Using EpiQuest - B

Learn how to use the program by analysing the Demo sequences

You can read how to operate the program EpiQuest-B, and how to use the settings of the program in detail in the Program's Manual. The Demo version of the program offers a number of Demo sequences for analysis, and here we show you how to read and interpret the results, and what difficulties you may encounter while using the program. The established B-epitopes for Demo sequences can be found at IEDB collection, as well as the references for the original research articles (unless there is a reference to specific data). It should be noted that we use the definitions of high-< intermediate and low antigenicity epitopes in accordance to their description in IEDB.

Introduction

Ro ribonucleoprotein

Ro is an excellent demo sequence and it contains multiple and well characterized epitopes. Moreover, a standard task is not to establish one epitope but to correctly predict multiple epitopes in silico within a protein's sequence and to characterize their relative strength with a minimum of false-positive results.

Presented below is the histogram of antigenicity distribution for linear sequences of Ro protein. The known epitopes, irrespective of their strength, are indicated by red frames. while the predicted epitopes are shown as the peaks in histogram and red bars below the sequences. To view a full-size image< please click on the picture.

We can see that the program correctly predicts practically all epitopes of Ro. Some of the predicted epitopes should be excluded on the basis of their non-exposure at the molecule's surface (as indicated by accessibility analysis, blue bars showing the exposed regions).

These are the epitopes predicted in Ro sequence in tabular from. The hidden sequences are indicated. The sequences of known epitopes are indicated in red within the sequences of the predicted ones.

Alpha-S2 Casein

Analysis of Alpha-S2 casein sequence predicts a number of epitopes of different antigenicity. the best one contains the sequence of the established immunodominant epitope in this protein, although the program shows wider area than the established epitope.

To isolate the most antigenic area, you may increase the cut-off threshold of the program (T) thus obtaining shorter epitopes.

Try also changing settings to even higher T (2,3) and see the changes in the histogram and tabular results.

To zoom, please click on the image.

Major pollen allergen Jun a1

Sometimes the presence of highly non-antigenic sequences right after the epitope may cause the shift of the position of the detected epitope due to the influence of the strongly negative context.

We can see this effect in presented example for analysis of Jun a1 sequence, where the dominant epitope is predicted correctly, but a part of the actual epitope sequence is excluded from the predicted one (click on image to zoom up).

Therefore we recommend to run, the analysis with Frame 3, 6, and 9 to see whether the context has no influence on the position of the epitope. In most cases the position will be the same; when you observe the effect of shifting epitope, it's better to include all sequences you see at different frame sizes into selected epitopes.

Outer membrane protein P5 (Fimbrin)

This example demonstrates that sometimes the predicted sequence may be represented by two fused epitopes. To better discriminate between them we recommend raise the threshold. We do not discuss here why one of two main epitopes predicted is not immunogenic in actual immune response to the molecule (run along the accessibility analysis). It should also be said that the known epitope in this case is not the actual sequence, but a wider area established during screening of sera with overlapping peptides.

Alpha/beta-gliadin A-V (Prolamin)

Here we show how several overlapping linear epitopes may be reflected in histogram obtained with EpiQuest-B. The immunodominant linear sequence of Prolamin is predicted correctly, but one peak may unite several epitopes.

We have presented the analysis of several cases of demo sequences, illustrating the accuracy of the prediction and how the results are affected by the settings for analysis. For more examples, visit our blog.

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