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Linear B-cell Epitopes (linear + b-cell_epitope)

Distribution by Scientific Domains

Chemistry	75%

Selected Abstracts

Preferential recognition of the phosphorylated major linear B-cell epitope of La/SSB 349,368aa by anti-La/SSB autoantibodies from patients with systemic autoimmune diseases

CLINICAL & EXPERIMENTAL IMMUNOLOGY, Issue 3 2006
A. G. Terzoglou
Summary Sera from patients with primary Sjögren Syndrome (pSS) or Systemic Lupus Erythematosus (SLE) often contain autoantibodies directed against La/SSB. The sequence 349,368aa represents the major B-cell epitope of La/SSB, also it contains, at position 366, a serine aminoacid residue which constitutes the main phosphorylation site of the protein. In this study we investigated the differential recognition of the 349,368aa epitope and its phosphorylated form by antibodies found in sera from patients with systemic autoimmune diseases. Peptides corresponding to the sequence of the unphosphorylated (pep349,368aa) and the phosphorylated form (pep349,368aaPh) of the La/SSB epitope 349,368aa, as well as to a truncated form spanning the sequence 349,364aa and lacking the phosphorylation site (pep349,364aa), were synthesized. Sera from 53 patients with pSS and SLE with anti-La/SSB specificity, 30 patients with pSS and SLE without anti-La/SSB antibodies, 25 patients with rheumatoid arthritis and 32 healthy individuals were investigated by ELISA experiments. Autoantibodies to pep349,368aaPh were detected in sera of anti-La/SSB positive patients with a higher prevalence compared to the pep349,368aa (66%versus 45%). Pep349,368aaPh inhibited the antibody binding almost completely (92%), while pep349,368aa inhibited the binding only partially (45%). Anti-La/SSB antibodies presented a higher relative avidity for the phosphorylated than the unphosphorylated peptide. Immunoadsorbent experiments using the truncated peptide pep349,364aa indicated that the flowthrough showed a selective specificity for pep349,368aaPh, while the eluted antibodies reacted with both peptide analogues of the La/SSB epitope. These data suggest that sera from pSS and SLE patients with anti-La/SSB reactivity possess autoantibodies that bind more frequently and with a higher avidity to the phosphorylated major B-cell epitope of the molecule. [source]

Machine learning approaches for prediction of linear B-cell epitopes on proteins

JOURNAL OF MOLECULAR RECOGNITION, Issue 3 2006
Johannes Söllner
Abstract Identification and characterization of antigenic determinants on proteins has received considerable attention utilizing both, experimental as well as computational methods. For computational routines mostly structural as well as physicochemical parameters have been utilized for predicting the antigenic propensity of protein sites. However, the performance of computational routines has been low when compared to experimental alternatives. Here we describe the construction of machine learning based classifiers to enhance the prediction quality for identifying linear B-cell epitopes on proteins. Our approach combines several parameters previously associated with antigenicity, and includes novel parameters based on frequencies of amino acids and amino acid neighborhood propensities. We utilized machine learning algorithms for deriving antigenicity classification functions assigning antigenic propensities to each amino acid of a given protein sequence. We compared the prediction quality of the novel classifiers with respect to established routines for epitope scoring, and tested prediction accuracy on experimental data available for HIV proteins. The major finding is that machine learning classifiers clearly outperform the reference classification systems on the HIV epitope validation set. Copyright © 2006 John Wiley & Sons, Ltd. [source]

Prediction of residues in discontinuous B-cell epitopes using protein 3D structures

PROTEIN SCIENCE, Issue 11 2006
Pernille Haste Andersen
Abstract Discovery of discontinuous B-cell epitopes is a major challenge in vaccine design. Previous epitope prediction methods have mostly been based on protein sequences and are not very effective. Here, we present DiscoTope, a novel method for discontinuous epitope prediction that uses protein three-dimensional structural data. The method is based on amino acid statistics, spatial information, and surface accessibility in a compiled data set of discontinuous epitopes determined by X-ray crystallography of antibody/antigen protein complexes. DiscoTope is the first method to focus explicitly on discontinuous epitopes. We show that the new structure-based method has a better performance for predicting residues of discontinuous epitopes than methods based solely on sequence information, and that it can successfully predict epitope residues that have been identified by different techniques. DiscoTope detects 15.5% of residues located in discontinuous epitopes with a specificity of 95%. At this level of specificity, the conventional Parker hydrophilicity scale for predicting linear B-cell epitopes identifies only 11.0% of residues located in discontinuous epitopes. Predictions by the DiscoTope method can guide experimental epitope mapping in both rational vaccine design and development of diagnostic tools, and may lead to more efficient epitope identification. [source]