Modeling and Viewing T Cell Receptors Using TCRmodel and TCR3d

Methods Mol Biol. 2020;2120:197-212. doi: 10.1007/978-1-0716-0327-7_14.


The past decade has seen a rapid increase in T cell receptor (TCR) sequences from single cell cloning and repertoire-scale high throughput sequencing studies. Many of these TCRs are of interest as potential therapeutics or for their implications in autoimmune disease or effective targeting of pathogens. As it is impractical to characterize the structure or targeting of the vast majority of these TCRs experimentally, advanced computational methods have been developed to predict their 3D structures and gain mechanistic insights into their antigen binding and specificity. Here, we describe the use of a TCR modeling web server, TCRmodel, which generates models of TCRs from sequence, and TCR3d, which is a weekly-updated database of all known TCR structures. Additionally, we describe the use of RosettaTCR, which is a protocol implemented in the Rosetta framework that serves as the command-line backend to TCRmodel. We provide an example where these tools are used to analyze and model a therapeutically relevant TCR based on its amino acid sequence.

Keywords: Antigen; Bioinformatics; Immunology; MHC; Rosetta; TCR.

MeSH terms

  • Amino Acid Sequence
  • Animals
  • Databases, Protein
  • Humans
  • Models, Molecular
  • Protein Conformation
  • Receptors, Antigen, T-Cell / chemistry*
  • Software


  • Receptors, Antigen, T-Cell