Quantifying conformational changes in the TCR:pMHC-I binding interface

Abstract

Background: T cells form one of the key pillars of adaptive immunity. Using their surface bound T cell antigen receptors (TCRs), these cells screen millions of antigens presented by major histocompatibility complex (MHC) or MHC-like molecules. In other protein families, the dynamics of protein-protein interactions have important implications for protein function. Case studies of TCR:class I peptide-MHCs (pMHC-Is) structures have reported mixed results on whether the binding interfaces undergo conformational change during engagement and no robust statistical quantification has been done to generalise these results. Thus, it remains an open question of whether movement occurs in the binding interface that enables the recognition and activation of T cells.

Methods: In this work, we quantify the conformational changes in the TCR:pMHC-I binding interface by creating a dataset of 391 structures, comprising 22 TCRs, 19 MHC alleles, and 79 peptide structures in both unbound (apo) and bound (holo) conformations.

Results: In support of some case studies, we demonstrate that all complementarity determining region (CDR) loops move to a certain extent but only CDR3α and CDR3β loops modify their shape when binding pMHC-Is. We also map the contacts between TCRs and pMHC-Is, generating a novel fingerprint of TCRs on MHC molecules and show that the CDR3α tends to bind the N-terminus of the peptide and the CDR3β tends to bind the C-terminus of the peptide. Finally, we show that the presented peptides can undergo conformational changes when engaged by TCRs, as has been reported in past literature, but novelly show these changes depend on how the peptides are anchored in the MHC binding groove.

Conclusions: Our work has implications in understanding the behaviour of TCR:pMHC-I interactions and providing insights that can be used for modelling Tcell antigen specificity, an ongoing grand challenge in immunology.

Keywords: HLA; MHC; T cell antigen specificity; TCR; conformational changes; peptide; structural biology.

Figure 1

Description of TCRs and pMHC-Is in the apo-holo analysis dataset. (A) Pairings of V genes used by the TCRs in the analysis. (B) Proportion of different MHC alleles in the dataset. (C) Clustering of peptides in the dataset based on sequence identity. Clusters are formed from peptides with 70% sequence identity and each peptide is coloured by the MHC allele presenting it according to the colouring in panel (B). (D) Comparison of V gene usage between the structure dataset and a background of TCRs taken from OTS. (E) Comparison of CDR lengths between the structure dataset and a background of TCRs taken from OTS. (F) Dataset coverage of canonical loop clusters from the whole STCRDab.

Figure 2

Quantifying the movement of each CDR loop after alignment on the TCR framework regions. (A) An example of CDR movement between the apo PDB ID 4jfh TCR (grey) and the holo PDB ID 4jfd TCR:pMHC-I structure (blue and cyan) as denoted by the yellow arrows. (B) Comparison of each loop between apo and holo states. There is an overall significant difference in the amount of movement each loop undergoes based on the Kruskal-Wallis test (p-value of 1.20×10⁻⁶; significance level < 0.05). (C) Percentage of different movement categories from all CDRs. (D) Comparison of different movement types for each CDR loop. apo:apo refers to changes between different apo structures of the same TCR (10 TCRs), apo:holo refers to changes between apo and holo structures (22 TCRs), and holo:holo refers to changes between different holo structures of the same TCR (30 TCRs). There are significant differences between the movement types based on a p-value of 1.28×10⁻²⁰ from a Kruskal-Wallis test (significance level < 0.05).

Figure 3

Examining the deformation of each CDR loop after superposition of apo and holo forms. (A) An example of loop deformation in the α-chain CDR loops between the apo (grey; PDB ID 2bnu) and holo (blue; PDB ID 2bnr) states. (B) Comparison of each loop between apo and holo states after aligning loops. (C) Per-residue RMSD changes of each CDR loop after aligning loops. The CDR loops are numbered following the IMGT numbering system to account for loops of different lengths. There are cases where only one TCR has a certain IMGT residue and thus no error bars are on those bars. (D) Normalised counts of shifting cluster types between apo and holo states for each type of loop.

Figure 4

Visualizing the contacts made between TCR and pMHC-Is. (A) The contacts made between TCR CDR loops and pMHC-Is. Here, all of the contacts (< 5 Å between heavy atoms) that make up over 1% of an MHC residue contact (denoted by the red line in panel C) for all of the TCRs bound to pMHC-Is in the STCRDab (15) are mapped to a reference MHC molecule (PDB ID 1hhi). Notably, there are no residues dominantly contacted by CDR1β at this threshold. (B) Distribution of contacts made between CDR loops and nonamer-peptides from the STCRDab structures. (C) Distribution of contacts made between CDR loops and MHC molecules from the STCRDab structures.

Figure 5

Quantifying the movement of pMHC-Is between apo and holo states. (A) Comparison of different parts of the pMHC-I complex between apo and holo states. There is a significant difference between these components as reported by a p-value of 3.32×10⁻⁶ from a one-way ANOVA test. (B) Effects of different peptide anchoring strategies on the deformation pattern of each peptide residue between apo and holo states.