MHC-II binding predictions - Tutorial
Guidelines for selecting thresholds (cut-offs) for MHC class I and II binding predictions can be found
How to obtain predictions
This website provides access to predictions of peptide binding to MHC class II molecules. The screenshot below illustrates the steps necessary to make a prediction.
Each of the steps is described in more detail below.
1. Specify sequences:
First specify the sequences you want to scan for binding peptides. The sequences
should either be entered directly into the textarea field labeled "Enter protein sequence(s),
or can be taken from a file that has to be uploaded using the button labeled "Browse". Please
enter no more then 200 FASTA sequences or upload file size less than or equal to 10 MB per query.
The sequences can be supplied in three different formats:
- Space separated sequences
- One continuous sequence
- FASTA format
The format of the sequences can be specified explicitly using the list box
labeled "Choose sequence format". If that list box is set to "auto detect format", the
input will be interpreted as FASTA if an opening ">" character is found, or as
a continuous sequence otherwise.
All sequences have to be amino acids specified in single letter code (
2. Choose a prediction method:
The prediction method list box allows choosing between nine currently implemented
MHC class II binding prediction methods:
The default selection IEDB Recommended is provided.
Based on availability of predictors and previously observed predictive performance,
this selection tries to use the best possible method for a given MHC molecule.
The selection IEDB Recommended uses the Consensus approach, combining NN-align, SMM-align, CombLib and Sturniolo
if any corresponding predictor is available for the molecule, otherwise NetMHCIIpan is used.
The Consensus approach considers a combination of any three of the four methods, if available, where Sturniolo as a final choice.
The expected predictive performances are based on large scale evaluations of the performance of the MHC class II
binding predictions: a 2008
study based on over 10,000
binding affinities, a 2010
study based on over 40,000
binding affinities and a 2012
Supplementary information for evaluation of predictive tools are available for
Of note, we fully expect the IEDB recommendation to change as we perform larger benchmarks
of newly developed methods on blind datasets to determine an accurate assessment of prediction quality.
Version method(s) used in the tool:
|SMM_align (NetMHCII) *||1.1||DTU|
|NN_align (NetMHCII) *||2.2||DTU|
|NN_align (NetMHCII) *||2.3||DTU|
* NetMHCII has changed method name from SMM_align to NN_align after version 2.2.
3. Specify what to make predictions for:
Predictions are limited to alleles that are currently covered by specific
prediction methods. Selection of a particular prediction method will generate
a list of available alleles. User can then choose a specific allele to make
predictions or upload a file containing list of alleles. User can also choose
1 or multiple peptide length(s) for the prediction.
• Select α and β chains separately:
When the locus selected is either HLA-DP or HLA-DQ, checking the box "Select α & β chains separately if applicable" enables you to choose
alpha and beta chains separately, which makes it possible for prediction of all different chain combinations. The default (un-checked) selection list only
certain chain combinations.
• Format for the upload allele file:
File should be in simple text format containing an allele in each line (example given below).
Additional information regarding HLA allele frequencies
are also provided.
• Select HLA allele reference set:
When the IEDB recommended option is selected, this box can be checked to select a reference panel of 27 alleles, as described here
• Select "7-allele" reference set:
When the IEDB recommended option is selected, this box can be checked to select a reference panel of 7 alleles, as described in Paul et al, 2015
• Select length:
1 or multiple peptide length(s) can be selected for the prediction. Available length options is from 10 to 30, and the default value is 15. A list of peptides will be automatically generated for predictions by scanning input sequence(s) with user selected length(s).
• Select "asis" length option:
When the box "asis" is selected, the length(s) of input sequence(s) will be used for the prediction. But the length(s) still should be from 10 to 30, and all the other inputs will be ignored for the prediction.
4. Specify the output:
The menus in this section change how the prediction output is displayed. Using the
"Sort peptides by" listbox, the results can be presorted by the order of the peptides
in their source sequence (default) or by their predicted affinity.
To reuse the prediction results in an external program, it is possible to
retrieve the predictions in a plain text format. To do this, choose "Text file" in the
output format listbox.
• Sending the result table in a email:
Inputting your email address is recommended to ensure you could receive the result, especially for those prediction jobs which will take a long time. A email with the result table attached will send to you mail box as well as the result displayed on the web site.
One or multiple email addresses with comma separated could be accepted.
firstname.lastname@example.org, email@example.com, firstname.lastname@example.org ...
Please input your email address for the extremely large predictions because for these jobs we only send the result to users by email. Or download the standalone
to finish these predictions locally.
For additional information regarding how to input your email address in the mhci API, Please look at the help page here
5. Submit the prediction:
This one is easy. Click the submit button, and a result screen similar
to the one below should appear.
Interpreting prediction output
Below is a screenshot of a prediction output page, with three relevant sections
marked that are described in more detail below.
1. Input Sequences:
This table displays the sequences and their names extracted from the user input.
If no names were assigned by the user (which is only possible in FASTA format),
the sequences are numbered in their input order (sequence 1, sequence 2, ...).
2. Prediction output table:
Each row in this table corresponds to one peptide binding prediction. The columns contain the allele the
prediction was made for, the input sequence number (#), start position and end position of the peptide,
its length, the peptide, ('method used' if IEDB recommened method is used and 'percentile rank' for both
consensus and IEDB recommended), the core sequence, the predicted score and percentile rank for combinatorial
library, SMM_align and Sturniolo. The table can be sorted by clicking on the table column headers.
3. Interpreting predicted results:
The predicted output is given in units of IC50
nM for combinatorial library and SMM_align.
Therefore a lower number indicates higher affinity. As a rough guideline, peptides with IC50
<50 nM are considered high affinity, <500 nM intermediate affinity and <5000 nM low affinity. Most known epitopes
have high or intermediate affinity. Some epitopes have low affinity, but no known T-cell epitope has an IC50
value greater than 5000.
The prediction result for Sturniolo is given as raw score. Higher score indicates higher affinity.
For each peptide, a percentile rank for each of the three methods (combinatorial library, SMM_align and Sturniolo)
is generated by comparing the peptide's score against the scores of five million random 15 mers selected from SWISSPROT
And the adjusted percentile rank is the percentile rank adjusted based on the frequency of pepetide lengths.
A small numbered percentile rank indicates high affinity. The median percentile rank of the three methods were
then used to generate the rank for consensus method.
4. Default prediction output table:
By default prediction result is collapsed to show only the Percentile Rank
and Adjusted Rank
when the Consensus method
used. The table can be expanded to display the individual score of different methods used by checking box above result
5. Predicted results:
NetMHCIIpan method is used when Consensus and other methods such as SMM_align, NN_align, COMBLIB and/or Sturniolo are
not available for a particular allele. However, if only one or two of these methods are available, NetMHCIIpan is
used as second or third method.