EpiQuest-B is a program predicting and ranging domains of linear protein sequences according to their capacity to elicit humoral immune response. The program allows in silico prediction of immunodominant epitopes by assessing their potential antigenicity. This means that it does it equally for linear peptides irrespective of their exposure at the surface of the mature protein molecule and without consideration of post-processing modifications, such as glycosylation, phophorylation, etc.
Antigenicity and Immune dominance of B-epitopes
To be antigenic (that is, being capable to elicit a humoral response) a peptide sequence should possess certain structural features defining its ability to strongly bind to IgG/B-cell receptors. The key idea is that not every peptide sequence may have an antibody that can bind to it with high affinity, even through the long process of B-cell clonal selection and mutation of paratopes sequences (the part of IgG that binds to the epitope). Sometimes IgGs can be raised against a "weak" epitope due to individual response of a particular animal. However, the immunodominant epitopes (that elicit strong, specific response with high affinity IgG in most antigen recipients) can provide an idea of the sequence’s structural base for a strong binding of an antibody.
The Scheme on the right demonstrates that the stronger the binding of the antigen to IgG on follicular dentritic calls, the stronger the stimulation of the clonal expansion of the respective B-cell clone will be.
The scheme is presented after: El Shikh, M.E.M., El Sayed, R.M., Sukumar, S., Szakal, A.K., Tew, J.G., 2010. Activation of B cells by antigens on follicular dendritic cells. Trends Immunol 31, 205–211. https://doi.org/10.1016/j.it.2010.03.002
The algorithm used in EpiQuest-B is based on the assumption that antigenicity of an epitope is defined by the nearest neighbors of amino acids in the sequence. The algorithm is based on the data on the contest for >40.000 individual amino acids in epitope sequences (strong, weak and negative) and tested the usability using >2000 individual epitopes with known immunization data from the immunizations performed in Aptum Biologics or its predecessor companies.
The algorithm of EpiQuest B calculates the probability of an aminoacid to be a part of an antigenic peptide sequence on the basis of aminoacids comprising its context. The Frame for analysis defines how wide context is taken into account (the best results are observed for Frames from 6 to 9 aminoacids.
EpiQuest-B and other prediction programs
To illustrate what EpiQuest-B can predict, the NS1 of Dengue virus 2 is one of the best examples, as its immunodominant epitopes were investigated with high precision and detail (Clin. Vaccine Immunol. 14, 493–504.) In total, there are 8 immunodominant epitopes covering 3 areas in the N-terminal part of the molecule. As can be seen in the Figure below, all 3 areas (indicated by red frames) were detected by EpiQuest-B with high precision, as 3 main peaks in the antigenicity profile of the molecule (the sensitivity of the program can be varied using the Threshold function, T=0 or T=2 in the analysis shown below)
We have compared the plots generated for NS1 by EpiQuest-B and by most prominent epitope/antigenicity defining programs available on the market: Antigenicity by Kolaskar & Tongaonkar, BepiPred, and COBEPro. In Figure (above, left) the antigenicity propensity plot as obtained by current versions of the programs at the default settings. The position of the known immunodominant epitopes is indicated, and it is clear that EpiQuest (Fig. A) is the only program that detects all three immunodominant epitopes areas as the highest values regions. Both algorithms of Kolaskar & Tongaonkar, as well as antigenicity algorithm of COBEPro either miss the epitopes entirely or detect only part of them, ascribing the other part to low antigenicity areas (Fig. B, D). BepiPred seeks only for epitopes probability, and it correctly predicts one of the immunodominant epitopes, although does not ascribe it a high value (Fig. C)
Antigenicity Index (AGI)
The algorithm of EpiQuest-B assigns the Antigenicity Index characterizing the potential of the sequence to elicit humoral immune response and strong high affinity antibodies. The higher the AGI, the more likely the strong humoral response to it. This is something NONE of the existing epitope prediction software is capable of, while EpiQuest-B does it with a high statistical significance (see below).
Two strains of mice (red dots or blue dots) of different haplotypes, were immunized with several types of antigens (NS1 peptide, native NS1 or live DV2), and their pooled sera were tested against a set of overlapping peptides. We have defined AGI for the fragments and have built correlation graphs for AGI vs. ELISA data (the graphs above show clearly the correlation of the observed ELISA titers with predicted AGI for the sequences.)
Moreover, statistical analysis showed that such correlation was significant (and highly significant biologically, R sq.>0.5)
New layout of EpiQuest-B (EpiQuest v4.1 and later) allows to perform the antigenicity profiling of the protein sequences along with other types of analysis (accessibility, complexity, and the other ones).
The results can be presented in the form of a plot or as bars (above) indicating the sequences above a predefined level of the peptide feature .
The data is also presented in tabular form (left), both types of the result data can be easily exported into MS Office or other types of office files.
Analysis of Demo Sequences
For a full overview of the program's capabilities you can use Demo Mode. The Manual for EpiQuest-B explains how to modify settings. You can also see the examples of how to analyse the sequences and interpret the results by visiting the Demo Sequences analysis page.
Scanning epitope collections with B-Scanner
When you need to analyse large numbers of epitopes, from your data collection, or isolated from protein sequences using other programs, or selected by some other criteria, you can use B-scanner, which performs ranking of the peptide epitopes according to their relative antigenicity using the same algorithm and matrixes, as EpiQuest-B.