A Targeted LC‐MS Strategy for Low‐Abundant HLA Class‐I‐Presented Peptide Detection Identifies Novel Human Papillomavirus T‐Cell Epitopes

For rational design of therapeutic vaccines, detailed knowledge about target epitopes that are endogenously processed and truly presented on infected or transformed cells is essential. Many potential target epitopes (viral or mutation‐derived), are presented at low abundance. Therefore, direct detection of these peptides remains a challenge. This study presents a method for the isolation and LC‐MS³‐based targeted detection of low‐abundant human leukocyte antigen (HLA) class‐I‐presented peptides from transformed cells. Human papillomavirus (HPV) was used as a model system, as the HPV oncoproteins E6 and E7 are attractive therapeutic vaccination targets and expressed in all transformed cells, but present at low abundance due to viral immune evasion mechanisms. The presented approach included preselection of target antigen‐derived peptides by in silico predictions and in vitro binding assays. The peptide purification process was tailored to minimize contaminants after immunoprecipitation of HLA‐peptide complexes, while keeping high isolation yields of low‐abundant target peptides. The subsequent targeted LC‐MS³ detection allowed for increased sensitivity, which resulted in successful detection of the known HLA‐A2‐restricted epitope E7_11–19 and ten additional E7‐derived peptides on the surface of HPV16‐transformed cells. T‐cell reactivity was shown for all the 11 detected peptides in ELISpot assays, which shows that detection by our approach has high predictive value for immunogenicity. The presented strategy is suitable for validating even low‐abundant candidate epitopes to be true immunotherapy targets.     

Peptide epitope identification by affinity selection on bacteriophage MS2 virus-like particles

Filamentous phages are now the most widely used vehicles for phage display and provide efficient means for epitope identification. However, the peptides they display are not very immunogenic because they normally fail to present foreign epitopes at the very high densities required for efficient B-cell activation. Meanwhile, systems based on virus-like particles (VLPs) permit the engineered high-density display of specific epitopes but are incapable of peptide library display and affinity selection. We developed a new peptide display platform based on VLPs of the RNA bacteriophage MS2. It combines the high immunogenicity of MS2 VLPs with the affinity selection capabilities of other phage display systems. Here, we describe plasmid vectors that facilitate the construction of high-complexity random sequence peptide libraries on MS2 VLPs and that allow control of the stringency of affinity selection through the manipulation of display valency. We used the system to identify epitopes for several previously characterized monoclonal antibody targets and showed that the VLPs thus obtained elicit antibodies in mice whose activities mimic those of the selecting antibodies.     

De novo design of peptide immunogens that mimic the coiled coil region of human T-cell leukemia virus type-1 glycoprotein 21 transmembrane subunit for induction of native protein reactive neutralizing antibodies

Peptide vaccines able to induce high affinity and protective neutralizing antibodies must rely in part on the design of antigenic epitopes that mimic the three-dimensional structure of the corresponding region in the native protein. We describe the design, structural characterization, immunogenicity, and neutralizing potential of antibodies elicited by conformational peptides derived from the human T-cell leukemia virus type 1 (HTLV-1) gp21 envelope glycoprotein spanning residues 347-374. We used a novel template design and a unique synthetic approach to construct two peptides (WCCR2T and CCR2T) that would each assemble into a triple helical coiled coil conformation mimicking the gp21 crystal structure. The peptide B-cell epitopes were grafted onto the epsilon side chains of three lysyl residues on a template backbone construct consisting of the sequence acetyl-XGKGKGKGCONH2 (where X represents the tetanus toxoid promiscuous T cell epitope (TT) sequence 580-599). Leucine substitutions were introduced at the a and d positions of the CCR2T sequence to maximize helical character and stability as shown by circular dichroism and guanidinium hydrochloride studies. Serum from an HTLV-1-infected patient was able to recognize the selected epitopes by enzyme-linked immunosorbent assay (ELISA). Mice immunized with the wild-type sequence (WCCR2T) and the mutant sequence (CCR2T) elicited high antibody titers that were capable of recognizing the native protein as shown by flow cytometry and whole virus ELISA. Sera and purified antibodies from immunized mice were able to reduce the formation of syncytia induced by the envelope glycoprotein of HTLV-1, suggesting that antibodies directed against the coiled coil region of gp21 are capable of disrupting cell-cell fusion. Our results indicate that these peptides represent potential candidates for use in a peptide vaccine against HTLV-1.     

In silico proteomic characterization of human epidermal growth factor receptor 2 (HER-2) for the mapping of high affinity antigenic determinants against breast cancer

Multiple different approaches are being used to activate the immune system against breast cancer. Vaccine therapy in general follows the principle that injections of various substances ultimately result in the presentation of tumor peptides to the patient’s immune system. We proposed a potential in silico DNA vaccine against breast cancer by integrating high affinity T cell (MHC-I and MHC-II) and B cell (continuous and discontinuous) epitopes. The matching of the HLA haplotype and antigen was performed to provide the appropriate peptide epitope suitable for majority of the patients. The immunogenic nature of the antigenic construct was also enhanced by the administration of consensus epitopes. The potency of DNA vaccines depends on the efficient expression and presentation of the encoded antigen of interest and the chances of efficient expression of our antigenic construct in host organism was also verified by in silico approaches. An attempt was made to overcome the limited potency of the DNA vaccine by targeting DNA to professional antigen-presenting cells (APCs). A higher immune response theoretically corresponds to a higher survival rate of patients. Therefore, optimization studies were also employed to enhance the immunogenicity of proposed in silico DNA vaccine.     

Bioinformatics tools for identifying class I-restricted epitopes

The lack of simple methods to identify relevant T-cell epitopes, the high mutation rate of many pathogens, and restriction of T-cell response to epitopes due to human lymphocyte antigen (HLA) polymorphism have significantly hindered the development of cytotoxic T-lymphocyte (CTL) epitope-based or "epitope-driven" vaccines. Previously, CTL epitopes were mapped using large arrays of overlapping synthetic peptides. The large number of protein sequences available for mapping is now making this method prohibitively expensive and time-consuming. Bioinformatics tools such as EpiMatrix and Conservatrix, which search for unique or multi-HLA-restricted (promiscuous) T-cell epitopes and identify epitopes that are conserved across variant strains of the same pathogen, accelerate epitope mapping. These tools offer a significant advantage over other methods of epitope selection because high-throughput screening can be performed in silico, followed by confirmatory studies in vitro. CTL epitopes discovered using these tools might be used to develop novel vaccines and therapeutics for the prevention and treatment of infectious diseases such as human immunodeficiency virus, hepatitis C, tuberculosis, and some cancers.     

In silico prediction of immunogenic T cell epitopes for HLA-DQ8

Background HLA-DQ alleles are involved in the pathogenesis of hypersensitivity reactions, with HLA-DQ8 associated with several human autoimmune disorders. Limited success has been achieved using sequence-based computational techniques for predicting HLA-DQ8-restricted T cell epitopes while accuracy and efficiency of recently developed structure-based models need to be improved. Results We describe a combined structure-based prediction approach for DQ8-restricted T cell epitope prediction using a recently developed fast and accurate docking protocol, pDOCK, and molecular surface electrostatic potential (MSEP)-based clustering of pMHC binding interfaces. The prediction model was rigorously trained, tested and validated using experimentally verified DQ8 binding and non-binding peptides. High prediction accuracy (average area under the ROC curve, average AROC>0.94) is validated against experimental data. Our model also predicts all binding registers correctly and known T cell activators with 77% accuracy. We also studied the patterns of DQ8-binding peptides and reassure the existence of epitopes not conforming to binding motifs. Conclusions We have developed a model that can be successfully applied as a generic protocol for easy in silico identification of potential immunogenic T cell epitopes. The current model is therefore applicable for screening vaccine candidates irrespective of sequence motifs. We have also illustrated efficient discrimination of different categories of binders from non-binders as well as different categories of pMHC agonists from non-agonists, while accurately predicting the binding registers of DQ8-restricted peptides. This combined approach provides a set of sensitive and specific computational tools to facilitate high-throughput screening of peptides for immunotherapeutic applications such as controlling allergic and autoimmune responses.     

IMPARO: inferring microbial interactions through parameter optimisation

Type 2 diabetes mellitus (T2DM) is a worldwide disease that have an impact on individuals of all ages causing micro and macro vascular impairments due to hyperglycemic internal environment. For ultimate treatment to cure T2DM, association of diabetes with immune components provides a strong basis for immunotherapies and vaccines developments that could stimulate the immune cells to minimize the insulin resistance and initiate gluconeogenesis through an insulin independent route. Immunoinformatics based approach was used to design a polyvalent vaccine for T2DM that involved data accession, antigenicity analysis, T-cell epitopes prediction, conservation and proteasomal evaluation, functional annotation, interactomic and in silico binding affinity analysis. We found the binding affinity of antigenic peptides with major histocompatibility complex (MHC) Class-I molecules for immune activation to control T2DM. We found 13-epitopes of 9 amino acid residues for multiple alleles of MHC class-I bears significant binding affinity. The downstream signaling resulted by T-cell activation is directly regulated by the molecular weight, amino acid properties and affinity of these epitopes. Each epitope has important percentile rank with significant ANN IC50 values. These high score potential epitopes were linked using AAY, EAAAK linkers and HBHA adjuvant to generate T-cell polyvalent vaccine with a molecular weight of 35.6 kDa containing 322 amino acids residues. In silico analysis of polyvalent construct showed the significant binding affinity (− 15.34 Kcal/mol) with MHC Class-I. This interaction would help to understand our hypothesis, potential activation of T-cells and stimulatory factor of cytokines and GLUT1 receptors. Our system-level immunoinformatics approach is suitable for designing potential polyvalent therapeutic vaccine candidates for T2DM by reducing hyperglycemia and enhancing metabolic activities through the immune system.     

Purification of polyclonal anti-conformational antibodies for use in affinity selection from random peptide phage display libraries: A study using the hydatid vaccine EG95

The use of polyclonal antibodies to screen random peptide phage display libraries often results in the recognition of a large number of peptides that mimic linear epitopes on various proteins. There appears to be a bias in the use of this technology toward the selection of peptides that mimic linear epitopes. In many circumstances the correct folding of a protein immunogen is required for conferring protection. The use of random peptide phage display libraries to identify peptide mimics of conformational epitopes in these cases requires a strategy for overcoming this bias. Conformational epitopes on the hydatid vaccine EG95 have been shown to result in protective immunity in sheep, whereas linear epitopes are not protective. In this paper we describe a strategy that results in the purification of polyclonal antibodies directed against conformational epitopes while eliminating antibodies directed against linear epitopes. These affinity purified antibodies were then used to select a peptide from a random peptide phage display library that has the capacity to mimic conformational epitopes on EG95. This peptide was subsequently used to affinity purify monospecific antibodies against EG95.     

Immunogenicity of peptide-vaccine candidates predicted by molecular dynamics simulations

We present an in silico, structure-based approach for design and evaluation of conformationally restricted peptide-vaccines. In particular, we designed four cyclic peptides of ten or 11 residues mimicking the crystallographically observed beta-turn conformation of a predicted immunodominant loop of PorA from Neisseria meningitidis. Conformational correctness and stability of the peptide designs, as evaluated by molecular dynamics simulations, correctly predicted the immunogenicity of the peptides. We observed a peptide-induced functional antibody response that, remarkably, exceeded the response induced by the native protein in outer membrane vesicles, without losing specificity for related strains. The presented approach offers tools for a priori design and selection of peptide-vaccine candidates with full biological activity. This approach could be widely applicable: to outer membrane proteins of Gram-negative bacteria, and to other epitopes in a large range of pathogens.     

Application of a novel design paradigm to generate general nonpeptide combinatorial scaffolds mimicking beta turns: synthesis of ligands for somatostatin receptors

Nonpeptide compounds that mimic bioactive peptides are desirable for a number of clinical indications. We report a new practical method for the design of scaffolds exhibiting drug-like properties that are suitable for the display of peptide pharmacophores. The synthesis of various synthons of 7'-hydroxy-2',3'-dihydro-1'H,2H,5H-spiro[imidazolidine-4,4'-quinoline]-2,5-dione (1) and methods for the introduction of several mimics of amino acid side-chains are described. This method is exemplified by derivatives that show agonist activity for the somatostatin type 2 receptor.     

T cell epitope identification for bovine vaccines: an epitope mapping method for BoLA A-11

T cell responses play an important role in immunity to parasites and other microbial agents of infectious diseases, therefore a number of T cell-directed vaccines are in development. Computer-driven algorithms that facilitate the discovery of T cell epitopes from protein and genome sequences are now being used to accelerate preclinical studies of human vaccines. Similar tools are not yet available for predicting T cell epitopes for animal vaccines, but there may be sufficient data available to begin the process of compiling the algorithms. We describe the construction of a novel mathematical 'matrix' that describes the properties of bovine major histocompatibility complex (BoLA) system antigen (BoLA) A-11 peptide ligands, developed for use with EpiMatrix, an existing T cell epitope-mapping algorithm. An alternative means of developing BoLA matrices, using the pocket profile method, is also discussed. Matrices such as the one described here may be used to develop T cell epitope-mapping tools for cattle and other ruminants. Epitope-mapping algorithms offer a significant advantage over other methods of epitope selection, such as the screening of synthetic overlapping peptides, because high throughput screening can be performed in silico, followed by ex vivo confirmatory studies. Furthermore, using epitope-mapping algorithms, putative T cell epitopes can be derived directly from genomic sequences, allowing researchers to circumvent labor-intensive cloning steps in the genome-to-vaccine discovery pathway.     

Rational design of complementary peptides to the betaAmyloid 29-42 fusion peptide: an application of PepDesign

Peptides in solution currently exist under several conformations; an equilibrium which varies with solvent polarity. Despite or because of this structure versatility, peptides can be selective biological tools: they can adapt to a target, vary conformation with solvents and so on. These capacities are crucial for cargo carriers. One promising way of using peptides in biotechnologies is to decipher their medium-sequence-structure-function relationships and one approach is molecular modelling. Only few "in silico" methods of peptide design are described in the literature. Most are used in support of experimental screening of peptide libraries. However, the way they are made does not teach us much for future researches. In this paper, we describe an "in silico" method (PepDesign) which starts by analysing the native interaction of a peptide with a target molecule in order to define which points are important. From there, a modelling protocol for the design of 'better' peptides is set. The PepDesign procedure calculates new peptides fulfilling the hypothesis, tests the conformational space of these peptides in interaction with the target by angular dynamics and goes up to the selection of the best peptide based on the analysis of complex structure properties. Experimental biological assays are finally used to test the selected peptides, hence to validate the approach. Applications of PepDesign are wide because the procedure will remain similar irrespective of the target which can be a protein, a drug or a nucleic acid. In this paper, we describe the design of peptides which binds to the fusogenic helical form of the C-terminal domain of the Abeta peptide (Abeta29-42).     

In silico prediction of peptides binding to multiple HLA-DR molecules accurately identifies immunodominant epitopes from gp43 of Paracoccidioides brasiliensis frequently recognized in primary peripheral blood mononuclear cell responses from sensitized individuals

One of the major drawbacks limiting the use of synthetic peptide vaccines in genetically distinct populations is the fact that different epitopes are recognized by T cells from individuals displaying distinct major histocompatibility complex molecules. Immunization of mice with peptide (181-195) from the immunodominant 43 kDa glycoprotein of Paracoccidioides brasiliensis (gp43), the causative agent of Paracoccidioidomycosis (PCM), conferred protection against infectious challenge by the fungus. To identify immunodominant and potentially protective human T-cell epitopes in gp43, we used the TEPITOPE algorithm to select peptide sequences that would most likely bind multiple HLA-DR molecules and tested their recognition by T cells from sensitized individuals. The 5 most promiscuous peptides were selected from the gp43 sequence and the actual promiscuity of HLA binding was assessed by direct binding assays to 9 prevalent HLA-DR molecules. Synthetic peptides were tested in proliferation assays with peripheral blood mononuclear cells (PBMC) from PCM patients after chemotherapy and healthy controls. PBMC from 14 of 19 patients recognized at least one of the promiscuous peptides, whereas none of the healthy controls recognized the gp43 promiscuous peptides. Peptide gp43(180-194) was recognized by 53% of patients, whereas the other promiscuous gp43 peptides were recognized by 32% to 47% of patients. The frequency of peptide binding and peptide recognition correlated with the promiscuity of HLA-DR binding, as determined by TEPITOPE analysis. In silico prediction of promiscuous epitopes led to the identification of naturally immunodominant epitopes recognized by PBMC from a significant proportion of a genetically heterogeneous patient population exposed to P. brasiliensis. The combination of several such epitopes may increase the frequency of positive responses and allow the immunization of genetically distinct populations.     

ADAM-HCV, a new-concept diagnostic assay for antibodies to hepatitis C virus in serum.

We screened phage libraries using sera from noninfected individuals and patients infected by hepatitis C virus (HCV). By applying different selection and maturation strategies, we identified a wide collection of efficient phage-borne ligands for HCV-specific antibodies. The selected ligands retained their antigenic properties when expressed as multimeric synthetic peptides. Peptides that mimic several immunodominant epitopes of the virus were used to develop a novel type of diagnostic assay which efficiently detects antibodies to HCV in serum. This type of analysis provides a conclusive diagnosis for many patients identified as indeterminate according to presently available serological assays.     

Computational design of peptide ligands

Peptides possess several attractive features when compared to small molecule and protein therapeutics, such as high structural compatibility with target proteins, the ability to disrupt protein-protein interfaces, and small size. Efficient design of high-affinity peptide ligands via rational methods has been a major obstacle to the development of this potential drug class. However, structural insights into the architecture of protein-peptide interfaces have recently culminated in several computational approaches for the rational design of peptides that target proteins. These methods provide a valuable alternative to experimental high-resolution structures of target protein-peptide complexes, bringing closer the dream of in silico designed peptides for therapeutic applications.     

Combining proteomics and bioinformatics to explore novel tegumental antigens as vaccine candidates against Echinococcus granulosus infection

Echinococcus granulosus is the parasite responsible for cystic echinococcosis (CE), an important worldwide-distributed zoonosis. New effective vaccines against CE could potentially have great economic and health benefits. Here, we describe an innovative vaccine design scheme starting from an antigenic fraction enriched in tegumental antigens from the protoscolex stage (termed PSEx) already known to induce protection against CE. We first used mass spectrometry to characterize the protein composition of PSEx followed by Gene Ontology analysis to study the potential Biological Processes, Molecular Functions, and Cellular Localizations of the identified proteins. Following, antigenicity predictions and determination of conservancy degree against other organisms were determined. Thus, nine novel proteins were identified as potential vaccine candidates. Furthermore, linear B cell epitopes free of posttranslational modifications were predicted in the whole PSEx proteome through colocalization of in silico predicted epitopes within peptide fragments identified by matrix-assisted laser desorption/ionization-TOF/TOF. Resulting peptides were termed “clean linear B cell epitopes,” and through BLASTp scanning against all nonhelminth proteins, those with 100% identity against any other protein were discarded. Then, the secondary structure was predicted for peptides and their corresponding proteins. Peptides with highly similar secondary structure respect to their parental protein were selected, and those potentially toxic and/or allergenic were discarded. Finally, the selected clean linear B cell epitopes were mapped within their corresponding 3D-modeled protein to analyze their possible antibody accessibilities, resulting in 14 putative peptide vaccine candidates. We propose nine novel proteins and 14 peptides to be further tested as vaccine candidates against CE.     

T-helper cell and associated antibody response to synthetic peptides of the E glycoprotein of Murray Valley encephalitis virus.

A battery of 16 synthetic peptides, selected primarily by computer analysis for predicted B- and T-cell epitopes, was prepared from the deduced amino acid sequence of the envelope (E) glycoprotein of Murray Valley encephalitis (MVE) virus. We examined all of the peptides for T-helper (Th)-cell recognition and antibody induction in three strains of mice: C57BL/6, BALB/c, and C3H. Lymphoproliferative and interleukin-2 assays were performed on splenic T cells from mice inoculated with peptides in Freund's incomplete adjuvant or with MVE virus. Several peptides found to contain predicted T-cell epitopes elicited a Th-cell response in at least one strain of mice, usually with a concomitant antibody response. Peptides 145 (amino acids 145 to 169) and 17 (amino acids 356 to 376) were strongly recognized by T cells from all three inbred strains of mice. Peptide 06 (amino acids 230 to 251) primed C57BL/6 mice for Th- and B-cell reactivity with native MVE virus, and T cells from virus-immune mice were stimulated by this peptide. Peptide 06 was recognized by several Th-cell clones prepared from mice immunized with MVE, West Nile, or Kunjin virus. These results indicate that it may be feasible to design synthetic flavivirus peptides that define T-cell epitopes capable of generating a helper cell response for B-cell epitopes involved in protective immunity.     

Design of a heterosubtypic epitope-based peptide vaccine fused with hemokinin-1 against influenza viruses

Influenza viruses continue to emerge and re-emerge, posing new threats for public health. Control and treatment of influenza depends mainly on vaccination and chemoprophylaxis with approved antiviral drugs. Identification of specific epitopes derived from influenza viruses has significantly advanced the development of epitope-based vaccines. Here, we explore the idea of using HLA binding data to design an epitope-based vaccine that can elicit heterosubtypic T-cell responses against circulating H7N9, H5N1, and H9N2 subtypes. The hemokinin-1(HK-1) peptide sequence was used to induce immune responses against the influenza viruses. Five conserved high score cytotoxic T lymphocyte(CTL) epitopes restricted to HLA-A*0201-binding peptides within the hemagglutinin(HA) protein of the viruses were chosen, and two HA CTL/HK-1 chimera protein models designed. Using in silico analysis, which involves interferon epitope scanning, protein structure prediction, antigenic epitope determination, and model quality evaluation, chimeric proteins were designed. The applicability of one of these proteins as a heterosubtypic epitopebased vaccine candidate was analyzed.