Structure‐based design of a T‐cell receptor leads to nearly 100‐fold improvement in binding affinity for pepMHC

Abstract

T cell receptors (TCRs) are proteins that recognize peptides from foreign proteins bound to the Major Histocompatibility Complex (MHC) on the surface of an antigen-presenting cell. This interaction enables the T cells to initiate a cell-mediated immune response to terminate cells displaying the foreign peptide on their MHC. Naturally occurring TCRs have high specificity but low affinity toward the peptide-MHC (pepMHC) complex. This prevents the usage of solubilized TCRs for diagnosis and treatment of viral infections or cancers. Efforts to enhance the binding affinity of several TCRs have been reported in recent years, through randomized libraries and in vitro selection. However, there have been no reported efforts to enhance the affinity via structure-based design, which allows more control and understanding of the mechanism of improvement. Here we have applied structurebased design to a human TCR to improve its pepMHC binding. Our design method evolved based on iterative steps of prediction, testing and generating more predictions based on the new data. The final design function, named ZAFFI, has a correlation of 0.77 and average error of 0.35 kcal/mol with the binding free energies of 26 point mutations for this system that we measured by surface plasmon resonance. Applying the filter we developed to remove non-binding predictions, this correlation increases to 0.85 and the average error decreases to 0.3 kcal/mol. Using this algorithm, we predicted and tested several point mutations that improved binding, with one giving over 6-fold binding improvement. Four of the point mutations that improved binding were then combined to give a mutant TCR that binds the pepMHC 99 times more strongly than the wild-type TCR.

A generalized framework for computational design and mutational scanning of T-cell receptor binding interfaces

“…Application of earlier structure-guided design methods to the B7 TCR Based on previous work with the A6 TCR (Haidar et al, 2009), we recently described a modeling and scoring scheme to predict the structural and energetic effects of point mutations within interfaces with the αβ TCR DMF5 . Using this approach we identified several affinity-enhancing mutations in DMF5 which when combined led to affinity enhancements towards pMHC of up to 400-fold.…”

“…1b). Utilizing the ZAFFI score function first developed for the A6 TCR and refined with the DMF5 TCR (Haidar et al, 2009;Pierce et al, 2014) led to an improved but still weak correlation (R = 0.47; Fig. 1c).…”

“…We collected 96 independent ΔΔG°values resulting from single amino acid mutations from four TCR-pMHC interfaces (A6-Tax 11-19 /HLA-A2; B7-Tax 11-19 /HLA-A2; DMF5-MART1 27-35 /HLA-A2; and DMF5-MART1 26(27L)-35 /HLA-A2). This data originated from our previously published structure-guided design efforts with the A6 and DMF5 TCRs (Haidar et al, 2009;Pierce et al, 2014) as well as our recent double mutant cycle deconstruction of the A6 interface (Piepenbrink et al, 2013). We also included the additional data with B7 described above, and performed new binding measurements in the DMF5-MART1 26(27L)-35 / HLA-A2 interface (Table S1 and Fig.…”

“…Not only can interactions be manipulated in a way that more appropriately addresses peptide specificity, affinity increments can in principle be more tightly controlled. Towards these goals, structureguided design has been used to modify a small number of TCRs (Haidar et al, 2009;Malecek et al, 2014;Pierce et al, 2014;Zoete et al, 2013). Recently, we used structure-guided design to engineer variants of the DMF5 TCR, which has been used clinically in immunotherapy for melanoma and continues to serve as a model TCR for improving cancer immunotherapy (Johnson et al, 2009).…”

“…Recently, we used structure-guided design to engineer variants of the DMF5 TCR, which has been used clinically in immunotherapy for melanoma and continues to serve as a model TCR for improving cancer immunotherapy (Johnson et al, 2009). Building on an approach originally developed for the well-studied A6 TCR (Haidar et al, 2009), we successfully engineered nanomolar affinity variants of DMF5 with altered specificity, and found excellent agreement between prediction and experiment for both structure and affinity .…”