Simulations reveal interactions that distinguish effective from ineffective T cell receptors, suggesting predictive potential for therapy.
We used AlphaFold3 and enhanced-sampling Gaussian accelerated molecular dynamics simulations to investigate the series of 11 class II MHC-restricted T cell receptors (TCRs) in a murine cancer model (Wolf et al., 2024. Sci. Immun. , https://doi.org/10.1126/sciimmunol.adp6529). These TCRs react to an immunodominant antigen, mL9, in a MHC molecule, I-Ek. They were classified into three groups according to their ability to induce tumor remission: effective (H6, H9, H12, and H13), intermediate (H11, H14, H15, and H16), and ineffective (H7, H8, and H10). Both α- and β-chains of effective TCRs demonstrate durable, long-lived (>80% of simulation time) contacts and have highly correlated motion (correlation coefficient > 0.5) with all chains of the p-MHC. In contrast, at least one, and in some cases both, chains of the ineffective TCRs lack stable contacts with the p-MHC, particularly the peptide. To examine the basis of these durable contacts, we performed H-bond and salt-bridge analysis. Both chains of effective TCRs form persistent H-bonds (>50% of simulation time) with both chains of the MHC. By comparison, none or only one chain of ineffective TCRs forms stable H-bonds with MHC. We also observed stable salt bridges in effective TCR-p-MHC complexes that were not present for ineffective TCRs. These interactions lent TCR-p-MHC domains a coherence that the ineffective TCRs lacked. Our findings suggest that a combination of MD simulations and analysis may be useful in distinguishing therapeutically effective from intermediate and ineffective TCR clones.
No takes yet. Share an insight, caveat, or question.
Wu et al. (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: