Quantitative online prediction of peptide binding to the major histocompatibility complex

With its implications for vaccine discovery, the accurate prediction of T cell epitopes is one of the key aspirations of computational vaccinology. We have developed a robust multivariate statistical method, based on partial least squares, for the quantitative prediction of peptide binding to major histocompatibility complexes (MHC), the principal checkpoint on the antigen presentation pathway. As a service to the immunobiology community, we have made a Perl implementation of the method available via a World Wide Web server. We call this server MHCPred. Access to the server is freely available from the URL: http://www.jenner.ac.uk/MHCPred. We have exemplified our method with a model for peptides binding to the common human MHC molecule HLA-B*3501.

Greater CD8+ TCR heterogeneity and functional flexibility in HIV-2 compared to HIV-1 infection

Virus-specific CD8+ T cells are known to play an important role in the control of HIV infection. In this study we investigated whether there may be qualitative differences in the CD8+ T cell response in HIV-1- and HIV-2-infected individuals that contribute to the relatively efficient control of the latter infection. A molecular comparison of global TCR heterogeneity showed a more oligoclonal pattern of CD8 cells in HIV-1- than HIV-2-infected patients. This was reflected in restricted and conserved TCR usage by CD8+ T cells recognizing individual HLA-A2- and HLA-B57-restricted viral epitopes in HIV-1, with limited plasticity in their response to amino acid substitutions within these epitopes. The more diverse TCR usage observed for HIV-2-specific CD8 T cells was associated with an enhanced potential for CD8+ expansion and IFN- production on cross-recognition of variant epitopes. Our data suggest a mechanism that could account for any possible cross-protection that may be mediated by HIV-2-specific CD8+ T cells against HIV-1 infection. Furthermore, they have implications for HIV vaccine development, demonstrating an association between a polyclonal, virus-specific CD8+ T cell response and an enhanced capacity to tolerate substitutions within T cell epitopes.

JenPep : a novel computational information resource for immunobiology and vaccinology

JenPep is a relational database containing a compendium of thermodynamic binding data for the interaction of peptides with a range of important immunological molecules:  the major histocompatibility complex, TAP transporter, and T cell receptor. The database also includes annotated lists of B cell and T cell epitopes. Version 2.0 of the database is implemented in a bespoke postgreSQL database system and is fully searchable online via a perl/HTML interface (URL:  http://www.jenner.ac.uk/JenPep).

EpiDOCK:a molecular docking-based tool for MHC class II binding prediction

Cellular peptide vaccines contain T-cell epitopes. The main prerequisite for a peptide to act as a T-cell epitope is that it binds to a major histocompatibility complex (MHC) protein. Peptide MHC binder identification is an extremely costly experimental challenge since human MHCs, named human leukocyte antigen, are highly polymorphic and polygenic. Here we present EpiDOCK, the first structure-based server for MHC class II binding prediction. EpiDOCK predicts binding to the 23 most frequent human, MHC class II proteins. It identifies 90% of true binders and 76% of true non-binders, with an overall accuracy of 83%. EpiDOCK is freely accessible at http://epidock.ddg-pharmfac. net. © The Author 2013. Published by Oxford University Press. All rights reserved.

Designing immunogenic peptides

Peptides fulfill many roles in immunology, yet none are more important than their role as immunogenic epitopes driving the adaptive immune response, our ultimate bulwark against infectious disease. Peptide epitopes are mediated primarily by their interaction with major histocompatibility complexes (T-cell epitopes) and antibodies (B-cell epitopes). As pathogen genomes continue to be revealed, both experimental and computational epitope mapping are becoming crucial tools in vaccine discovery1,2. Immunoinformatics offers many tools, techniques and approaches for in silico epitope characterization, which is capable of greatly accelerating epitope design. © 2013 Nature America, Inc. All rights reserved.

MHC class II binding prediction by molecular docking

Proteins of the Major Histocompatibility Complex (MHC) bind self and nonself peptide antigens or epitopes within the cell and present them at the cell surface for recognition by T cells. All T-cell epitopes are MHC binders but not all MCH binders are T-cell epitopes. The MHC class II proteins are extremely polymorphic. Polymorphic residues cluster in the peptide-binding region and largely determine the MHC's peptide selectivity. The peptide binding site on MHC class II proteins consist of five binding pockets. Using molecular docking, we have modelled the interactions between peptide and MHC class II proteins from locus DRB1. A combinatorial peptide library was generated by mutation of residues at peptide positions which correspond to binding pockets (so called anchor positions). The binding affinities were assessed using different scoring functions. The normalized scoring functions for each amino acid at each anchor position were used to construct quantitative matrices (QM) for MHC class II binding prediction. Models were validated by external test sets comprising 4540 known binders. Eighty percent of the known binders are identified in the best predicted 15% of all overlapping peptides, originating from one protein. © 2011 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Towards the knowledge-based design of universal influenza epitope ensemble vaccines

Motivation: Influenza A viral heterogeneity remains a significant threat due to unpredictable antigenic drift in seasonal influenza and antigenic shifts caused by the emergence of novel subtypes. Annual review of multivalent influenza vaccines targets strains of influenza A and B likely to be predominant in future influenza seasons. This does not induce broad, cross protective immunity against emergent subtypes. Better strategies are needed to prevent future pandemics. Cross-protection can be achieved by activating CD8+ and CD4+ T cells against highly-conserved regions of the influenza genome. We combine available experimental data with informatics-based immunological predictions to help design vaccines potentially able to induce cross-protective T-cells against multiple influenza subtypes. Results: To exemplify our approach we designed two epitope ensemble vaccines comprising highly-conserved and experimentally-verified immunogenic influenza A epitopes as putative non-seasonal influenza vaccines; one specifically targets the US population and the other is a universal vaccine. The USA-specific vaccine comprised 6 CD8+ T cell epitopes (GILGFVFTL, FMYSDFHFI, GMDPRMCSL, SVKEKDMTK, FYIQMCTEL, DTVNRTHQY) and 3 CD4+ epitopes (KGILGFVFTLTVPSE, EYIMKGVYINTALLN, ILGFVFTLTVPSERG). The universal vaccine comprised 8 CD8+ epitopes: (FMYSDFHFI, GILGFVFTL, ILRGSVAHK, FYIQMCTEL, ILKGKFQTA, YYLEKANKI, VSDGGPNLY, YSHGTGTGY) and the same 3 CD4+ epitopes. Our USA-specific vaccine has a population protection coverage (portion of the population potentially responsive to one or more component epitopes of the vaccine, PPC) of over 96% and 95% coverage of observed influenza subtypes. The universal vaccine has a PPC value of over 97% and 88% coverage of observed subtypes.

MHC class I bound to an immunodominant Theileria parva epitope demonstrates unconventional presentation to T cell receptors

T cell receptor (TCR) recognition of peptide-MHC class I (pMHC) complexes is a crucial event in the adaptive immune response to pathogens. Peptide epitopes often display a strong dominance hierarchy, resulting in focusing of the response on a limited number of the most dominant epitopes. Such T cell responses may be additionally restricted by particular MHC alleles in preference to others. We have studied this poorly understood phenomenon using Theileria parva, a protozoan parasite that causes an often fatal lymphoproliferative disease in cattle. Despite its antigenic complexity, CD8+ T cell responses induced by infection with the parasite show profound immunodominance, as exemplified by the Tp1(214-224) epitope presented by the common and functionally important MHC class I allele N*01301. We present a high-resolution crystal structure of this pMHC complex, demonstrating that the peptide is presented in a distinctive raised conformation. Functional studies using CD8+ T cell clones show that this impacts significantly on TCR recognition. The unconventional structure is generated by a hydrophobic ridge within the MHC peptide binding groove, found in a set of cattle MHC alleles. Extremely rare in all other species, this feature is seen in a small group of mouse MHC class I molecules. The data generated in this analysis contribute to our understanding of the structural basis for T cell-dependent immune responses, providing insight into what determines a highly immunogenic p-MHC complex, and hence can be of value in prediction of antigenic epitopes and vaccine design.

Innate recognition of apoptotic cells:novel apoptotic cell-associated molecular patterns revealed by crossreactivity of anti-LPS antibodies

Cells dying by apoptosis are normally cleared by phagocytes through mechanisms that can suppress inflammation and immunity. Molecules of the innate immune system, the pattern recognition receptors (PRRs), are able to interact not only with conserved structures on microbes (pathogen-associated molecular patterns, PAMPs) but also with ligands displayed by apoptotic cells. We reasoned that PRRs might therefore interact with structures on apoptotic cells-apoptotic cell-associated molecular patterns (ACAMPs)-that are analogous to PAMPs. Here we show that certain monoclonal antibodies raised against the prototypic PAMP, lipopolysaccharide (LPS), can crossreact with apoptotic cells. We demonstrate that one such antibody interacts with a constitutively expressed intracellular protein, laminin-binding protein, which translocates to the cell surface during apoptosis and can interact with cells expressing the prototypic PRR, mCD14 as well as with CD14-negative cells. Anti-LPS cross reactive epitopes on apoptotic cells colocalised with annexin V-and C1q-binding sites on vesicular regions of apoptotic cell surfaces and were released associated with apoptotic cell-derived microvesicles (MVs). These results confirm that apoptotic cells and microbes can interact with the immune system through common elements and suggest that anti-PAMP antibodies could be used strategically to characterise novel ACAMPs associated not only with apoptotic cells but also with derived MVs. © 2013 Macmillan Publishers Limited All rights reserved.

EpiJen:a server for multistep T cell epitope prediction

Background - The main processing pathway for MHC class I ligands involves degradation of proteins by the proteasome, followed by transport of products by the transporter associated with antigen processing (TAP) to the endoplasmic reticulum (ER), where peptides are bound by MHC class I molecules, and then presented on the cell surface by MHCs. The whole process is modeled here using an integrated approach, which we call EpiJen. EpiJen is based on quantitative matrices, derived by the additive method, and applied successively to select epitopes. EpiJen is available free online. Results - To identify epitopes, a source protein is passed through four steps: proteasome cleavage, TAP transport, MHC binding and epitope selection. At each stage, different proportions of non-epitopes are eliminated. The final set of peptides represents no more than 5% of the whole protein sequence and will contain 85% of the true epitopes, as indicated by external validation. Compared to other integrated methods (NetCTL, WAPP and SMM), EpiJen performs best, predicting 61 of the 99 HIV epitopes used in this study. Conclusion - EpiJen is a reliable multi-step algorithm for T cell epitope prediction, which belongs to the next generation of in silico T cell epitope identification methods. These methods aim to reduce subsequent experimental work by improving the success rate of epitope prediction.

Modeling the peptide-T cell receptor interaction by the comparative molecular similarity indices analysis-soft independent modeling of class analogy technique

A set of 38 epitopes and 183 non-epitopes, which bind to alleles of the HLA-A3 supertype, was subjected to a combination of comparative molecular similarity indices analysis (CoMSIA) and soft independent modeling of class analogy (SIMCA). During the process of T cell recognition, T cell receptors (TCR) interact with the central section of the bound nonamer peptide; thus only positions 4−8 were considered in the study. The derived model distinguished 82% of the epitopes and 73% of the non-epitopes after cross-validation in five groups. The overall preference from the model is for polar amino acids with high electron density and the ability to form hydrogen bonds. These so-called “aggressive” amino acids are flanked by small-sized residues, which enable such residues to protrude from the binding cleft and take an active role in TCR-mediated T cell recognition. Combinations of “aggressive” and “passive” amino acids in the middle part of epitopes constitute a putative TCR binding motif

The administration route is decisive for the ability of the vaccine adjuvant CAF09 to induce antigen-specific CD8+ T-cell responses:the immunological consequences of the biodistribution profile

A prerequisite for vaccine-mediated induction of CD8+ T-cell responses is the targeting of dendritic cell (DC) subsets specifically capable of cross-presenting antigen epitopes to CD8+ T cells. Administration of a number of cationic adjuvants via the intraperitoneal (i.p.) route has been shown to result in strong CD8+ T-cell responses, whereas immunization via e.g. the intramuscular (i.m.) or subcutaneous (s.c.) routes often stimulate weak CD8+ T-cell responses. The hypothesis for this is that self-drainage of the adjuvant/antigen to the lymphoid organs, which takes place upon i.p. immunization, is required for the subsequent activation of cross-presenting lymphoid organ-resident CD8α+ DCs. In contrast, s.c. or i.m. immunization usually results in the formation of a depot at the site of injection (SOI), which hinders the self-drainage and targeting of the vaccine to cross-presenting CD8α+ DCs. We investigated this hypothesis by correlating the biodistribution pattern and the adjuvanticity of the strong CD8+ T-cell inducing liposomal cationic adjuvant formulation 09 (CAF09), which is composed of dimethyldioctadecylammonium bromide/monomycoloyl glycerol liposomes with polyinosinic:polycytidylic acid electrostatically adsorbed to the surface. Biodistribution studies with radiolabeled CAF09 and a surface-adsorbed model antigen [ovalbumin (OVA)] showed that a significantly larger fraction of the vaccine dose localized in the draining lymph nodes (dLNs) and the spleen 6 h after i.p. immunization, as compared to after i.m. immunization. Studies with fluorescently labelled OVA + CAF09 demonstrated a preferential association of OVA + CAF09 to DCs/monocytes, as compared to macrophages and B cells, following i.p. immunization. Administration of OVA + CAF09 via the i.p. route did also result in DC activation, whereas no DC activation could be measured within the same period with unadjuvanted OVA and OVA + CAF09 administered via the s.c. or i.m. routes. In the dLNs, the highest level of activated, cross-presenting CD8α+ DCs was detected at 24 h post immunization, whereas an influx of activated, migrating and cross-presenting CD103+ DCs to the dLNs could be measured after 48 h. This suggests that the CD8α+ DCs are activated by self-draining OVA + CAF09 in the lymphoid organs, whereas the CD103+ DCs are stimulated by the OVA + CAF09 at the SOI. These results support the hypothesis that the self-drainage of OVA + CAF09 to the draining LNs is required for the activation of CD8α+ DCs, while the migratory CD103+ DCs may play a role in sustaining the subsequent induction of strong CD8+ T-cell responses.