NetCTLpan: pan-specific MHC class I pathway epitope predictions

Reliable predictions of immunogenic peptides are essential in rational vaccine design and can minimize the experimental effort needed to identify epitopes. In this work, we describe a pan-specific major histocompatibility complex (MHC) class I epitope predictor, NetCTLpan. The method integrates predictions of proteasomal cleavage, transporter associated with antigen processing (TAP) transport efficiency, and MHC class I binding affinity into a MHC class I pathway likelihood score and is an improved and extended version of NetCTL. The NetCTLpan method performs predictions for all MHC class I molecules with known protein sequence and allows predictions for 8-, 9-, 10-, and 11-mer peptides. In order to meet the need for a low false positive rate, the method is optimized to achieve high specificity. The method was trained and validated on large datasets of experimentally identified MHC class I ligands and cytotoxic T lymphocyte (CTL) epitopes. It has been reported that MHC molecules are differentially dependent on TAP transport and proteasomal cleavage. Here, we did not find any consistent signs of such MHC dependencies, and the NetCTLpan method is implemented with fixed weights for proteasomal cleavage and TAP transport for all MHC molecules. The predictive performance of the NetCTLpan method was shown to outperform other state-of-the-art CTL epitope prediction methods. Our results further confirm the importance of using full-type human leukocyte antigen restriction information when identifying MHC class I epitopes. Using the NetCTLpan method, the experimental effort to identify 90% of new epitopes can be reduced by 15% and 40%, respectively, when compared to the NetMHCpan and NetCTL methods. The method and benchmark datasets are available at .     

Selection of T-cell epitopes from foot-and-mouth disease virus reflects the binding affinity to different cattle MHC class II molecules

The major histocompatibility complex (MHC)-restricted selection of T-cell epitopes of foot-and-mouth disease virus (FMDV) by individual cattle MHC class II DR (BoLA-DR) molecules was studied in a direct MHC-peptide binding assay. By in vitro priming of T lymphocytes derived from animals homozygous for both MHC class I and II, five T-cell epitopes were analyzed in the context of three MHC class II haplotypes. We found that the presentation of these T-cell epitopes was mediated by DR molecules, since blocking this pathway of antigen presentation using monoclonal antibody TH14B completely abolished the proliferative responses against the peptides. To study the DR-restricted presentation of these T-cell epitopes, a direct MHC-peptide binding assay on isolated cattle DR molecules was developed. Purified cattle MHC class II DR molecules of the BoLA-DRB3*0201, BoLA-DRB3*1101, and BoLA-DRB3*1201 alleles were isolated from peripheral blood mononuclear cells. For each allele, one of the identified T-cell epitopes was biotinylated, and used as a marker peptide for the development of a competitive MHC-peptide binding assay. Subsequently, the T-cell epitopes of FMDV with functionally defined MHC class II specificity were analyzed in this binding assay. The affinity of the epitopes to bind to certain DR molecules was significantly correlated to the capacity to induce T-cell proliferation. This demonstrated at the molecular level that the selection of individual T-cell epitopes found at the functional level was indeed the result of MHC restriction.     

Enhancement to the RANKPEP resource for the prediction of peptide binding to MHC molecules using profiles

We introduced previously an on-line resource, RANKPEP that uses position specific scoring matrices (PSSMs) or profiles for the prediction of peptide-MHC class I (MHCI) binding as a basis for CD8 T-cell epitope identification. Here, using PSSMs that are structurally consistent with the binding mode of MHC class II (MHCII) ligands, we have extended RANKPEP to prediction of peptide-MHCII binding and anticipation of CD4 T-cell epitopes. Currently, 88 and 50 different MHCI and MHCII molecules, respectively, can be targeted for peptide binding predictions in RANKPEP. Because appropriate processing of antigenic peptides must occur prior to major histocompatibility complex (MHC) binding, cleavage site prediction methods are important adjuncts for T-cell epitope discovery. Given that the C-terminus of most MHCI-restricted epitopes results from proteasomal cleavage, we have modeled the cleavage site from known MHCI-restricted epitopes using statistical language models. The RANKPEP server now determines whether the C-terminus of any predicted MHCI ligand may result from such proteasomal cleavage. Also implemented is a variability masking function. This feature focuses prediction on conserved rather than highly variable protein segments encoded by infectious genomes, thereby offering identification of invariant T-cell epitopes to thwart mutation as an immune evasion mechanism.     

Predicting peptides bound to I-Ag7 class II histocompatibility molecules using a novel expectation-maximization alignment algorithm

The useful structural features of class II MHC molecules are rarely integrated into T-cell epitope predictions. We propose an approach that applies a novel expectation-maximization algorithm to align the naturally processed peptides selected by the class II MHC I-A(g7) molecule - focusing on the five MHC-specific anchor positions. Based on the alignment profile, log of odds (LOD) scores supplemented with the Laplace plus-one pseudocounts method are applied to identify the potential T-cell epitopes. In addition, an innovative computational concept of hindering residues using statistical and structural information is developed to refine the prediction. Performance analysis by receiver operating characteristics statistics and the experimental validation of the LOD scores demonstrate the accuracy of our predictive model. Furthermore, our model successfully predicts T-cell epitopes of hen egg-white lysozyme protein antigen. Our study provides a framework for predicting T-cell epitopes in class II MHC molecules.     

Prediction and Molecular Modeling of T-cell Epitopes Derived from Placental Alkaline Phosphatase for use in Cancer Immunotherapy

Abstract

In our ongoing efforts to combat cancer, peptide-based tumor vaccines are promising as one of the several alternatives used for cancer immunotherapy and immunoprevention. We have attempted to identify T-cell epitopes suitable for the development of a peptide-based cancer vaccine directed towards placental isozyme of alkaline phosphatase (PLAP), an oncofetal antigen. After identifying amino acid residues specific to PLAP and distinct from other close PLAP homologs, we have used sequence-based immunoinformatics tools (BIMAS and SYF- PEITHI) and conducted molecular modeling studies using InsightII to investigate the binding affinity of the epitopes containing the unique residues with respective MHC class I molecules. Promiscuous epitopes binding to different alleles of different class I HLA loci were analyzed to get a population coverage that is widespread. Binding affinity deduced from the modeling studies corroborated the status of most of the epitopes scoring high in BIMAS and SYFPEITHI. We have thus identified specific epitopes from PLAP that have a potential for binding to their respective MHC class I alleles with high affinity. These peptides would be analysed in experiments to demonstrate their involvement in the induction of primary cytotoxic T-cell responses in vitro, using respective HLA-restricted T-cells in our way towards the development of an effective anti-cancer vaccine in a background of diverse MHC haplotypes.     

An effective and effecient peptide binding prediction approach for a broad set of HLA-DR molecules based on ordered weighted averaging of binding pocket profiles

Background

The immune system must detect a wide variety of microbial pathogens, such as viruses, bacteria, fungi and parasitic worms, to protect the host against disease. Antigenic peptides displayed by MHC II (class II Major Histocompatibility Complex) molecules is a pivotal process to activate CD4+ T_H cells (Helper T cells). The activated T_H cells can differentiate into effector cells which assist various cells in activating against pathogen invasion. Each MHC locus encodes a great number of allele variants. Yet this limited number of MHC molecules are required to display enormous number of antigenic peptides. Since the peptide binding measurements of MHC molecules by biochemical experiments are expensive, only a few of the MHC molecules have suffecient measured peptides. To perform accurate binding prediction for those MHC alleles without suffecient measured peptides, a number of computational algorithms were proposed in the last decades.

Results

Here, we propose a new MHC II binding prediction approach, OWA-PSSM, which is a significantly extended version of a well known method called TEPITOPE. The TEPITOPE method is able to perform prediction for only 50 MHC alleles, while OWA-PSSM is able to perform prediction for much more, up to 879 HLA-DR molecules. We evaluate the method on five benchmark datasets. The method is demonstrated to be the best one in identifying binding cores compared with several other popular state-of-the-art approaches. Meanwhile, the method performs comparably to the TEPITOPE and NetMHCIIpan2.0 approaches in identifying HLA-DR epitopes and ligands, and it performs significantly better than TEPITOPEpan in the identification of HLA-DR ligands and MultiRTA in identifying HLA-DR T cell epitopes.

Conclusions

The proposed approach OWA-PSSM is fast and robust in identifying ligands, epitopes and binding cores for up to 879 MHC II molecules.

     

Defining MHC class II T helper epitopes for WT1 tumor antigen

The product of Wilms‘ tumor gene 1 (WT1) is overexpressed in diverse human tumors, including leukemia, lung and breast cancer, and is often recognized by antibodies in the sera of patients with leukemia. Since WT1 encodes MHC class I-restricted peptides recognized by cytotoxic T lymphocytes (CTL), WT1 has been considered as a promising tumor-associated antigen (TAA) for developing anticancer immunotherapy. In order to carry out an effective peptide-based cancer immunotherapy, MHC class II-restricted epitope peptides that elicit anti-tumor CD4⁺ helper T lymphocytes (HTL) will be needed. In this study, we analyzed HTL responses against WT1 antigen using HTL lines elicited by in vitro immunization of human lymphocytes with synthetic peptides predicted to serve as HTL epitopes derived from the sequence of WT1. Two peptides, WT1_124–138 and WT1_247–261, were shown to induce peptide-specific HTL, which were restricted by frequently expressed HLA class II alleles. Here, we also demonstrate that both peptides-reactive HTL lines were capable of recognizing naturally processed antigens presented by dendritic cells pulsed with tumor lysates or directly by WT1+ tumor cells that express MHC class II molecules. Interestingly, the two WT1 HTL epitopes described here are closely situated to known MHC class I-restricted CTL epitopes, raising the possibility of stimulating CTL and HTL responses using a relatively small synthetic peptide vaccine. Because HTL responses to TAA are known to be important for promoting long-lasting anti-tumor CTL responses, the newly described WT1 T-helper epitopes could provide a useful tool for designing powerful vaccines against WT1-expressing tumors.     

Construction and immunogenicity prediction of Plasmodium falciparum CTL epitope minigene vaccine

The minigenes encoding Plasmodiumfalciparum CTL epitopes restricted to human MHC class I molecular HLA-A2 and HLA-B51, which were both at high frequency among Chinese population, were constructed as mono-epitope CTL vaccines named pcDNA3.1/tr and pcDNA3.1/sh. The minigenes of the two epitopes were then tandem linked to form a dimeric CTL epitope minigene recombinant vaccine. After DNA transfection, the epitope minigenes were expressed respectively in two human cell lines, each bearing one MHC class I molecule named CIR/HLA-A2.1 and K562/HLA-B51. The intracellular expression of the CTL epitope minigenes not only enhanced the stability of HLA-A2.1 and HLA-B51 molecules but also increased the assemblage of MHC class I molecules on cell surfaces, which testified the specific process and presentation of those endogenous expressed epitopes. For the cells transfected with the dimeric minigene encoding two tandem linked epitopes, the expression and presentation of each epitope were also detected on cell membranes that bore different MHC class I molecules. It meant that the adjacency of the two CTL epitopes did not interfere with the specific process and presentation of each epitope. Compared with the ordinary CTL studies that inoculated synthesized epitope peptides with peripheral blood cells, this work aimed to process the epitopes directly inside HLA class I allele specific human cells, and thus theoretically imitated the same procedurein vivo. It was also an economical way to predict the immunogenicity of CTL epitopes at an early stage especially in laboratories with limited financial resource.     

HIV-1 Envelope Resistance to Proteasomal Cleavage: Implications for Vaccine Induced Immune Responses

Background

Antigen processing involves many proteolytic enzymes such as proteasomes and cathepsins. The processed antigen is then presented on the cell surface bound to either MHC class I or class II molecules and induces/interacts with antigen-specific CD8+ and CD4+ T-cells, respectively. Preliminary immunological data from the RV144 phase III trial indicated that the immune responses were biased towards the Env antigen with a dominant CD4+ T-cell response.

Methods

In this study, we examined the susceptibility of HIV-1 Env-A244 gp120 protein, one of the protein boost subunits of the RV144 Phase III vaccine trial, to proteasomes and cathepsins and identified the generated peptide epitope repertoire by mass spectrometry. The peptide fragments were tested for cytokine production in CD4⁺ T-cell lines derived from RV144 volunteers.

Results

Env-A244 was resistant to proteasomes, thus diminishing the possibility of the generation of class I epitopes by the classical MHC class I pathway. However, Env-A244 was efficiently cleaved by cathepsins generating peptide arrays identified by mass spectrometry that contained both MHC class I and class II epitopes as reported in the Los Alamos database. Each of the cathepsins generated distinct degradation patterns containing regions of light and dense epitope clusters. The sequence DKKQKVHALF that is part of the V2 loop of gp120 produced by cathepsins induced a polyfunctional cytokine response including the generation of IFN-γ from CD4⁺ T-cell lines-derived from RV144 vaccinees. This sequence is significant since antibodies to the V1/V2-loop region correlated inversely with HIV-1 infection in the RV144 trial.

Conclusions

Based on our results, the susceptibility of Env-A244 to cathepsins and not to proteasomes suggests a possible mechanism for the generation of Env-specific CD4⁺T cell and antibody responses in the RV144 vaccinees.     

Computational characterization of epitopic region within the outer membrane protein candidate in Flavobacterium columnare for vaccine development

Abstract

Gram-negative bacteria is the main causative agents for columnaris disease outbreak to finfishes. The outer membrane proteins (OMPs) candidate of Flavobacterium columnare bacterial cell served a critical component for cellular invasion targeted to the eukaryotic cell and survival inside the macrophages. Therefore, OMPs considered as the supreme element for the development of promising vaccine against F. columnare. Implies advanced in silico approaches, the predicted 3-D model of targeted OMPs were characterized by the Swiss model server and validated through Procheck programs and Protein Structure Analysis (ProSA) web server. The protein sequences having B-cell binding sites were preferred from sequence alignment; afterwards the B cell epitopes prediction was prepared using the BCPred and amino acid pairs (AAP) prediction algorithms modules of BCPreds. Consequently, the selected antigenic amino acids sequences (B-cell epitopic regions) were analyzed for T-cell epitopes determination (MHC I and MHC II alleles binding sequence) performing the ProPred 1 and ProPred server respectively. The epitopes (9 mer: IKKYEPAPV, YGPNYKWKF and YRGLNVGTS) within the OMPs binds to both of the MHC classes (MHC I and MHC II) and covered highest number of MHC alleles are characterized. OMPs of F. columnare being conserved across serotypes and highly immunogenic for their exposed epitopes on the cell surface as a potent candidate focus to vaccine development for combating the disease problems in commercial aquaculture. The portrayed epitopes might be beneficial for practical designing of abundant peptide-based vaccine development against the columnaris through boosting up the advantageous immune responses.

Communicated by Ramaswamy H. Sarma     

Flow cytometric analysis of peptide binding to major histocampatibility complex class I for hepatitis C virus core T-cell epitopes

BACKGROUND/METHODS: To characterize the repertoire of T-cell epitopes on the hepatitis C virus (HCV) core protein, we studied major histocompatibility complex (MHC) class I binding of 75 decapeptides on 20 human B-cell lines and murine spleen cells using a flow cytometric assay. The results were compared with MHC class I stabilization on T2 cells, the SYFPEITHI algorithm, and known T-cell epitopes from the literature. RESULTS: Binding of peptides proved to be specific for MHC class I molecules. We observed peak fluorescence signals at positions amino acids (aa) 35-44, aa 87-96, aa 131-140, and aa 167-176 in virtually all HLA-A2-positive cell lines. These sites corresponded to T-cell epitopes predicted by SYFPEITHI and the positions of known T-cell epitopes, whereas T2 stabilization was at variance for two peptides. The assay was applied to HLA-A2-negative cells and murine spleen cells without further modification, and identified additional peptides, corresponding to known T-cell epitopes. CONCLUSIONS: Peptide binding to different MHC class I alleles can be mapped rapidly by a flow cytometric assay and enables a first orientation on the sites of possible T-cell epitopes. Application of this assay to HCV core suggests a rather limited repertoire of epitopes in the Caucasoid population.     

Prediction of Epitope-Based Peptides for Vaccine Development from Coat Proteins GP2 and VP24 of Ebola Virus Using Immunoinformatics

This study aims to design epitope-based peptides for the utility of vaccine development by targeting Glycoprotein 2 (GP2) and Viral Protein 24 (VP24) of the Ebola virus (EBOV) that, respectively, facilitate attachment and fusion of EBOV with host cells. Using various databases and tools, immune parameters of conserved sequences from GP2 and VP24 proteins of different strains of EBOV were tested to predict probable epitopes. Binding analyses of the peptides with major histocompatibility complex (MHC) class I and class II molecules, population coverage, and linear B cell epitope prediction were peroformed. Predicted peptides interacted with multiple MHC alleles and illustrated maximal population coverage for both GP2 and VP24 proteins, respectively. The predicted class-I nonamers, FLYDRLAST, LFLRATTEL and NYNGLLSSI were found to cover the maximum number of MHC I alleles and showed interactions with binding energies of ?7.8, ?8.5 and ?7.7 kcal/mol respectively. Highest scoring class II MHC binding peptides were EGAFFLYDRLASTVI and SPLWALRVILAAGIQ with binding energies of ?6.2 and -5.6 kcal/mol. Putative B cell epitopes were also found on 4 conserved regions in GP2 and two conserved regions in VP24. Our in silico analysis suggests that the predicted epitopes could be a better choice as universal vaccine component against EBOV irrespective of different strains and should be subjected to in vitro and in vivo analyses for further research and development.     

Structure-based identification of MHC binding peptides: Benchmarking of prediction accuracy

Identification of MHC binding peptides is essential for understanding the molecular mechanism of immune response. However, most of the prediction methods use motifs/profiles derived from experimental peptide binding data for specific MHC alleles, thus limiting their applicability only to those alleles for which such data is available. In this work we have developed a structure-based method which does not require experimental peptide binding data for training. Our method models MHC-peptide complexes using crystal structures of 170 MHC-peptide complexes and evaluates the binding energies using two well known residue based statistical pair potentials, namely Betancourt-Thirumalai (BT) and Miyazawa-Jernigan (MJ) matrices. Extensive benchmarking of prediction accuracy on a data set of 1654 epitopes from class I and class II alleles available in the SYFPEITHI database indicate that BT pair-potential can predict more than 60% of the known binders in case of 14 MHC alleles with AUC values for ROC curves ranging from 0.6 to 0.9. Similar benchmarking on 29,522 class I and class II MHC binding peptides with known IC(50) values in the IEDB database showed AUC values higher than 0.6 for 10 class I alleles and 9 class II alleles in predictions involving classification of a peptide to be binder or non-binder. Comparison with recently available benchmarking studies indicated that, the prediction accuracy of our method for many of the class I and class II MHC alleles was comparable to the sequence based methods, even if it does not use any experimental data for training. It is also encouraging to note that the ranks of true binding peptides could further be improved, when high scoring peptides obtained from pair potential were re-ranked using all atom forcefield and MM/PBSA method.     

Hepatitis B virus splice-generated protein induces T-cell responses in HLA-transgenic mice and hepatitis B virus-infected patients

Hepatitis B virus splice-generated protein (HBSP), encoded by a spliced hepatitis B virus RNA, was recently identified in liver biopsy specimens from patients with chronic active hepatitis B. We investigated the possible generation of immunogenic peptides by the processing of this protein in vivo. We identified a panel of potential epitopes in HBSP by using predictive computational algorithms for peptide binding to HLA molecules. We used transgenic mice devoid of murine major histocompatibility complex (MHC) class I molecules and positive for human MHC class I molecules to characterize immune responses specific for HBSP. Two HLA-A2-restricted peptides and one immunodominant HLA-B7-restricted epitope were identified following the immunization of mice with DNA vectors encoding HBSP. Most importantly, a set of overlapping peptides covering the HBSP sequence induced significant HBSP-specific T-cell responses in peripheral blood mononuclear cells from patients with chronic hepatitis B. The response was multispecific, as several epitopes were recognized by CD8(+) and CD4(+) human T cells. This study provides the first evidence that this protein generated in vivo from an alternative reading frame of the hepatitis B virus genome activates T-cell responses in hepatitis B virus-infected patients. Given that hepatitis B is an immune response-mediated disease, the detection of T-cell responses directed against HBSP in patients with chronic hepatitis B suggests a potential role for this protein in liver disease progression.     

Prediction of MHC class II binding affinity using SMM-align,a novel stabilization matrix alignment method

Background  

Antigen presenting cells (APCs) sample the extra cellular space and present peptides from here to T helper cells, which can be activated if the peptides are of foreign origin. The peptides are presented on the surface of the cells in complex with major histocompatibility class II (MHC II) molecules. Identification of peptides that bind MHC II molecules is thus a key step in rational vaccine design and developing methods for accurate prediction of the peptide:MHC interactions play a central role in epitope discovery. The MHC class II binding groove is open at both ends making the correct alignment of a peptide in the binding groove a crucial part of identifying the core of an MHC class II binding motif. Here, we present a novel stabilization matrix alignment method, SMM-align, that allows for direct prediction of peptide:MHC binding affinities. The predictive performance of the method is validated on a large MHC class II benchmark data set covering 14 HLA-DR (human MHC) and three mouse H2-IA alleles.     

Reconstruction of a pathway of antigen processing and class II MHC peptide capture

Endocytosed antigens are proteolytically processed and small amounts of peptides captured by class II MHC molecules. The details of antigen proteolysis, peptide capture and how destruction of T-cell epitopes is avoided are incompletely understood. Using the tetanus toxin antigen, we show that the introduction of 3-6 cleavage sites is sufficient to trigger a partially unfolded conformation able to bind to class II MHC molecules. The known locations of T-cell epitopes and protease cleavage sites predict that large domains of processed antigen (8-35 kDa) are captured under these conditions. Remarkably, when antigen is bound to the B-cell antigen receptor (BCR), processing can trigger a concerted 'hand-over' reaction whereby BCR-associated processed antigen is captured by neighbouring class II MHC molecules. Early capture of minimally processed antigen and confinement of the processing and class II MHC loading reaction to the membrane plane may improve the likelihood of T-cell epitope survival in the class II MHC pathway and may help explain the reciprocal relationships observed between B- and T-cell epitopes in many protein antigens and autoantigens.     

MHC motif viewer

In vertebrates, the major histocompatibility complex (MHC) presents peptides to the immune system. In humans, MHCs are called human leukocyte antigens (HLAs), and some of the loci encoding them are the most polymorphic in the human genome. Different MHC molecules present different subsets of peptides, and knowledge of their binding specificities is important for understanding the differences in the immune response between individuals. Knowledge of motifs may be used to identify epitopes, to understand the MHC restriction of epitopes, and to compare the specificities of different MHC molecules. Algorithms that predict which peptides MHC molecules bind have recently been developed and cover many different alleles, but the utility of these algorithms is hampered by the lack of tools for browsing and comparing the specificity of these molecules. We have, therefore, developed a web server, MHC motif viewer, that allows the display of the likely binding motif for all human class I proteins of the loci HLA A, B, C, and E and for MHC class I molecules from chimpanzee (Pan troglodytes), rhesus monkey (Macaca mulatta), and mouse (Mus musculus). Furthermore, it covers all HLA-DR protein sequences. A special viewing feature, MHC fight, allows for display of the specificity of two different MHC molecules side by side. We show how the web server can be used to discover and display surprising similarities as well as differences between MHC molecules within and between different species. The MHC motif viewer is available at .     

H2-M polymorphism in mice susceptible to collagen-induced arthritis involves the peptide binding groove

 The ability to develop type II collagen (CII)-induced arthritis (CIA) in mice is associated with the major histocompatibility I-A gene and with as yet poorly defined regulatory molecules of the major histocompatibility complex (MHC) class II antigen processing and presentation pathway. H2-M molecules are thought to be involved in the loading of antigenic peptides into the MHC class II binding cleft. We sequenced H2-Ma, H2-Mb1, and H2-Mb2 genes from CIA-susceptible and -resistant mouse strains and identified four different Ma and Mb2 alleles and three different Mb1 alleles defined by polymorphic residues within the predicted peptide binding groove. Most CIA-resistant mouse strains share common Ma, Mb1, and Mb2 alleles. In contrast, H2-M alleles designated Ma-III, Ma-IV, Mb1-III, and Mb2-IV could be exclusively identified in the CIA-susceptible H2 ^r and H2 ^q haplotypes, suggesting that allelic H2-M molecules may modulate the composition of different CII peptides loaded onto MHC class II molecules, presumably presenting “arthritogenic” epitopes to T lymphocytes. Received: 8 December 1995 / Revised: 16 January 1996     

Identification and evaluation of universal epitopes in Plasmodium vivax Duffy binding protein

Selected PvDBP-derived synthetic peptides were tested in competition assays with HLA molecules in order to identify and evaluate their binding to a wide range of MHC class II molecules. Binding was evaluated as the peptide’s ability to displace the biotinylated control peptide (HA_306-318) and was detected by a conventional ELISA. Thus, one epitope for the HLA-DR1 molecule, two epitopes for the HLA-DR4 molecule, six epitopes for the HLA-DR7 molecule and three epitopes for the HLA-DR11 molecule displaying a high binding percentage (above 50%) were experimentally obtained. The in vitro results were compared with the epitope prediction results. Two peptides behaved as universal epitopes since they bound to a larger number of HLA-DR molecules. Given that these peptides are located in the conserved PvDBP region II, they could be considered good candidates to be included in the design of a synthetic vaccine against Plasmodium vivax malaria.