Examination of possible structural constraints of MHC-binding peptides by assessment of their native structure within their source proteins

Integral Use of Immunopeptidomics and Immunoinformatics for the Characterization of Antigen Presentation and Rational Identification of BoLA-DR-Presented Peptides and Epitopes

MHC peptide binding and presentation is the most selective event defining the landscape of T cell epitopes. Consequently, understanding the diversity of MHC alleles in a given population and the parameters that define the set of ligands that can be bound and presented by each of these alleles (the immunopeptidome) has an enormous impact on our capacity to predict and manipulate the potential of protein Ags to elicit functional T cell responses. Liquid chromatography-mass spectrometry analysis of MHC-eluted ligand data has proven to be a powerful technique for identifying such peptidomes, and methods integrating such data for prediction of Ag presentation have reached a high level of accuracy for both MHC class I and class II. In this study, we demonstrate how these techniques and prediction methods can be readily extended to the bovine leukocyte Ag class II DR locus (BoLA-DR). BoLA-DR binding motifs were characterized by eluted ligand data derived from bovine cell lines expressing a range of DRB3 alleles prevalent in Holstein-Friesian populations. The model generated (NetBoLAIIpan, available as a Web server at www.cbs.dtu.dk/services/NetBoLAIIpan) was shown to have unprecedented predictive power to identify known BoLA-DR-restricted CD4 epitopes. In summary, the results demonstrate the power of an integrated approach combining advanced mass spectrometry peptidomics with immunoinformatics for characterization of the BoLA-DR Ag presentation system and provide a prediction tool that can be used to assist in rational evaluation and selection of bovine CD4 T cell epitopes.

Protective immunity provided by a new modified SERA protein peptide: its immunogenetic characteristics and correlation with 3D structure

The serine repeat antigen (SERA) protein is a leading candidate molecule for inclusion as a component in a multi-antigen, multi-stage, minimal subunit-based, chemically synthesised anti-malarial vaccine. Peptides having high red blood cell binding affinity (known as HABPs) have been identified in this protein. The 6733 HABP was located in the C-terminal portion of the 47-kDa fragment while HABP 6754 was located in the C-terminal region of the 56-kDa fragment. These conserved HABPs failed to induce an immune response. Critical red blood cell binding residues and/or their neighbours (assessed by glycine-analogue scanning) were replaced by others having the same mass, volume and surface but different polarity, rendering some of them highly immunogenic when assessed by antibody production against the parasite or its proteins and protection-inducers against experimental challenge with a highly infectious Aotus monkey-adapted Plasmodium falciparum strain. This manuscript presents some modified HABPs as vaccine candidate components for enriching our tailor-made anti-malarial vaccine repertoire, as well as their 3D structure obtained by 1H-NMR displaying a short-structured region, differently from the native ones having random structures.

Modeling peptide-protein interactions

Peptide-protein interactions are prevalent in the living cell and form a key component of the overall protein-protein interaction network. These interactions are drawing increasing interest due to their part in signaling and regulation, and are thus attractive targets for computational structural modeling. Here we report an overview of current techniques for the high resolution modeling of peptide-protein complexes. We dissect this complicated challenge into several smaller subproblems, namely: modeling the receptor protein, predicting the peptide binding site, sampling an initial peptide backbone conformation and the final refinement of the peptide within the receptor binding site. For each of these conceptual stages, we present available tools, approaches, and their reported performance. We summarize with an illustrative example of this process, highlighting the success and current challenges still facing the automated blind modeling of peptide-protein interactions. We believe that the upcoming years will see considerable progress in our ability to create accurate models of peptide-protein interactions, with applications in binding-specificity prediction, rational design of peptide-mediated interactions and the usage of peptides as therapeutic agents.

Opportunities and limitations of mouse models humanized for HLA class II antigens

MHC class II molecules are essential for shaping the CD4+ T-cell repertoire in the thymus and for selecting antigenic peptides that are presented to CD4+ T cells in the periphery. A range of different mouse models humanized for HLA class II antigens have been developed to study the regulation of MHC-class II restricted immune responses. These mouse models have been used to identify immunodominant peptides that trigger diseases and to characterize the interactions of T-cell receptors with disease-associated peptides and MHC class II molecules. Peptides presented to CD4+ T cells in these mouse models were shown to be similar to peptides presented to CD4+ T cells in patients who carry the same MHC class II haplotype. Opportunities and limitations associated with these mouse models will be discussed and the potential application of these models for understanding the regulation of antibody responses against factor VIII in hemophilia A will be indicated.

Functional anthology of intrinsic disorder. 2. Cellular components, domains, technical terms, developmental processes, and coding sequence diversities correlated with long disordered regions

Biologically active proteins without stable ordered structure (i.e., intrinsically disordered proteins) are attracting increased attention. Functional repertoires of ordered and disordered proteins are very different, and the ability to differentiate whether a given function is associated with intrinsic disorder or with a well-folded protein is crucial for modern protein science. However, there is a large gap between the number of proteins experimentally confirmed to be disordered and their actual number in nature. As a result, studies of functional properties of confirmed disordered proteins, while helpful in revealing the functional diversity of protein disorder, provide only a limited view. To overcome this problem, a bioinformatics approach for comprehensive study of functional roles of protein disorder was proposed in the first paper of this series (Xie, H.; Vucetic, S.; Iakoucheva, L. M.; Oldfield, C. J.; Dunker, A. K.; Obradovic, Z.; Uversky, V. N. Functional anthology of intrinsic disorder. 1. Biological processes and functions of proteins with long disordered regions. J. Proteome Res. 2007, 5, 1882-1898). Applying this novel approach to Swiss-Prot sequences and functional keywords, we found over 238 and 302 keywords to be strongly positively or negatively correlated, respectively, with long intrinsically disordered regions. This paper describes approximately 90 Swiss-Prot keywords attributed to the cellular components, domains, technical terms, developmental processes, and coding sequence diversities possessing strong positive and negative correlation with long disordered regions.

MHC class II proteins and disease: a structural perspective

MHC class II molecules on the surface of antigen-presenting cells display a range of peptides for recognition by the T-cell receptors of CD4+ T helper cells. Therefore, MHC class II molecules are central to effective adaptive immune responses, but conversely, genetic and epidemiological data have implicated these molecules in the pathogenesis of autoimmune diseases. Indeed, the strength of the associations between particular MHC class II alleles and disease render them the main genetic risk factors for autoimmune disorders such as type 1 diabetes. Here, we discuss the insights that the crystal structures of MHC class II molecules provide into the molecular mechanisms by which sequence polymorphisms might contribute to disease susceptibility.