MHC-II-EpiPred: MHC Class II T Cell Epitope Prediction

Instructions

 

Here is an instruction guide for using the MHC-II-EpiPred Web Server:


Overview

The MHC-II-EpiPred web server provides an intuitive platform for predicting potential MHC class II T cell epitopes from protein sequences. By inputting an amino acid sequence and selecting a window size, users can scan their sequence for potential epitope regions and receive prediction results ranked by probability.

Step-by-Step Guide

1. Inputting a Protein Sequence

  • In the text box, enter the amino acid sequence you wish to analyze.
  • You may also click “Click here for an example” to view a sample input sequence.

2. Setting the Sliding Window Size

  • Use the "Window Size" dropdown menu to select a window length between 8 and 15 amino acids.
  • This determines the size of the peptide segments analyzed for potential MHC class II epitopes.

3. Running the Prediction

  • Click "Submit" to start the prediction process.
  • The sliding window method will scan from the N-terminus to the C-terminus of the input sequence, evaluating each segment for epitope potential.

4. Viewing Prediction Results

  • The predicted epitopes are displayed in the "Potential Epitopes" text box.
  • Each result includes:
    • Epitope Sequence (Predicted peptide)
    • Start Position (Index of the first amino acid in the sequence)
    • End Position (Index of the last amino acid in the sequence)
    • Prediction Probability Score (Confidence level of the prediction)
  • The results are sorted in descending order of probability, showing the most likely epitopes first.

5. Downloading and Saving Results

  • Click "Save Results" to download the prediction results to your local device.
  • If you want to reset the input, click "Clear Input" or "Clear Results".

6. Checking Sequence Length

  • To verify the length of your input sequence, click "Check Sequence Length" before submission.

Contact & Support

For any issues or inquiries regarding the MHC-II-EpiPred Web Server, please contact Sihua Peng: Sihua.Peng@UGA.edu.