From Conformation to Signal: Structure-Guided Engineering of T-cell Receptors for Enhanced Antigen-specific T-cell Function

Abstract

T-cells recognize cells undergoing malignant transformation or viral infection through the T-cell receptor (TCR). TCR signaling is mediated by conformational transitions at the TCR-CD3 interface, yet the molecular mechanisms governing these dynamics remain unresolved. In this thesis, we combined structural, and computational strategies to re-engineer the TCRα DE loop—a proposed signaling relay—to strengthen CD3δ engagement in its active conformation. Evolutionary analysis of 76 TCRα constant domains (TRAC) and 119 CD3δ homologs suggest co-evolving residues at TCR-CD3δ interface. Structural comparisons between closed (unliganded) and open (pMHC-bound) TCR conformations revealed that antigen engagement redistributes electrostatic complementarity at TCR-CD3δ interface, favoring polar interactions in the open state. Leveraging this insight, we deployed Rosetta FastDesign and ProteinMPNN for optimization of the DE loop at TCRα-CD3δ interface. Rosetta-driven designs prioritized hydrophobic packing efficiency, whereas ProteinMPNN favored charged residues to enhance electrostatic synergy. Despite divergent strategies, both methods converged on critical interfacial residues, generating 20 high-confidence candidates for experimental testing. In parallel, we developed an experimental pipeline in which TCRs were lentivirally transduced into Jurkat cells (WT and NFκB-GFP) and tested for signaling capacity via coculture with HIV(Pol448-456) peptide pulsed HLA-B*35:01-expressing 721.221 antigen-presenting cells (APCs). While lentiviral TCR transduction was successful in both Jurkat lines, signaling assays failed due to the absence of CD8 and CD28—coreceptors required for optimal TCR activation. To address this limitation, we adopted a Jurkat NFAT-Luciferase reporter line (CD8+, CD28+, TCR−), which could potentially restore coreceptor-dependent signaling and provided a robust, specificity-preserving platform to quantify TCR activation. This study attempts to decipher evolutionary and biophysical principles underlying TCR-CD3δ dynamics, delivers a computational framework for engineering TCR conformational transitions, and establishes an experimental pipeline to functionally validate engineered TCRs without altering their antigen specificity. These advances lay the groundwork for reprogramming TCR signaling to enhance therapies against viruses and cancers.