NetTCR - 2.1

Sequence-based prediction of peptide-TCR binding.

NetTCR-2.1 predicts binding probability between a T-cell receptor (TCR) CDR loops and MHC-I peptides

Submit data

Paste in CDR sequences (all the six CDRs or only CDR3 αβ). One TCR sequence per line is required. For each TCR, the different CDR seqiences should be comma separated.
Alternatively, load and example input or upload a file from your local machine.

Only amino acid input is accepted. For detailed instructions, see Instructions tab above.

For an overview of the method and citation information, see Abstract tab.

Sequence submission

Paste the sequence(s):

or load some sample data:
or upload a local file:

Select CDR loops

CDR3 loops   All CDRs

Select one or more peptides

Instructions for NetTCR-2.1

Input format

  • The server only accepts amino acid sequences takes in newspace separated TCR CDR sequences. The CDR sequences should be comma-separated. (Load Example on Submission page for illustration of the format);
  • The sequences should be maximum 30 amino acid long and should contain only uppercase standard amino acid;


  1. Paste CDR sequence(s) into the box, or load an example file, or load a file from your lcoal machine. In case CDR3 is selected, two columns are expexted in the input file; for "All CDRs" option, 6 columns are expexted. The input file should be a text or .csv file with no headers for the columns.
  2. Select the desire CDR3s to use;
  3. Select the peptide(s) to pair the CDR sequences with.
Click the submit button when protein sequences are entered.


Prediction of T cell receptor (TCR) interactions with MHC-peptide complexes remains highly challenging. This challenge is primarily due to three dominant factors: data accuracy, data scarceness, and problem complexity.
Here, we showcase that "shallow" convolutional neural network (CNN) architectures are adequate to deal with the problem complexity imposed by the length variations of TCRs.
We demonstrate that current public bulk CDR3β-pMHC binding data overall is of low quality and that the development of accurate prediction models is contingent on paired α/β TCR sequence data corresponding to at least 150 distinct pairs for each investigated pMHC.
In comparison, models trained on CDR3α or CDR3β data demonstrated a variable and pMHC specific relative performance drop. Together these findings support that T cell specificity is predictable given the availability of accurate and sufficient paired TCR sequence data.


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