Selection of peptides that bind to the HLA-A2.1 molecule by molecular modelling

Mesothelin- and nucleolin-specific T cells from combined short peptides effectively kill triple-negative breast cancer cells

BACKGROUND

Triple-negative breast cancer (TNBC), known for its aggressiveness and limited treatment options, presents a significant challenge. Adoptive cell transfer, involving the ex vivo generation of antigen-specific T cells from peripheral blood mononuclear cells (PBMCs), emerges as a promising approach. The overexpression of mesothelin (MSLN) and nucleolin (NCL) in TNBC samples underscores their potential as targets for T cell therapy. This study explored the efficacy of multi-peptide pulsing of PBMCs to generate MSLN/NCL-specific T cells targeting MSLN+/NCL+ TNBC cells.

METHODS

TNBC patient samples were confirmed for both MSLN and NCL expression via immunohistochemistry. Synthesized MSLN and NCL peptides were combined and administered to activate PBMCs from healthy donors. The cancer-killing ability of the resultant T cells was assessed using crystal violet staining, and their subtypes and cytotoxic cytokines were characterized through flow cytometry and cytokine bead array.

RESULTS

Findings showed that 85.3% (127/149) of TNBC cases were positive for either MSLN or NCL, or both; with single positivity rates for MSLN and NCL of 14.1% and 28.9%, respectively. MSLN and NCL peptides, with high binding affinity for HLA-A*02, were combined and introduced to activated PBMCs from healthy donors. The co-pulsed PBMCs significantly induced TEM and TEMRA CD3+/CD8+ T cells and IFN-γ production, compared to single-peptide pulsed or unpulsed conditions. Notably, MSLN/NCL-specific T cells successfully induced cell death in MSLN+/NCL+ MDA-MB-231 cells, releasing key cytotoxic factors such as perforin, granzymes A and B, Fas ligand, IFN-γ, and granulysin.

CONCLUSIONS

These findings serve as a proof-of-concept for using multiple immunogenic peptides as a novel therapeutic approach in TNBC patients.

Stimulating T cell responses against patient-derived breast cancer cells with neoantigen peptide-loaded peripheral blood mononuclear cells

Breast cancer stands as a formidable global health challenge for women. While neoantigens exhibit efficacy in activating T cells specific to cancer and instigating anti-tumor immune responses, the accuracy of neoantigen prediction remains suboptimal. In this study, we identified neoantigens from the patient-derived breast cancer cells, PC-B-142CA and PC-B-148CA cells, utilizing whole-genome and RNA sequencing. The pVAC-Seq pipeline was employed, with minor modification incorporating criteria (1) binding affinity of mutant (MT) peptide with HLA (IC50 MT) ≤ 500 nm in 3 of 5 algorithms and (2) IC50 wild type (WT)/MT > 1. Sequencing results unveiled 2513 and 3490 somatic mutations, and 646 and 652 non-synonymous mutations in PC-B-142CA and PC-B-148CA, respectively. We selected the top 3 neoantigens to perform molecular dynamic simulation and synthesized 9-12 amino acid neoantigen peptides, which were then pulsed onto healthy donor peripheral blood mononuclear cells (PBMCs). Results demonstrated that T cells activated by ADGRL1E274K, PARP1E619K, and SEC14L2R43Q peptides identified from PC-B-142CA exhibited significantly increased production of interferon-gamma (IFN-γ), while PARP1E619K and SEC14L2R43Q peptides induced the expression of CD107a on T cells. The % tumor cell lysis was notably enhanced by T cells activated with MT peptides across all three healthy donors. Moreover, ALKBH6V83M and GAAI823T peptides from PC-B-148CA remarkably stimulated IFN-γ- and CD107a-positive T cells, displaying high cell-killing activity against target cancer cells. In summary, our findings underscore the successful identification of neoantigens with anti-tumor T cell functions and highlight the potential of personalized neoantigens as a promising avenue for breast cancer treatment.

T-cell epitope vaccine design by immunoinformatics

Vaccination is generally considered to be the most effective method of preventing infectious diseases. All vaccinations work by presenting a foreign antigen to the immune system in order to evoke an immune response. The active agent of a vaccine may be intact but inactivated ('attenuated') forms of the causative pathogens (bacteria or viruses), or purified components of the pathogen that have been found to be highly immunogenic. The increased understanding of antigen recognition at molecular level has resulted in the development of rationally designed peptide vaccines. The concept of peptide vaccines is based on identification and chemical synthesis of B-cell and T-cell epitopes which are immunodominant and can induce specific immune responses. The accelerating growth of bioinformatics techniques and applications along with the substantial amount of experimental data has given rise to a new field, called immunoinformatics. Immunoinformatics is a branch of bioinformatics dealing with in silico analysis and modelling of immunological data and problems. Different sequence- and structure-based immunoinformatics methods are reviewed in the paper.

Predicting HLA class I non-permissive amino acid residues substitutions

Prediction of peptide binding to human leukocyte antigen (HLA) molecules is essential to a wide range of clinical entities from vaccine design to stem cell transplant compatibility. Here we present a new structure-based methodology that applies robust computational tools to model peptide-HLA (p-HLA) binding interactions. The method leverages the structural conservation observed in p-HLA complexes to significantly reduce the search space and calculate the system’s binding free energy. This approach is benchmarked against existing p-HLA complexes and the prediction performance is measured against a library of experimentally validated peptides. The effect on binding activity across a large set of high-affinity peptides is used to investigate amino acid mismatches reported as high-risk factors in hematopoietic stem cell transplantation.

Computational analysis on the binding of epitope peptide to human leukocyte antigen class I molecule A*2402 subtype

Immunological response induced by small amino peptide has attracted much recent attention in the field of immunotherapy. Wilms' tumor (WT1) protein is one of the potent tumor antigens inducing immunological response in mouse and human, because WT1 is over expressed in many types of leukemia and various kinds of solid tumors. A 9-mer peptide encoded in WT1 protein (CMTWNQMNL; amino acid 235-243) is known to serve as antigenic peptide for human leukocyte antigen (HLA)-A*2402 molecule. It was reported that the replacement of the second amino residue, which is deeply responsible for the peptide binding to HLA, induced strong immunological response compared to the natural peptide. In this study, 19 kinds of single amino substitutions were introduced at position 2 of this 9-mer WT1 peptide. We performed molecular dynamics simulation on the complex of each of WT1 epitope peptides and HLA-β2 micro globulin (β2m) molecule, and subsequently estimated the binding affinity using molecular mechanics/generalized-Born surface area method combined with normal mode analysis. Our computation indicated that the peptide containing M2Y or M2W mutation showed high binding affinity to the HLA-β2m molecule as well as the natural peptide. We have also examined the role of the residue at position 2 in peptide binding to HLA-β2m. The calculation showed that van der Waals interaction between the side chain of the residue at position 2 and hydrophobic residues inside B-pocket of HLA are important. These findings will be helpful to search other potent peptides that will enhance strong immunological response specific to HLA-A*2402 molecule.

Secreted HLA recapitulates the immunopeptidome and allows in-depth coverage of HLA A*02:01 ligands

HLA molecules are cell-surface glycoproteins that present peptides, derived from intracellular protein antigens, for surveillance by T lymphocytes. Secreted HLA (sHLA) technology is a powerful approach for studying these peptides, since it facilitates large-scale production of HLA-bound peptides. We compared secreted and membrane-bound forms of HLA A2 in terms of intracellular trafficking and their bound peptide repertoire (termed the immunopeptidome). We demonstrate that sHLA and membrane bound HLA (mHLA) negotiate intracellular compartments with similar maturation kinetics. Moreover, mass spectrometry revealed a substantial overlap in the immunopeptidome was observed when HLA A2-bound peptides were purified from various sources of sHLA and mHLA. By combining machine based algorithms with manual validation, we identified 1266 non-redundant peptides. Analysis of these peptides revealed a number bearing post-translational modifications, although some of these may arise spontaneously others represent modifications performed within the cell that survive antigen processing. Peptides bearing some of these modifications have not previously been described for HLA ligands, therefore, this compendium of 1266 non-redundant peptide sequences adds greatly to the existing database of HLA A2 ligands. Peptides from all sources displayed comparable HLA A2 consensus binding motifs, peptide lengths, predicted HLA A2 binding affinities and putative source antigens. We conclude that sHLA is a valid and useful technique for studying the immunopeptidome.

Novel myeloma-associated antigens revealed in the context of syngeneic hematopoietic stem cell transplantation

Targets of curative donor-derived graft-versus-myeloma (GVM) responses after allogeneic hematopoietic stem cell transplantation (HSCT) remain poorly defined, partly because immunity against minor histocompatibility Ags (mHAgs) complicates the elucidation of multiple myeloma (MM)-specific targets. We hypothesized that syngeneic HSCT would facilitate the identification of GVM-associated Ags because donor immune responses in this setting should exclusively target unique tumor Ags in the absence of donor-host genetic disparities. Therefore, in the present study, we investigated the development of tumor immunity in an HLA-A0201(+) MM patient who achieved durable remission after myeloablative syngeneic HSCT. Using high-density protein microarrays to screen post-HSCT plasma, we identified 6 Ags that elicited high-titer (1:5000-1:10 000) Abs that correlated with clinical tumor regression. Two Ags (DAPK2 and PIM1) had enriched expression in primary MM tissues. Both elicited Ab responses in other MM patients after chemotherapy or HSCT (11 and 6 of 32 patients for DAPK2 and PIM1, respectively). The index patient also developed specific CD8(+) T-cell responses to HLA-A2-restricted peptides derived from DAPK2 and PIM1. Peptide-specific T cells recognized HLA-A2(+) MM-derived cell lines and primary MM tumor cells. Coordinated T- and B-cell immunity develops against MM-associated Ags after syngeneic HSCT. DAPK1 and PIM1 are promising target Ags for MM-directed immunotherapy.

T-cell epitope prediction and immune complex simulation using molecular dynamics: state of the art and persisting challenges

Atomistic Molecular Dynamics provides powerful and flexible tools for the prediction and analysis of molecular and macromolecular systems. Specifically, it provides a means by which we can measure theoretically that which cannot be measured experimentally: the dynamic time-evolution of complex systems comprising atoms and molecules. It is particularly suitable for the simulation and analysis of the otherwise inaccessible details of MHC-peptide interaction and, on a larger scale, the simulation of the immune synapse. Progress has been relatively tentative yet the emergence of truly high-performance computing and the development of coarse-grained simulation now offers us the hope of accurately predicting thermodynamic parameters and of simulating not merely a handful of proteins but larger, longer simulations comprising thousands of protein molecules and the cellular scale structures they form. We exemplify this within the context of immunoinformatics.

Identification of HLA-A*0201-restricted cytotoxic T lymphocyte epitope from proliferating cell nuclear antigen

Peptide-based immunotherapy strategies appear promising as an approach to successfully induce an antitumor immune response and prolong survival in patients with various cancers. Protein antigens and their specific epitopes are formulation targets for anti-tumor vaccines. Bioinformatical approaches to predict major histocompatibility complex binding peptides can facilitate the resource-consuming effort of T cell epitope identification. Proliferating cell nuclear antigen including Ki-67 and PCNA, associated with the proliferation process of the cell, seems to be an attractive new target for tumor-specific immunotherapy. In this study, we predicted seven HLA-A*0201-restricted CTL candidate epitope of Ki-67 and eight epitope of PCNA by computer algorithm SYFPEITHI, BIMAS, and IEDB_ANN. Subsequently, biological functions of these peptides were tested by experiments in vitro. We found Ki-67((280-288)) (LQGETQLLV) had the strongest binding-affinity with HLA-A*0201. Further study revealed that Ki-67((280-288)) increased the frequency of IFN-γ-producing T cells compared to a negative peptide. Because Ki-67 was broadly expressed in most advanced malignant tumors, indicating a potential anti-tumor application in the future.

HLA-A2-restricted cytotoxic T lymphocyte epitopes from human heparanase as novel targets for broad-spectrum tumor immunotherapy

Peptide vaccination for cancer immunotherapy requires identification of peptide epitopes derived from antigenic proteins associated with tumors. Heparanase (Hpa) is broadly expressed in various advanced tumors and seems to be an attractive new tumor-associated antigen. The present study was designed to predict and identify HLA-A2-restricted cytotoxic T lymphocyte (CTL) epitopes in the protein of human Hpa. For this purpose, HLA-A2-restricted CTL epitopes were identified using the following four-step procedure: 1) a computer-based epitope prediction from the amino acid sequence of human Hpa, 2) a peptide-binding assay to determine the affinity of the predicted protein with the HLA-A2 molecule, 3) stimulation of the primary T-cell response against the predicted peptides in vitro, and 4) testing of the induced CTLs toward different kinds of carcinoma cells expressing Hpa antigens and/or HLA-A2. The results demonstrated that, of the tested peptides, effectors induced by peptides of human Hpa containing residues 525-533 (PAFSYSFFV, Hpa525), 277-285 (KMLKSFLKA, Hpa277), and 405-413 (WLSLLFKKL, Hpa405) could effectively lyse various tumor cell lines that were Hpa-positive and HLA-A2-matched. We also found that these peptide-specific CTLs could not lyse autologous lymphocytes with low Hpa activity. Further study revealed that Hpa525, Hpa277, and Hpa405 peptides increased the frequency of IFN-gamma-producing T cells compared to a negative peptide. Our results suggest that Hpa525, Hpa277, and Hpa405 peptides are new HLA-A2-restricted CTL epitopes capable of inducing Hpa-specific CTLs in vitro. Because Hpa is expressed in most advanced malignant tumors, Hpa525, Hpa277, and Hpa405 peptide-based vaccines may be useful for the immunotherapy for patients with advanced tumors.

Direct class I HLA antigen discovery to distinguish virus-infected and cancerous cells

Class I human leukocyte antigen molecules are nature's proteome-scanning chips, presenting thousands of endogenously loaded peptides on the surface of virtually every cell in the body. Cytotoxic T cells survey the class I human leukocyte antigen peptide cargo presented, recognize peptides unique to unhealthy cells and destroy diseased cells. A precise understanding of how class I molecules distinguish diseased cells is positioned to drive immune-based diagnostics, therapies and vaccines. When identifying epitopes unique to unhealthy cells, the most experimentally direct approach is to examine the class I-presented peptides of infected/cancerous cells. Here we discuss the strategies adapted for protein production, protein/peptide purification, peptide separation and for maintaining experimental reproducibility during the direct characterization of class I human leukocyte antigen peptides.

Prediction and molecular modeling of T-cell epitopes derived from placental alkaline phosphatase for use in cancer immunotherapy

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 SYFPEITHI) 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.

Modeling the bound conformation of Pemphigus vulgaris-associated peptides to MHC Class II DR and DQ alleles

Background

Pemphigus vulgaris (PV) is a severe autoimmune blistering disorder characterized by the presence of pathogenic autoantibodies directed against desmoglein-3 (Dsg3), involving specific DR4 and DR6 alleles in Caucasians and DQ5 allele in Asians. The development of sequence-based predictive algorithms to identify potential Dsg3 epitopes has encountered limited success due to the paucity of PV-associated allele-specific peptides as training data.

Results

In this work we constructed atomic models of ten PV associated, non-associated and protective alleles. Nine previously identified stimulatory Dsg3 peptides, Dsg3 96–112, Dsg3 191–205, Dsg3 206–220, Dsg3 252–266, Dsg3 342–356, Dsg3 380–394, Dsg3 763–777, Dsg3 810–824 and Dsg3 963–977, were docked into the binding groove of each model to analyze the structural aspects of allele-specific binding.

Conclusion

Our docking simulations are entirely consistent with functional data obtained from in vitro competitive binding assays and T cell proliferation studies in DR4 and DR6 PV patients. Our findings ascertain that DRB1*0402 plays a crucial role in the selection of specific self-peptides in DR4 PV. DRB1*0402 and DQB1*0503 do not necessarily share the same core residues, indicating that both alleles may have different binding specificities. In addition, our results lend credence to the hypothesis that the alleles DQB1*0201 and *0202 play a protective role by binding Dsg3 peptides with greater affinity than the susceptible alleles, allowing for efficient deletion of autoreactive T cells.

Modeling the structure of bound peptide ligands to major histocompatibility complex

In this article, we present a new technique for the rapid and precise docking of peptides to MHC class I and class II receptors. Our docking procedure consists of three steps: (1) peptide residues near the ends of the binding groove are docked by using an efficient pseudo-Brownian rigid body docking procedure followed by (2) loop closure of the intervening backbone structure by satisfaction of spatial constraints, and subsequently, (3) the refinement of the entire backbone and ligand interacting side chains and receptor side chains experiencing atomic clash at the MHC receptor-peptide interface. The method was tested by remodeling of 40 nonredundant complexes of at least 3.00 A resolution for which three-dimensional structural information is available and independently for docking peptides derived from 15 nonredundant complexes into a single template structure. In the first test, 33 out of 40 MHC class I and class II peptides and in the second test, 11 out of 15 MHC-peptide complexes were modeled with a Calpha RMSD < 1.00 A.

Response of primed human PBMC to synthetic peptides derived from hepatitis B virus envelope proteins: a search for promiscuous epitopes

This investigation was aimed at identifying effective T helper cell epitopes to the hepatitis B virus in humans. A panel of synthetic peptides that represent the hepatitis B virus whole envelope proteins was examined for their capability to stimulate peripheral blood mononuclear cells from human subjects infected with hepatitis B virus naturally. In addition, a large number of subjects were examined and their human leukocyte antigen (HLA) class II allele types were identified to determine whether the helper T cell epitope is specific for a particular HLA allele or 'promiscuous'. The peptides of the amino acid residues 52-67, 110-125, 190-205, and 228-243 appeared to be immunogenic, and particularly, the 52-67 residue was the most promiscuous epitope peptide. These results would contribute to the better understanding of the helper T cell responses to the hepatitis B virus and provide a useful way in designing epitope-based vaccines and future therapeutic strategies.

Proteomics in Vaccinology and Immunobiology: An Informatics Perspective of the Immunone

The postgenomic era, as manifest, inter alia, by proteomics, offers unparalleled opportunities for the efficient discovery of safe, efficacious, and novel subunit vaccines targeting a tranche of modern major diseases. A negative corollary of this opportunity is the risk of becoming overwhelmed by this embarrassment of riches. Informatics techniques, working to address issues of both data management and through prediction to shortcut the experimental process, can be of enormous benefit in leveraging the proteomic revolution. In this disquisition, we evaluate proteomic approaches to the discovery of subunit vaccines, focussing on viral, bacterial, fungal, and parasite systems. We also adumbrate the impact that proteomic analysis of host-pathogen interactions can have. Finally, we review relevant methods to the prediction of immunome, with special emphasis on quantitative methods, and the subcellular localization of proteins within bacteria.

Computational immunology: The coming of age

The explosive growth in biotechnology combined with major advances in information technology has the potential to radically transform immunology in the postgenomics era. Not only do we now have ready access to vast quantities of existing data, but new data with relevance to immunology are being accumulated at an exponential rate. Resources for computational immunology include biological databases and methods for data extraction, comparison, analysis and interpretation. Publicly accessible biological databases of relevance to immunologists number in the hundreds and are growing daily. The ability to efficiently extract and analyse information from these databases is vital for efficient immunology research. Most importantly, a new generation of computational immunology tools enables modelling of peptide transport by the transporter associated with antigen processing (TAP), modelling of antibody binding sites, identification of allergenic motifs and modelling of T-cell receptor serial triggering.

Predicting sequences and structures of MHC-binding peptides: a computational combinatorial approach

Peptides bound to MHC molecules on the surface of cells convey critical information about the cellular milieu to immune system T cells. Predicting which peptides can bind an MHC molecule, and understanding their modes of binding, are important in order to design better diagnostic and therapeutic agents for infectious and autoimmune diseases. Due to the difficulty of obtaining sufficient experimental binding data for each human MHC molecule, computational modeling of MHC peptide-binding properties is necessary. This paper describes a computational combinatorial design approach to the prediction of peptides that bind an MHC molecule of known X-ray crystallographic or NMR-determined structure. The procedure uses chemical fragments as models for amino acid residues and produces a set of sequences for peptides predicted to bind in the MHC peptide-binding groove. The probabilities for specific amino acids occurring at each position of the peptide are calculated based on these sequences, and these probabilities show a good agreement with amino acid distributions derived from a MHC-binding peptide database. The method also enables prediction of the three-dimensional structure of MHC-peptide complexes. Docking, linking, and optimization procedures were performed with the XPLOR program [1].

Changes at the floor of the peptide-binding groove induce a strong preference for proline at position 3 of the bound peptide: molecular dynamics simulations of HLA-A*0217

We report on molecular dynamics simulations of major histocompatibility complex (MHC)-peptide complexes. Class I MHC molecules play an important role in cellular immunity by presenting antigenic peptides to cytotoxic T cells. Pockets in the peptide-binding groove of MHC molecules accommodate anchor side chains of the bound peptide. Amino acid substitutions in MHC affect differences in the peptide-anchor motifs. HLA-A*0217, human MHC class I molecule, differs from HLA-A*0201 only by three amino acid residues substitutions (positions 95, 97, and 99) at the floor of the peptide-binding groove. A*0217 showed a strong preference for Pro at position 3 (p3) and accepted Phe at p9 of its peptide ligands, but these preferences have not been found in other HLA-A2 ligands. To reveal the structural mechanism of these observations, the A*0217-peptide complexes were simulated by 1000 ps molecular dynamics at 300 K with explicit solvent molecules and compared with those of the A*0201-peptide complexes. We examined the distances between the anchor side chain of the bound peptide and the pocket, and the rms fluctuations of the bound peptides and the HLA molecules. On the basis of the results from our simulations, we propose that Pro at p3 serves as an optimum residue to lock the dominant anchor residue (p9) tightly into pocket F and to hold the peptide in the binding groove, rather than a secondary anchor residue fitting optimally the complementary pocket. We also found that Phe at p9 is used to occupy the space created by replacements of three amino acid residues at the floor within the groove. These findings would provide a novel understanding in the peptide-binding motifs of class I MHC molecules.

Magnitude of structural changes of the T-cell receptor binding regions determine the strength of T-cell antagonism: molecular dynamics simulations of HLA-DR4 (DRB1*0405) complexed with analogue peptide

In our model system, we generated T cell clones specific for the HLA-DR4 (DRB1*0405)-index peptide (YWALEAAAD) complex. Based on response patterns of the T cell clones, analogue peptides containing single amino acid substitutions of the index peptide were classified into three types, agonists, antagonists or null peptides (non-agonistic and non-antagonistic peptides). Subtle structural changes induced by the antagonists in the T-cell receptor (TCR) binding regions have already been explained using the root mean square (r.m.s.) deviations from the DR4-index peptide complex in the molecular dynamics (MD) trajectory. In this work, we performed additional MD simulations at 300 K with explicit solvent molecules to reveal the structural character of the HLA-DR4 complexed with the analogue peptides. We examined the r.m.s. deviations of the TCR-binding sites and the exposed areas of the bound peptides. Remarkable differences of the r.m.s. deviations among the DR4-antagonist complexes, together with our previous data, suggest that the magnitude of structural changes of TCR-binding regions would determine the strength of TCR antagonism. The simulations also indicate that TCR could discriminate null peptides from other ligands mainly through the changes of exposed side chains of the bound peptide, rather than the conformational changes of TCR-binding surfaces on HLA molecule.

The MHC Class I-Restricted Immune Response to HIV-gag in BALB/c Mice Selects a Single Epitope That Does Not Have a Predictable MHC-Binding Motif and Binds to Kd Through Interactions Between a Glutamine at P3 and Pocket D

Using a strain of Listeria monocytogenes that stably expresses and secretes HIV gag to deliver this Ag to the MHC class I pathway of Ag processing, we have identified the immunodominant CTL epitope to gag in the BALB/c mouse and shown that it is Kd restricted. The specific motif for the peptides that bind the MHC class I molecule H-2 Kd is believed to be a nonamer with residues tyrosine or phenylalanine in the second amino acid position and leucine or isoleucine in the carboxyl-terminal or ninth amino acid position as dominant anchoring positions. Surprisingly, the identified gag peptide, AMQMLKETI, does not contain an anchoring aromatic residue in position two although competition assays with other Kd-restricted epitopes indicated that it binds to Kd with comparable affinity. Using a theoretical molecular dynamics approach to probe the stability of peptide binding to MHC class I molecules, we show that the absence of an appropriate anchor residue at P2 in AMQMLKETI is compensated by favorable interactions of the glutamine at P3 with pocket D of Kd. These findings were verified experimentally, demonstrating the predictive power of this theoretical approach in analyzing MHC class I/peptide interactions. These studies also indicate that CTL epitope prediction that relies on dominant peptide motifs may not always identify the correct epitope.

Peptide-specific CTL induction in HBV-seropositive PBMC by stimulation with peptides in vitro: novel epitopes identified from chronic carriers

Cytotoxic T lymphocytes (CTL) recognize and destroy virus-infected cells, and it has been established that epitope-based peptides could induce such CTL in vivo as well as in vitro. In this study attempts were made to define the epitopes that are recognized by the CTL, and thus a series of 9- to 10-mer peptides derived from the amino acid sequences of hepatitis B virus (HBV) proteins were synthesized on the basis of the previously described HLA-A2 peptide binding motif. The binding assay of the synthetic peptides using transporter-associated with antigen processing (TAP)-deficient human cell line, T2, showed that eight out of 11 peptides tested enhanced the expression of HLA-A2 molecules on the T2 cell surface. Some of these peptides triggered activation of CTL in peripheral blood mononuclear cells of HBV-seropositive chronic carriers. The activated CTL in turn recognized and killed the T2 cells pulsed with the same peptides. This study shows that novel HLA-A2-restricted epitopes exist in the natural repertoire of immunity against HBV. These findings can be useful in developing peptide-based therapeutics against viral infections.