Characterizing B-cell epitopes is a fundamental step for understanding the immunological basis of bio-recognition. To date, epitope analyses have either been based on limited structural data, or sequence data alone. In this study, our null hypothesis was that the surface of the antigen is homogeneously antigenic. To test this hypothesis, a large dataset of antibody-antigen complex structures, together with crystal structures of the native antigens, has been compiled. Computational methods were developed and applied to detect and extract physico-chemical, structural, and geometrical properties that may distinguish an epitope from the remaining antigen surface. Rigorous statistical inference was able to clearly reject the null hypothesis showing that epitopes are distinguished from the remaining antigen surface in properties such as amino acid preference, secondary structure composition, geometrical shape, and evolutionary conservation. Specifically, epitopes were found to be significantly enriched with tyrosine and tryptophan, and to show a general preference for charged and polar amino acids. Additionally, epitopes were found to show clear preference for residing on planar parts of the antigen that protrude from the surface, yet with a rugged surface shape at the atom level. The effects of complex formation on the structural properties of the antigen were also computationally characterized and it is shown that epitopes undergo compression upon antibody binding. This correlates with the finding that epitopes are enriched with unorganized secondary structure elements that render them flexible. Thus, this study extends the understanding of the underlying processes required for antibody binding, and reveals new aspects of the antibody-antigen interaction.

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Direct monitoring of primary molecular-binding interactions without the need for secondary reactants would markedly simplify and expand applications of high-throughput label-free detection methods. A simple interferometric technique is presented that monitors the optical phase difference resulting from accumulated biomolecular mass. As an example, 50 spots for each of four proteins consisting of BSA, human serum albumin, rabbit IgG, and protein G were dynamically monitored as they captured corresponding antibodies. Dynamic measurements were made at 26 pg/mm 2 SD per spot and with a detectable concentration of 19 ng/ml. The presented method is particularly relevant for protein microarray analysis because it is label-free, simple, sensitive, and easily scales to high-throughput.dynamic monitoring ͉ optical biosensor ͉ protein microarray ͉ immunoassay ͉ interference

A phage-display library of random peptides is a combinatorial experimental technique that can be harnessed for studying antibody–antigen interactions. In this technique, a phage peptide library is scanned against an antibody molecule to obtain a set of peptides that are bound by the antibody with high affinity. This set of peptides is regarded as mimicking the genuine epitope of the antibody's interacting antigen and can be used to define it. Here we present PepSurf, an algorithm for mapping a set of affinity-selected peptides onto the solved structure of the antigen. The problem of epitope mapping is converted into the task of aligning a set of query peptides to a graph representing the surface of the antigen. The best match of each peptide is found by aligning it against virtually all possible paths in the graph. Following a clustering step, which combines the most significant matches, a predicted epitope is inferred. We show that PepSurf accurately predicts the epitope in four cases for which the epitope is known from a solved antibody–antigen co-crystal complex. We further examine the capabilities of PepSurf for predicting other types of protein–protein interfaces. The performance of PepSurf is compared to other available epitope mapping programs.

Antibodies are an effective line of defense in preventing infectious diseases. Highly potent neutralizing antibodies can intercept a virus before it attaches to its target cell and, thus, inactivate it. This ability is based on the antibodies' specific recognition of epitopes, the sites of the antigen to which antibodies bind. Thus, understanding the antibody/epitope interaction provides a basis for the rational design of preventive vaccines. It is assumed that immunization with the precise epitope, corresponding to an effective neutralizing antibody, would elicit the generation of similarly potent antibodies in the vaccinee. Such a vaccine would be a 'B-cell epitope-based vaccine', the implementation of which requires the ability to backtrack from a desired antibody to its corresponding epitope. In this article we discuss a range of methods that enable epitope discovery based on a specific antibody. Such a reversed immunological approach is the first step in the rational design of an epitope-based vaccine. Undoubtedly, the gold standard for epitope definition is x-ray analyses of crystals of antigen:antibody complexes. This method provides atomic resolution of the epitope; however, it is not readily applicable to many antigens and antibodies, and requires a very high degree of sophistication and expertise. Most other methods rely on the ability to monitor the binding of the antibody to antigen fragments or mutated variations. In mutagenesis of the antigen, loss of binding due to point modification of an amino acid residue is often considered an indication of an epitope component. In addition, computational combinatorial methods for epitope mapping are also useful. These methods rely on the ability of the antibody of interest to affinity isolate specific short peptides from combinatorial phage display peptide libraries. The peptides are then regarded as leads for the definition of the epitope corresponding to the antibody used to screen the peptide library. For epitope mapping, computational algorithms have been developed, such as Mapitope, which has recently been found to be effective in mapping conformational discontinuous epitopes. The pros and cons of various approaches towards epitope mapping are also discussed.