Dear colleagues,
Currently I'm trying to predict probable IgE-binding regions in one of the allergenic proteins and reveal candidate residues for mutation in order to design a hypoallergenic derivative.
I made a prediction of B-cell epitopes with few sequence-based and few structure-based tools. In parallel I predicted the surface-exposed regions in the protein by another software. Moreover, I looked to the homologous protein for which the IgE-binding regions were predicted experimentally and projected these residues on my protein.
Finally, when I tried to integrate the data of all these predictions I've found that they don't match. I'm confused about this. What results should I prefer in the case when data of different predictions don't match? What results are of a higher value?
Would be grateful for any suggestions.
I would trust experimental data the most. Did you consider linear versus conformational epitopes?
The in silico modeling reliability depends a lot on the input data file. Eg do you have a good crystal structure available which you could use to reliably model your specific allergen (eg homolgy >60%)? As you didn't specify the allergen, some allergens undergo a lot of additonal modification eg in the digestive tract.
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