The B-Cell Epitopes (DNASTAR) prediction track uses a bioinformatics approach that uses experimental antibody recognition data. For a set of peptides provided by NeoClone® Biotechnology International, LLC (Madison, WI USA), the antigenicity of each peptide was determined by measuring the relative binding affinity of the peptide against hybridoma-secreted antibodies raised in mice inoculated with the peptide.
The following video is a brief introduction to the B-Cell Epitopes (DNASTAR) track.
Select the track in the Tracks panel. Open the Track Options section, which appears as follows:
- Confidence score threshold – A confidence score with a value from 0 to 1 is assigned to each residue in a protein sequence. By default, residues with a confidence score greater than 0.5 are classified as putative antigenic residues. Changing this threshold value will update the Analysis View accordingly. The default is 0.5.
- Method version – Choose whether to use the Basic or Advanced version of the method. Basic uses the legacy "NeoClone" algorithm from Protean 3D version 10.1, while Advanced uses an updated algorithm.
Click if you wish to return to the default settings.
A cross-validated machine learning approach was used to train two models that predict antigenic and highly antigenic regions. The antigenic models consider sequence-based helix, sheet, beta turn, and flexibility predictions as well as hydropathy, antigenicity, and stability indices when predicting antigenic regions; the highly antigenic models consider a modified combination of secondary structure predictions, hydropathy, antigenicity, and stability.
- Highly antigenic – At least 5% of hybridoma cultures create antibodies that tightly bind the peptide. The highly antigenic model may predict narrow regions of a protein sequence to be antigenic. Use these predictions to highlight regions from the antigenic model with an even greater likelihood of generating an immunological response.
- Antigenic – At least 2.5% of hybridoma cultures create antibodies that tightly bind the peptide. The antigenic model may predict wide-spanning regions of a protein sequence to be antigenic. Increase the threshold value (e.g. 0.75) to focus your analysis on regions with a higher antigenic confidence level.
- Non-antigenic – Less than 2.5% of hybridoma cultures create antibodies that tightly bind the peptide.
Need more help with this?