This designed construct was analyzed for different physicochemical properties. It was also codon-optimized for high-level expression in Escherichia coli k12. Taken all, we propose the present in silico vaccine constructs as a promising platform for the generation of broadly protective vaccines for species and genus-specific immunization of the natural hosts of the parasite.

Identification of potential antigens from non-classically secreted proteins and designing novel multitope peptide vaccine candidate against Brucella melitensis through reverse vaccinology and immunoinformatics approach

Brucella melitensis is an intracellular pathogen resides in the professional and non-professional phagocytes of the host, causing zoonotic disease brucellosis. The stealthy nature of the Brucella makes it's highly pathogenic, and it is hard to eliminate the bacteria completely from the infected host. Hitherto, no licensed vaccines are available for human brucellosis. In this study, we identified potential antigens for vaccine development from non-classically secreted proteins through reverse vaccinology approach. Based on the systemic screening of non-classically secreted proteins of B. melitensis 16M, we identified nine proteins as potential vaccine candidates. Among these, Omp31 and Omp22 are known immunogens, and its role in the virulence of Brucella is known. Roles of other proteins in the pathogenesis are yet to be studied. From the nine proteins, we identified six novel antigenic epitopes that can elicit both B-cell and T-cell immune responses. Among the nine proteins, the epitopes were predicted from Omp31 immunogenic protein precursor, Omp22 protein precursor, extracellular serine protease, hypothetical membrane-associated protein, iron-regulated outer membrane protein FrpB. Further, we designed a multitope vaccine using Omp31 immunogenic protein precursor, Omp22 protein precursor, extra cellular serine protease, iron-regulated outer membrane protein FrpB, hypothetical membrane-associated protein, and LPS-assembly protein LptD and polysaccharide export protein identified in the previous study. Epitopes were joined using amino acid linkers such as EAAAK and GPGPG. Cholera toxin subunit B, the nontoxic part of cholera toxin, was used as an adjuvant and it was linked to the N-terminal of the multitope vaccine candidate. The designed vaccine candidate was modeled, validated and the physicochemical properties were analyzed. Results revealed that the vaccine candidate is soluble, stable, non-allergenic, antigenic and 87% of residues of the designed vaccine candidate is located in the favored region. In conclusion, the computational analysis showed that the newly designed multitope protein could be used to develop a promising vaccine for human brucellosis.

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.

Designing an efficient multi-epitope oral vaccine against Helicobacter pylori using immunoinformatics and structural vaccinology approaches

Helicobacter pylori is the cunning bacterium that can live in the stomachs of many people without any symptoms, but gradually can lead to gastric cancer. Due to various obstacles, which are related to anti-H. pylori antibiotic therapy, recently developing an anti-H. pylori vaccine has attracted more attention. In this study, different immunoinformatics and computational vaccinology approaches were employed to design an efficient multi-epitope oral vaccine against H. pylori. Our multi-epitope vaccine is composed of heat labile enterotoxin IIc B (LT-IIc) that is used as a mucosal adjuvant to enhance vaccine immunogenicity for oral immunization, cartilage oligomeric matrix protein (COMP) to increase vaccine stability in acidic pH of gut, one experimentally protective antigen, OipA, and two hypothetical protective antigens, HP0487 and HP0906, and "CTGKSC" peptide motif that target epithelial microfold cells (M cells) to enhance vaccine uptake from the gut barrier. All the aforesaid segments were joined to each other by proper linkers. The vaccine construct was modeled, validated, and refined by different programs to achieve a high-quality 3D structure. The resulting high-quality model was applied for conformational B-cell epitopes selection and docking analyses with a toll-like receptor 2 (TLR2). Moreover, molecular dynamics studies demonstrated that the protein-TLR2 docked model was stable during simulation time. We believe that our vaccine candidate can induce mucosal sIgA and IgG antibodies, and Th1/Th2/Th17-mediated protective immunity that are crucial for eradicating H. pylori infection. In sum, the computational results suggest that our newly designed vaccine could serve as a promising anti-H. pylori vaccine candidate.

Development of a multi-epitope peptide vaccine inducing robust T cell responses against brucellosis using immunoinformatics based approaches

Current investigations have demonstrated that a multi-epitope peptide vaccine targeting multiple antigens could be considered as an ideal approach for prevention and treatment of brucellosis. According to the latest findings, the most effective immunogenic antigens of brucella to induce immune responses are included Omp31, BP26, BLS, DnaK and L7-L12. Therefore, in the present study, an in silico approach was used to design a novel multi-epitope vaccine to elicit a desirable immune response against brucellosis. First, five novel T-cell epitopes were selected from Omp31, BP26, BLS, DnaK and L7-L12 proteins using different servers. In addition, helper epitopes selected from Tetanus toxin fragment C (TTFrC) were applied to induce CD4+ helper T lymphocytes (HTLs) responses. Selected epitopes were fused together by GPGPG linkers to facilitate the immune processing and epitope presentation. Moreover, cholera toxin B (CTB) was linked to N terminal of vaccine construct as an adjuvant by using EAAAK linker. A multi-epitope vaccine was designed based on predicted epitopes which was 377 amino acid residues in length. Then, the physico-chemical properties, secondary and tertiary structures, stability, intrinsic protein disorder, solubility and allergenicity of this multi-epitope vaccine were assessed using immunoinformatics tools and servers. Based on obtained results, a soluble, and non-allergic protein with 40.59kDa molecular weight was constructed. Expasy ProtParam classified this chimeric protein as a stable protein and also 89.8% residues of constructed vaccine were located in favored regions of the Ramachandran plot. Furthermore, this multi-epitope peptide vaccine was able to strongly induce T cell and B-cell mediated immune responses. In conclusion, immunoinformatics analysis indicated that this multi-epitope peptide vaccine can be effectively expressed and potentially be used for prophylactic or therapeutic usages against brucellosis.