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.

MHCPred : a server for quantitative prediction of peptide-MHC binding

Accurate T-cell epitope prediction is a principal objective of computational vaccinology. As a service to the immunology and vaccinology communities at large, we have implemented, as a server on the World Wide Web, a partial least squares-base multivariate statistical approach to the quantitative prediction of peptide binding to major histocom-patibility complexes (MHC), the key checkpoint on the antigen presentation pathway within adaptive,cellular immunity. MHCPred implements robust statistical models for both Class I alleles (HLA-A*0101, HLA-A*0201, HLA-A*0202, HLA-A*0203,HLA-A*0206, HLA-A*0301, HLA-A*1101, HLA-A*3301, HLA-A*6801, HLA-A*6802 and HLA-B*3501) and Class II alleles (HLA-DRB*0401, HLA-DRB*0401and HLA-DRB* 0701).

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.

Development of plasmid dna formulations for application as microspheric dna vaccines

The advent of DNA vaccines has heralded a new technology allowing the design and elicitation of immune responses more adequate for a wider range of pathogens. The formulation of these vaccines into the desired dosage forms extends their capability in terms of stability, routes of administration and efficacy. This thesis describes an investigation into the fabrication of plasmid DNA, the active principle of DNA vaccines, into microspheres, based on the tenet of an increased cellular uptake of microparticulate matter by phagocytic cells. The formulation of plasmid DNA into microspheres using two methods, is presented. Formulation of microspheric plasmid DNA using the double emulsion solvent evaporation method and a spray-drying method was explored. The former approach involves formation of a double emulsion, by homogenisation. This method produced microspheres of uniform size and smooth morphology, but had a detrimental effect on the formulated DNA. The spray-drying method resulted in microspheres with an improved preservation of DNA stability. The use of polyethylenimine (PEI) and stearylamine (SA) as agents in the microspheric formulation of plasmid DNA is a novel approach to DNA vaccine design. Using these molecules as model positively-charged agents, their influence on the characteristics of the microspheric formulations was investigated. PEI improved the entrapment efficiency of the plasmid DNA in microspheres, and has minimal effect on either the surface charge, morphology or size distribution of the formulations. Stearylamine effected an increase in the entrapment efficiency and stability of the plasmid DNA and its effect on the micropshere morphology was dependent on the method of preparation. The differences in the effects of the two molecules on microsphere formulations may be attributable to their dissimilar physico-chemical properties. PEI is water-soluble and highly-branched, while SA is hydrophobic and amphipathic. The positive charge of both molecules is imparted by amine functional groups. Preliminary data on the in vivo application of formulated DNA vaccine, using hepatitis B plasmid, showed superior humoral responses to the formulated antigen, compared with free (unformulated) antigen.

Disulfiram/copper complex inhibiting NFκB activity and potentiating cytotoxic effect of gemcitabine on colon and breast cancer cell lines

Most of the gemcitabine (dFdC) resistant cell lines manifested high NF?B activity. The NF?B activity can be induced by dFdC and 5-FU exposure. The chemosensitizing effect of disulfiram (DS), an anti-alcoholism drug and NF?B inhibitor, and copper (Cu) on the chemoresistant cell lines was examined. The DS/Cu complex significantly enhanced the cytotoxicity of dFdC (resistant cells: 12.2–1085-fold) and completely reversed the dFdC resistance in the resitant cell lines. The dFdC-induced NF?B activity was markedly inhibited by DS/Cu complex. The data from this study indicated that DS may be used in clinic to improve the therapeutic effect of dFdC in breast and colon cancer patients.

Toward the prediction of class I and II mouse major histocompatibility complex-peptide-binding affinity:in silico bioinformatic step-by-step guide using quantitative structure-activity relationships

Quantitative structure-activity relationship (QSAR) analysis is a cornerstone of modern informatics. Predictive computational models of peptide-major histocompatibility complex (MHC)-binding affinity based on QSAR technology have now become important components of modern computational immunovaccinology. Historically, such approaches have been built around semiqualitative, classification methods, but these are now giving way to quantitative regression methods. We review three methods--a 2D-QSAR additive-partial least squares (PLS) and a 3D-QSAR comparative molecular similarity index analysis (CoMSIA) method--which can identify the sequence dependence of peptide-binding specificity for various class I MHC alleles from the reported binding affinities (IC50) of peptide sets. The third method is an iterative self-consistent (ISC) PLS-based additive method, which is a recently developed extension to the additive method for the affinity prediction of class II peptides. The QSAR methods presented here have established themselves as immunoinformatic techniques complementary to existing methodology, useful in the quantitative prediction of binding affinity: current methods for the in silico identification of T-cell epitopes (which form the basis of many vaccines, diagnostics, and reagents) rely on the accurate computational prediction of peptide-MHC affinity. We have reviewed various human and mouse class I and class II allele models. Studied alleles comprise HLA-A*0101, HLA-A*0201, HLA-A*0202, HLA-A*0203, HLA-A*0206, HLA-A*0301, HLA-A*1101, HLA-A*3101, HLA-A*6801, HLA-A*6802, HLA-B*3501, H2-K(k), H2-K(b), H2-D(b) HLA-DRB1*0101, HLA-DRB1*0401, HLA-DRB1*0701, I-A(b), I-A(d), I-A(k), I-A(S), I-E(d), and I-E(k). In this chapter we show a step-by-step guide into predicting the reliability and the resulting models to represent an advance on existing methods. The peptides used in this study are available from the AntiJen database (http://www.jenner.ac.uk/AntiJen). The PLS method is available commercially in the SYBYL molecular modeling software package. The resulting models, which can be used for accurate T-cell epitope prediction, will be made are freely available online at the URL http://www.jenner.ac.uk/MHCPred.

Class I T-cell epitope prediction:improvements using a combination of proteasome cleavage, TAP affinity, and MHC binding

Cleavage by the proteasome is responsible for generating the C terminus of T-cell epitopes. Modeling the process of proteasome cleavage as part of a multi-step algorithm for T-cell epitope prediction will reduce the number of non-binders and increase the overall accuracy of the predictive algorithm. Quantitative matrix-based models for prediction of the proteasome cleavage sites in a protein were developed using a training set of 489 naturally processed T-cell epitopes (nonamer peptides) associated with HLA-A and HLA-B molecules. The models were validated using an external test set of 227 T-cell epitopes. The performance of the models was good, identifying 76% of the C-termini correctly. The best model of proteasome cleavage was incorporated as the first step in a three-step algorithm for T-cell epitope prediction, where subsequent steps predicted TAP affinity and MHC binding using previously derived models.