An epitope is the portion of the surface of an antigen that binds to an antibody, or the peptide fragment of a protein antigen that binds to the T lymphocyte antigen receptor when presented by the cognate major histocompatibility protein. The best way to identify an antibody epitope is from a crystal structure of the antibody:antigen complex, where the contacts are evident. There are several servers that attempt to predict epitopes.

TerminologyTerminology

Antibody EpitopesAntibody Epitopes

Antibody epitopes may also be called determinants, which is an historically earlier but equally good term. The term epitope implies that the determinant is on the surface of the antigen ("epi").

T Lymphocyte EpitopesT Lymphocyte Epitopes

It is unfortunate that epitope has caught on as the term to describe the peptide fragments that T cells recognize, since these are not necessarily derived from the surfaces of protein antigens, but may be derived from portions that were buried in the folded protein. The terms cryptotope and unfoldon are almost never used, but are perhaps more descriptive.

CharacteristicsCharacteristics

Antibody epitopes can be made up of discontinuous portions of a protein antigen's sequence, or of a continuous portion. In contrast, T cell epitopes always represent a continuous fragment of the sequence of a protein antigen.

Antibody epitopes can occur on the surfaces of native folded proteins, or equally well on denatured conformations of proteins. Peptides are typically too short to have a well-defined fold, yet sometimes can simulate the epitope, binding to antibodies. T cell epitopes are always peptide fragments, and hence, represent a denatured (unfolded) form of the native protein.

Epitope Prediction ServersEpitope Prediction Servers

In the absence of the crystal structure of an antibody:antigen complex, a common way to identify the epitope recognized by a particular antibody is to display random peptides (for example, using phage display libraries), and then to identify the sequences of the peptides with the highest affinity for the antibody. These sequences can then be used to predict where the epitope lies on the native protein, taking into account that the epitope on the native protein may be discontinuous. In this strategy, the 3D structure of the protein antigen must be known.

EpiSearchEpiSearch

EpiSearch requires as input the sequences of peptides that bind to the antibody in question, and an uploaded 3D model of the protein antigen. It offers an interactive 3D view of the epitopes, in Jmol, as well as a list of possible epitopes. No publication is cited.

Epitopia ServerEpitopia Server

The Epitopia Server predicts immunogenic regions in general. It will accept either a protein sequence, or a 3D protein structure. It "implements a machine learning scheme to rank individual amino acids in the protein, according to their potential of eliciting a humoral immune response". (Thus, it does not require a list of peptides that bind to an antibody of interest.) When a 3D model is submitted, it can be visualized in Jmol colored by predicted immunogenicity. The methods are published[1].

References and NotesReferences and Notes

  1. Rubinstein ND, Mayrose I, Pupko T. A machine-learning approach for predicting B-cell epitopes. Mol Immunol. 2009 Feb;46(5):840-7. Epub 2008 Oct 22. PMID:18947876 doi:10.1016/j.molimm.2008.09.009

Proteopedia Page Contributors and Editors (what is this?)Proteopedia Page Contributors and Editors (what is this?)

Eric Martz, Wayne Decatur