Introduction
There are several approaches possible when predicting T-epitopes, particularly CTL epitopes. Most of them are related to the prediction of a peptide's ability to bind the groove of MHC molecules, indicating that it can be presented in the context of MHC I or II respectively.
However, less than 5% of peptides binding to MHC demonstrate ANY biological activity, even less being strong, functional epitopes. Whereas, when we plan to use the epitopes for immunization, its highly desirable to use only immunodominant sequences, as the excess of weak epitopes leads to suppression of the immune response (see Chung, B., Stuge, T.B., Murad, J.P., Beilhack, G., Andersen, E., Armstrong, B.D., Weber, J.S., Lee, P.P., 2014. Antigen-Specific Inhibition of High-Avidity T Cell Target Lysis by Low-Avidity T Cells via Trogocytosis, Cell Reports 8, 871–882. )
In contrast to other programs EpiQuest-T predicts areas in the molecule that are likely to contain strong, immunodominant CTL epitopes.
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Strong and Weak T-epitopes
All informatics’ efforts are currently focused on defining in a protein sequence (peptide T-epitopes) capable of binding to the groove of the respected MHC class I or II molecules. However, there is a T - cell receptor, and it also defines the strength (or affinity) to the peptide in the context of the MHC. Based on our experience of sequences capable of eliciting high-affinity antibodies, we focused on the structural characteristics of the peptide epitope: whether it is capable of eliciting a strongly binding TCR. The T (CTL) epitope sequences differ in their capability to induce strongly binding TCR. Irrespective of the fact that they may bind well to the respective MHC.
Therefore, in search of sequences for T-cell epitopes, the program should pick-up the unique features of the sequence that allow it to elicit TCR that would strongly bind to it in the context of the respective MHC.
The Scheme on the left demonstrates that the stronger the binding of the TCR to the peptide (in the context of MHC), the stronger the stimulation of the respective clone.
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
EpiQuest-T is based on our unique algorithm that has identified the typical structural features of a strong T-epitope that should be recognized by TCR in the context of a particular type of MHC molecule.
The algorithm calculates the value of an individual amino acid defined by its context using a Matrix of values. It finds the amino acids that may participate in HLA and TCR binding.
In other words, the Matrix defines the relative value of amino acid in sequence on the basis of close and distant neighbors. It was developed experimentally by analysis of the context for over 10.000 amino acids in known epitopes (strong, low and non-immunogenic).
The software analyzes the linear protein sequence and calculates the probability of an amino acid at a given position in the sequence, depending on the context, to be involved into high affinity (immuno-dominant) CTL epitope depending on its context.
Program output
The program predicts the areas likely to contain immunodominant CTL epitopes and ranks them according to their strength. The results are presented as histogram and tabular results. The prediction is haplotype-restricted, and the peptide is recognized by TCR in the context of particular MHC which contributes to the complex recognition.
In the example presented below of the analysis for the presence of HLA-A2 restricted CTL epitopes in an insulin sequence, we can see that the program finds several areas of potential epitopes of different strength. It well discriminates strong epitopes from both weak and negative areas, the main peak corresponding to the immunodominant CTL epitope in Insulin sequence (the known epitopes indicated below the histogram):
The tabular results show relative immunogenicity (AGI) and antigenicity corrected for the length of the fragment (AGR).
As can be seen, the immunodominant epitope-containing sequence has the highest predicted score.
EpiQuest-T and other programs
To illustrate the key differences between EpiQuest-T and programs based on finding the best MHC binder, we have compared the prediction results between EpiQuest-T and of the program suggested by IEDB in the optimal settings. In both examples shown below the red boxes indicate areas potentially containing functional CTL epitopes, blue boxes indicate the best (highest score) epitopes predicted by IEDB tool, and the purple ones - the actual biologically active epitopes discovered experimentally. Orange frame indicates the best epitope according to either the prediction or to experimental data.
As can be seen, the prediction of EpiQuest-T directly covers the area of the most functionally active CTL epitope in LCV glycoprotein. Among predictions made by IEDB tool (14 best are shown) none correspond to actual functional (either strong or weak) CTL epitopes in this sequence.
It is likely that some of them appear among the lower score predictions, but the example clearly indicates the absence of connections between predictions of the program and functional activity of the CTL epitopes.
For another protein, EpiQuest-T defines the area (the most likely location of immunodominant epitope) that covers exactly the locations of 3 functional CTL epitopes in this protein. Among the best 8 predicted by IEDB tool the lowest one corresponds to the part of the area of the functional epitopes location. The location of the best epitopes predicted by IEDB tool does not contain functional epitopes at all.
The presented examples were analysed for mouse CTL epitopes, H2kB haplotype.
AGI index as predictor of CTL epitope "strength"
The program EpiQuest-T (and its T-Scanner version, more adapted for the analysis of large collections of epitopes) ascribes a value of its potential "strength" to each epitope. The Antigenicity Index (AGI) allows comparing epitopes to each other and selecting the best ones. Below we show two examples of how AGI index is related to the functional activity of CTL epitopes.
In this example, we have compared the functional activity of several mutant epitopes to their AGI defined by EpiQuest-T. The mutant epitopes were different in their ability to activate splenocytes, and their functionality directly correlated to AGI defined by the program.
We have used here two different Matrixes offered by EpiQuest-T for H2kB haplotype: matrix H1 has a selective preference for high activity epitopes, discriminating them better from low and intermediate activity ones. Matrix HI2 has a better recognition of high and intermediate activity epitopes.
All H2kB epitopes from IEDB database were divided according to their activity in functional tests, as described in the database. The AGI index was calculated by EpiQuest-T for the best 8-mer epitope within the epitope sequence (which could range from 8 to 15 amino acids). The figure above shows the values for epitopes in every group and the median value of AGI in every group. The low values for the best epitopes of H2kD haplotype show that the analysis works only for the particular haplotype, the data is MHC-restricted.
Analysis of Demo Sequences
For a full overview of the program's capabilities you can use Demo Mode. The Manual for EpiQuest-T 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 CTL epitopes with T-Scanner
When you want to rank epitopes of the selected group (up to 2000 in one file), you may use T-Scanner.
This program is based on the same algorithm and matrix as EpiQuest-T, but developed for comparing large number of epitopes, either selected by other programs (i.e. the programs predicting MHC-binding or proteolytic cleavage of the sequence in MHCI compartments) or eluted from target cells, etc.
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