Selection of vaccine-candidate peptides from subsp. by prediction, T-cell line proliferation, and immunogenicity.

subspecies (MAP) is a global concern in modern livestock production worldwide. The available vaccines against paratuberculosis do not offer optimal protection and interfere with the diagnosis of bovine tuberculosis. The aim of this study was to identify immunogenic MAP-specific peptides that do not interfere with the diagnosis of bovine tuberculosis.

Allergen-specific IgG memory B cells are temporally linked to IgE memory responses.

Background: IgE is the least abundant immunoglobulin and tightly regulated, and IgE-producing B cells are rare. The cellular origin and evolution of IgE responses are poorly understood.

Objective: The cellular and clonal origin of IgE memory responses following mucosal allergen exposure by sublingual immunotherapy (SLIT) were investigated.

Diverse and highly cross-reactive T-cell responses in ragweed allergic patients independent of geographical region.

Background: Ragweed frequently causes seasonal allergies in North America and Europe. In the United States, several related ragweed species with diverse geographical distribution cause allergic symptoms. Cross-reactivity towards related ragweed species of IgE and treatment-induced IgG has been demonstrated previously.

MHCcluster, a method for functional clustering of MHC molecules.

The identification of peptides binding to major histocompatibility complexes (MHC) is a critical step in the understanding of T cell immune responses. The human MHC genomic region (HLA) is extremely polymorphic comprising several thousand alleles, many encoding a distinct molecule. The potentially unique specificities remain experimentally uncharacterized for the vast majority of HLA molecules.

In silico peptide-binding predictions of passerine MHC class I reveal similarities across distantly related species, suggesting convergence on the level of protein function.

The major histocompatibility complex (MHC) genes are the most polymorphic genes found in the vertebrate genome, and they encode proteins that play an essential role in the adaptive immune response. Many songbirds (passerines) have been shown to have a large number of transcribed MHC class I genes compared to most mammals. To elucidate the reason for this large number of genes, we compared 14 MHC class I alleles (α1-α3 domains), from great reed warbler, house sparrow and tree sparrow, via phylogenetic analysis, homology modelling and in silico peptide-binding predictions to investigate their functional and genetic relationships.

Bioinformatics identification of antigenic peptide: predicting the specificity of major MHC class I and II pathway players.

Bioinformatics methods for immunology have become increasingly used over the last decade and now form an integrated part of most epitope discovery projects. This wide usage has led to the confusion of defining which of the many methods to use for what problems. In this chapter, an overview is given focusing on the suite of tools developed at the Technical University of Denmark.

Reliable B cell epitope predictions: impacts of method development and improved benchmarking.

The interaction between antibodies and antigens is one of the most important immune system mechanisms for clearing infectious organisms from the host. Antibodies bind to antigens at sites referred to as B-cell epitopes. Identification of the exact location of B-cell epitopes is essential in several biomedical applications such as; rational vaccine design, development of disease diagnostics and immunotherapeutics.

Characterization of HIV-specific CD4+ T cell responses against peptides selected with broad population and pathogen coverage.

CD4+ T cells orchestrate immunity against viral infections, but their importance in HIV infection remains controversial. Nevertheless, comprehensive studies have associated increase in breadth and functional characteristics of HIV-specific CD4+ T cells with decreased viral load. A major challenge for the identification of HIV-specific CD4+ T cells targeting broadly reactive epitopes in populations with diverse ethnic background stems from the vast genomic variation of HIV and the diversity of the host cellular immune system.

Immune epitope database analysis resource.

The immune epitope database analysis resource (IEDB-AR: http://tools.iedb.org) is a collection of tools for prediction and analysis of molecular targets of T- and B-cell immune responses (i.

Predictions versus high-throughput experiments in T-cell epitope discovery: competition or synergy?

Prediction methods as well as experimental methods for T-cell epitope discovery have developed significantly in recent years. High-throughput experimental methods have made it possible to perform full-length protein scans for epitopes restricted to a limited number of MHC alleles. The high costs and limitations regarding the number of proteins and MHC alleles that are feasibly handled by such experimental methods have made in silico prediction models of high interest.

Human leukocyte antigen (HLA) class I restricted epitope discovery in yellow fewer and dengue viruses: importance of HLA binding strength.

Epitopes from all available full-length sequences of yellow fever virus (YFV) and dengue fever virus (DENV) restricted by Human Leukocyte Antigen class I (HLA-I) alleles covering 12 HLA-I supertypes were predicted using the NetCTL algorithm. A subset of 179 predicted YFV and 158 predicted DENV epitopes were selected using the EpiSelect algorithm to allow for optimal coverage of viral strains. The selected predicted epitopes were synthesized and approximately 75% were found to bind the predicted restricting HLA molecule with an affinity, K(D), stronger than 500 nM.

NetMHCcons: a consensus method for the major histocompatibility complex class I predictions.

A key role in cell-mediated immunity is dedicated to the major histocompatibility complex (MHC) molecules that bind peptides for presentation on the cell surface. Several in silico methods capable of predicting peptide binding to MHC class I have been developed. The accuracy of these methods depends on the data available characterizing the binding specificity of the MHC molecules.

NetTurnP--neural network prediction of beta-turns by use of evolutionary information and predicted protein sequence features.

Unlabelled: β-turns are the most common type of non-repetitive structures, and constitute on average 25% of the amino acids in proteins. The formation of β-turns plays an important role in protein folding, protein stability and molecular recognition processes. In this work we present the neural network method NetTurnP, for prediction of two-class β-turns and prediction of the individual β-turn types, by use of evolutionary information and predicted protein sequence features.

NetMHCIIpan-2.0 - Improved pan-specific HLA-DR predictions using a novel concurrent alignment and weight optimization training procedure.

Background: Binding of peptides to Major Histocompatibility class II (MHC-II) molecules play a central role in governing responses of the adaptive immune system. MHC-II molecules sample peptides from the extracellular space allowing the immune system to detect the presence of foreign microbes from this compartment. Predicting which peptides bind to an MHC-II molecule is therefore of pivotal importance for understanding the immune response and its effect on host-pathogen interactions.

State of the art and challenges in sequence based T-cell epitope prediction.

Sequence based T-cell epitope predictions have improved immensely in the last decade. From predictions of peptide binding to major histocompatibility complex molecules with moderate accuracy, limited allele coverage, and no good estimates of the other events in the antigen-processing pathway, the field has evolved significantly. Methods have now been developed that produce highly accurate binding predictions for many alleles and integrate both proteasomal cleavage and transport events.

Prediction of epitopes using neural network based methods.

In this paper, we describe the methodologies behind three different aspects of the NetMHC family for prediction of MHC class I binding, mainly to HLAs. We have updated the prediction servers, NetMHC-3.2, NetMHCpan-2.

Mice, men and MHC supertypes.

Mice are still the most used model organism in initial phases of vaccine design. Bioinformatics is becoming increasingly more important in vaccine development, both for the design of novel simplified epitope-based vaccines and also in order to understand the specific immune response of selected vaccine formulations. Toxoplasma gondii, an intracellular parasite, causes severe neurologic and ocular disease in congenitally infected and immunocompromised individuals.

CPHmodels-3.0--remote homology modeling using structure-guided sequence profiles.

CPHmodels-3.0 is a web server predicting protein 3D structure by use of single template homology modeling. The server employs a hybrid of the scoring functions of CPHmodels-2.

Major histocompatibility complex class I binding predictions as a tool in epitope discovery.

Over the last decade, in silico models of the major histocompatibility complex (MHC) class I pathway have developed significantly. Before, peptide binding could only be reliably modelled for a few major human or mouse histocompatibility molecules; now, high-accuracy predictions are available for any human leucocyte antigen (HLA) -A or -B molecule with known protein sequence. Furthermore, peptide binding to MHC molecules from several non-human primates, mouse strains and other mammals can now be predicted.

MHC class II epitope predictive algorithms.

Major histocompatibility complex class II (MHC-II) molecules sample peptides from the extracellular space, allowing the immune system to detect the presence of foreign microbes from this compartment. To be able to predict the immune response to given pathogens, a number of methods have been developed to predict peptide-MHC binding. However, few methods other than the pioneering TEPITOPE/ProPred method have been developed for MHC-II.

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.

A generic method for assignment of reliability scores applied to solvent accessibility predictions.

Background: Estimation of the reliability of specific real value predictions is nontrivial and the efficacy of this is often questionable. It is important to know if you can trust a given prediction and therefore the best methods associate a prediction with a reliability score or index. For discrete qualitative predictions, the reliability is conventionally estimated as the difference between output scores of selected classes.

Pan-specific MHC class I predictors: a benchmark of HLA class I pan-specific prediction methods.

Motivation: MHC:peptide binding plays a central role in activating the immune surveillance. Computational approaches to determine T-cell epitopes restricted to any given major histocompatibility complex (MHC) molecule are of special practical value in the development of for instance vaccines with broad population coverage against emerging pathogens. Methods have recently been published that are able to predict peptide binding to any human MHC class I molecule.

The peptide-binding specificity of HLA-A*3001 demonstrates membership of the HLA-A3 supertype.

Human leukocyte antigen class I (HLA-I) molecules are highly polymorphic peptide receptors, which select and present endogenously derived peptide epitopes to CD8+ cytotoxic T cells (CTL). The specificity of the HLA-I system is an important component of the overall specificity of the CTL immune system. Unfortunately, the large and rapidly increasing number of known HLA-I molecules seriously complicates a comprehensive analysis of the specificities of the entire HLA-I system (as of June 2008, the international HLA registry holds >1,650 unique HLA-I protein entries).