Asymmetric framework motion of TCRαß controls load-dependent peptide discrimination.

Mechanical force is critical for the interaction between an αß T cell receptor (TCR) and a peptide-bound major histocompatibility complex (pMHC) molecule to initiate productive T-cell activation. However, the underlying mechanism remains unclear. We use all-atom molecular dynamics simulations to examine the A6 TCR bound to HLA-A*02:01 presenting agonist or antagonist peptides under different extensions to simulate the effects of applied load on the complex, elucidating their divergent biological responses. We found that TCR α and ß chains move asymmetrically, which impacts the interface with pMHC, in particular the peptide-sensing CDR3 loops. For the wild-type agonist, the complex stabilizes in a load-dependent manner while antagonists destabilize it. Simulations of the Cß FG-loop deletion, which reduces the catch bond response, and simulations with in silico mutant peptides further support the observed behaviors. The present results highlight the combined role of interdomain motion, fluctuating forces, and interfacial contacts in determining the mechanical response and fine peptide discrimination by a TCR, thereby resolving the conundrum of nearly identical crystal structures of TCRαß-pMHC agonist and antagonist complexes.

Asymmetric framework motion of TCRαß controls load-dependent peptide discrimination.

Mechanical force is critical for the interaction between an αßT cell receptor (TCR) and a peptide-bound major histocompatibility complex (pMHC) molecule to initiate productive T-cell activation. However, the underlying mechanism remains unclear. We use all-atom molecular dynamics simulations to examine the A6 TCR bound to HLA-A*02:01 presenting agonist or antagonist peptides under different extensions to simulate the effects of applied load on the complex, elucidating their divergent biological responses. We found that TCR α and ß chains move asymmetrically, which impacts the interface with pMHC, in particular the peptide-sensing CDR3 loops. For the wild-type agonist, the complex stabilizes in a load-dependent manner while antagonists destabilize it. Simulations of the Cß FG-loop deletion, which reduces the catch bond response, and simulations with in silico mutant peptides further support the observed behaviors. The present results highlight the combined role of interdomain motion, fluctuating forces, and interfacial contacts in determining the mechanical response and fine peptide discrimination by a TCR, thereby resolving the conundrum of nearly identical crystal structures of TCRαß-pMHC agonist and antagonist complexes.

Building a three-dimensional model of early-stage zebrafish embryo brain.

We introduce a computational approach to build three-dimensional (3D) surface mesh models of the early-stage zebrafish brain primordia from time-series microscopy images. The complexity of the early-stage brain primordia and lack of recognizable landmarks pose a distinct challenge for feature segmentation and 3D modeling. Additional difficulty arises because of noise and variations in pixel intensity. We overcome these by using a hierarchical approach in which simple geometric elements, such as "beads" and "bonds," are assigned to represent local features and their connectivity is used to smoothen the surface while retaining high-curvature regions. We apply our method to build models of two zebrafish embryo phenotypes at discrete time points between 19 and 28 h post-fertilization and collect measurements to quantify development. Our approach is fast and applicable to building models of other biological systems, as demonstrated by models from magnetic resonance images of the human fetal brain. The source code, input scripts, sample image files, and generated outputs are publicly available on GitHub.