Structural Framework for Analysis of CD4+ T-Cell Epitope Dominance in Viral Fusion Proteins.

Antigen conformation shapes CD4+ T-cell specificity through mechanisms of antigen processing, and the consequences for immunity may rival those from conformational effects on antibody specificity. CD4+ T cells initiate and control immunity to pathogens and cancer and are at least partly responsible for immunopathology associated with infection, autoimmunity, and allergy. The primary trigger for CD4+ T-cell maturation is the presentation of an epitope peptide in the MHC class II antigen-presenting protein (MHCII), most commonly on an activated dendritic cell, and then the T-cell responses are recalled by subsequent presentations of the epitope peptide by the same or other antigen-presenting cells.

CD4+ T-Cell Epitope Prediction by Combined Analysis of Antigen Conformational Flexibility and Peptide-MHCII Binding Affinity.

Antigen processing in the class II MHC pathway depends on conventional proteolytic enzymes, potentially acting on antigens in native-like conformational states. CD4+ epitope dominance arises from a competition among antigen folding, proteolysis, and MHCII binding. Protease-sensitive sites, linear antibody epitopes, and CD4+ T-cell epitopes were mapped in plague vaccine candidate F1-V to evaluate the various contributions to CD4+ epitope dominance.

The Serpin-like Loop Insertion of Ovalbumin Increases the Stability and Decreases the OVA 323-339 Epitope Processing Efficiency.

Chicken ovalbumin (cOVA) has been studied for decades primarily due to the robust genetic and molecular resources that are available for experimental investigations. cOVA is a member of the serpin superfamily of proteins that function as protease inhibitors, although cOVA does not exhibit this activity. As a serpin, cOVA possesses a protease-sensitive reactive center loop that lies adjacent to the OVA 323-339 CD4+ T-cell epitope.

Deciphering and predicting CD4+ T cell immunodominance of influenza virus hemagglutinin.

The importance of CD4+ T helper (Th) cells is well appreciated in view of their essential role in the elicitation of antibody and cytotoxic T cell responses. However, the mechanisms that determine the selection of immunodominant epitopes within complex protein antigens remain elusive. Here, we used ex vivo stimulation of memory T cells and screening of naive and memory T cell libraries, combined with T cell cloning and TCR sequencing, to dissect the human naive and memory CD4+ T cell repertoire against the influenza pandemic H1 hemagglutinin (H1-HA).

Deimmunizing substitutions in exotoxin domain III perturb antigen processing without eliminating T-cell epitopes.

Effective adaptive immune responses depend on activation of CD4+ T cells via the presentation of antigen peptides in the context of major histocompatibility complex (MHC) class II. The structure of an antigen strongly influences its processing within the endolysosome and potentially controls the identity of peptides that are presented to T cells. A recombinant immunotoxin, comprising exotoxin A domain III (PE-III) from and a cancer-specific antibody fragment, has been developed to manage cancer, but its effectiveness is limited by the induction of neutralizing antibodies.

Structural Basis for CD4+ T Cell Epitope Dominance in Arbo-Flavivirus Envelope Proteins: A Meta-Analysis.

A meta-analysis of CD4+ T cell epitope maps reveals clusters and gaps in envelope-protein (E protein) immunogenicity that can be explained by the likelihood of epitope processing, as determined by E protein three-dimensional structures. Differential processing may be at least partially responsible for variations in disease severity among arbo-flaviruses and points to structural features that modulate protection from disease.

CD4+ T-cell epitope prediction using antigen processing constraints.

T-cell CD4+ epitopes are important targets of immunity against infectious diseases and cancer. State-of-the-art methods for MHC class II epitope prediction rely on supervised learning methods in which an implicit or explicit model of sequence specificity is constructed using a training set of peptides with experimentally tested MHC class II binding affinity. In this paper we present a novel method for CD4+ T-cell eptitope prediction based on modeling antigen-processing constraints.

Comprehensive analysis of contributions from protein conformational stability and major histocompatibility complex class II-peptide binding affinity to CD4+ epitope immunogenicity in HIV-1 envelope glycoprotein.

Unlabelled: Helper T-cell epitope dominance in human immunodeficiency virus type 1 (HIV-1) envelope glycoprotein gp120 is not adequately explained by peptide binding to major histocompatibility complex (MHC) proteins. Antigen processing potentially influences epitope dominance, but few, if any, studies have attempted to reconcile the influences of antigen processing and MHC protein binding for all helper T-cell epitopes of an antigen. Epitopes of gp120 identified in both humans and mice occur on the C-terminal flanks of flexible segments that are likely to be proteolytic cleavage sites.

Protein identification using receptor arrays and mass spectrometry.

Mass spectrometry is one of the main tools for protein identification in complex mixtures. When the sequence of the protein is known, we can check to see if the known mass distribution of peptides for a given protein is present in the recorded mass distribution of the mixture being analyzed. Unfortunately, this general approach suffers from high false-positive rates, since in a complex mixture, the likelihood that we will observe any particular mass distribution is high, whether or not the protein of interest is in the mixture.

A polynomial-time algorithm for de novo protein backbone structure determination from nuclear magnetic resonance data.

We describe an efficient algorithm for protein backbone structure determination from solution Nuclear Magnetic Resonance (NMR) data. A key feature of our algorithm is that it finds the conformation and orientation of secondary structure elements as well as the global fold in polynomial time. This is the first polynomial-time algorithm for de novo high-resolution biomacromolecular structure determination using experimentally recorded data from either NMR spectroscopy or X-ray crystallography.

An algebraic geometry approach to protein structure determination from NMR data.

Our paper describes the first provably-efficient algorithm for determining protein structures de novo, solely from experimental data. We show how the global nature of a certain kind of NMR data provides quantifiable complexity-theoretic benefits, allowing us to classify our algorithm as running in polynomial time. While our algorithm uses NMR data as input, it is the first polynomial-time algorithm to compute high-resolution structures de novo using any experimentally-recorded data, from either NMR spectroscopy or X-Ray crystallography.

High-throughput inference of protein-protein interfaces from unassigned NMR data.

Summary: We cast the problem of identifying protein-protein interfaces, using only unassigned NMR spectra, into a geometric clustering problem. Identifying protein-protein interfaces is critical to understanding inter- and intra-cellular communication, and NMR allows the study of protein interaction in solution. However it is often the case that NMR studies of a protein complex are very time-consuming, mainly due to the bottleneck in assigning the chemical shifts, even if the apo structures of the constituent proteins are known.