Molecular Basis of Peptide Recognition by the TCR: Affinity Differences Calculated Using Large Scale Computing

Abstract

Free energy calculations of the wild-type and the variant human T cell lymphotropic virus type 1 Tax peptide presented by the MHC to the TCR have been performed using large scale massively parallel molecular dynamics simulations. The computed free energy difference (−1.86 ± 0.44 kcal/mol) using alchemical mutation-based thermodynamic integration agrees well with experimental data (−2.9 ± 0.2 kcal/mol). Our simulations exploit state-of-the-art hardware and codes whose algorithms have been optimized for supercomputing platforms. This enables us to simulate larger, more realistic biological systems for longer durations without the imposition of artificial constraints.

Prediction of T-Cell Epitope

“…State A is a peptide with standard sequence (λ = 0) and state B is a peptide with the sequence of interest (λ = 1). The difference in free energy between the two states can be calculated as where means the ensemble average of the differential of system's Hamiltonian with λ. Wan et al calculated the affinity difference between HLA-A0201-peptide A6-TCR and HLA-A0201-peptide P6A-TCR using this method, and they obtained a result that well agreed with the experimental data (96). Even though this method is theoretically consistent, sampling along the ordinary trajectory is not adequate to obtain a reliable ensemble average within a practical calculation time, due to being trapped in energy local minima, especially in a case with strong interactions such as the peptide-MHC complex.…”

Practical Estimation of TCR-pMHC Binding Free-Energy Based on the Dielectric Model and the Coarse-Grained Model

“…This suggests that the exact and efficient evaluation of solvation is important for the affinity calculation (Michielin and Karplus 2002). Other FEP calculations of the wild-type and the variant human T cell lymphotropic virus type 1 Tax peptide presented by the MHC to the TCR have been performed using large scale massively parallel molecular dynamics simulations and the computed free energy difference using alchemical mutationbased thermodynamic integration, which agrees well with experimental data semiquantitatively (Wan, Coveney et al 2005). However, the conventional FEP is still very timeconsuming when searching for so many unknown docking structures because all-atom MD for a large molecular system is a computationally hard task and MD simulations must be done not only in initial and final states but also in many intermediate states.…”

Conformational Dimorphism of Self-peptides and Molecular Mimicry in a Disease-associated HLA-B27 Subtype

“…It seems thus possible that the emergence of autoreactive CTL may be a direct consequence of conformational dimorphisms and dynamic properties of a given peptide within a distinct binding groove (39). The importance of MHC allele-dependent dynamics and different conformational states of a peptide for recognition of a pMHC by T cells is only beginning to be considered (14,19,39,(43)(44)(45). These attributes of peptides bound to MHC molecules may play a role in the context of molecular mimicry and in the differential association of HLA-B27 subtypes such as B*2704 and B*2706 or B*2705 and B*2709 with AS (5,6,12).…”