Structural characterization and AlphaFold modeling of human T cell receptor recognition of NRAS cancer neoantigens

Daichao Wu1,2, Rui Yin2,3, Guodong Chen1

  • 1Department of Hepatopancreatobiliary Surgery, The First Affiliated Hospital, Laboratory of Structural Immunology, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China.

Science Advances
|November 22, 2024
PubMed

Insights

Understanding T cell receptor (TCR) recognition of cancer neoantigens is key for immunotherapy. This study reveals the structural basis for TCR dual recognition of NRAS neoantigens and evaluates AI models for predicting these interactions.

Area of Science:

  • Immunology
  • Structural Biology
  • Computational Biology

Background:

  • T cell receptors (TCRs) are crucial for recognizing cancer neoantigens, driving anti-cancer immune responses and immunotherapy efficacy.
  • Elucidating the structural basis of TCR-neoantigen recognition is vital for understanding specificity and designing improved TCR-based therapies.

Purpose of the Study:

  • To determine the crystal structures of a human TCR complexed with NRAS Q61K and Q61R neoantigen peptides and HLA-A1.
  • To investigate the molecular mechanisms underlying the TCR's dual recognition and specificity for neoantigenic versus wild-type NRAS peptides.
  • To assess the utility and accuracy of AlphaFold AI models in predicting TCR-peptide-MHC complex structures.

Main Methods:

  • X-ray crystallography was employed to determine the high-resolution structures of the TCR-neoantigen-MHC complexes.
  • Multiple AlphaFold versions, including AlphaFold2 (TCRmodel2) and AlphaFold3, were utilized to model these complexes.
  • Comparative analysis was performed between experimentally determined structures and AI-generated models.

Main Results:

  • Crystal structures revealed the molecular details of a human TCR recognizing both NRAS Q61K and Q61R neoantigen peptides bound to HLA-A1.
  • The structures elucidated the basis for the TCR's dual specificity compared to the wild-type NRAS peptide.
  • AlphaFold2 (TCRmodel2) with enhanced sampling successfully modeled the TCR-peptide-MHC complexes, demonstrating strong performance.
  • AlphaFold3 also showed promising results, though with variable success across different complexes.

Conclusions:

  • This research provides critical structural insights into the recognition of a shared cancer neoantigen by a TCR.
  • The study highlights the potential and practical considerations of employing AlphaFold for modeling TCR-peptide-MHC interactions.
  • Findings can inform the rational design of TCR-based immunotherapies targeting specific cancer neoantigens.

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