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

Abstract

T cell receptors (TCRs) that recognize cancer neoantigens are important for anti-cancer immune responses and immunotherapy. Understanding the structural basis of TCR recognition of neoantigens provides insights into their exquisite specificity and can enable design of optimized TCRs. We determined crystal structures of a human TCR in complex with NRAS Q61K and Q61R neoantigen peptides and HLA-A1 MHC, revealing the molecular underpinnings for dual recognition and specificity versus wild-type NRAS peptide. We then used multiple versions of AlphaFold to model the corresponding complex structures, given the challenge of immune recognition for such methods. Interestingly, one implementation of AlphaFold2 (TCRmodel2) was able to generate accurate models of the complexes, while AlphaFold3 also showed strong performance, although success was lower for other complexes. This study provides insights into TCR recognition of a shared cancer neoantigen, as well as the utility and practical considerations for using AlphaFold to model TCR-peptide-MHC complexes.

SARS-CoV-2 spike does not interact with the T cell receptor or directly activate T cells

“…Computational tools to predict protein structures and interactions are rapidly evolving and easily deployed, particularly with the introduction of AI methods ( 19 , 20 ). However, accurate prediction of novel molecular interactions is still a particular challenge, including for TCRs ( 21 – 23 ), highlighting that experimental validation remains crucial for modeled data.…”