Modeling and Viewing T Cell Receptors Using TCRmodel and TCR3d.

Methods Mol Biol

Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, MD, USA.

Published: February 2021

AI Article Synopsis

  • The past decade has seen a surge in T cell receptor (TCR) sequences due to advances in single-cell cloning and high-throughput sequencing, revealing their potential in therapy and autoimmune research.
  • Advanced computational tools have been created to predict the 3D structures of TCRs, helping to understand how they identify and interact with antigens, as physically testing all TCRs is often impractical.
  • The TCRmodel web server and the TCR3d database are key resources for modeling TCRs and accessing known TCR structures, along with the RosettaTCR protocol that aids in this analysis; an example shows how these tools effectively model a relevant TCR based on its amino acid sequence.

Article Abstract

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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7224193PMC
http://dx.doi.org/10.1007/978-1-0716-0327-7_14DOI Listing

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