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T Cell Activation and Clonal Selection

T Cell Activation and Clonal Selection

T cells are integral to our adaptive immune system, recognizing and effectively responding to foreign antigens. T cell activation and clonal selection are pivotal in orchestrating this immune response. This article elucidates these mechanisms, detailing the roles of cluster of differentiation (CD) markers, major histocompatibility complex (MHC) molecules, costimulatory signals, and the process of clonal selection.
Naive T cells that have not yet encountered an antigen express two primary CD...

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Streamlined Single Cell TCR Isolation and Generation of Retroviral Vectors for In Vitro and In Vivo Expression of Human TCRs

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STEGG: Structural TCR-pMHC ensemble generator and gallery.

Jared K Slone¹, Alexander W Bock¹, Mauricio Menegatti Rigo²

¹Computer Science, Rice University, Houston 77005, TX, USA.

Journal of Molecular Biology

|March 19, 2026

Summary

This summary is machine-generated.

We developed STEGG, a computational tool that models the dynamic, flexible interactions between T cell receptors (TCRs) and peptide-MHC complexes (pMHCs). This framework generates diverse structural ensembles, advancing personalized immunotherapies.

Keywords:

3D protein modeling TCR-pMHC conformational sampling molecular interactions

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Area of Science:

Immunology
Computational Biology
Structural Biology

Background:

T cell receptor (TCR) recognition of peptide-MHC complexes (pMHCs) is crucial for adaptive immunity, infectious disease, autoimmunity, and cancer immunotherapy.
Current 3D modeling struggles to represent the dynamic and flexible nature of TCR-pMHC interactions, which involve flexible CDR loops and peptides.
A single static structure fails to capture the range of energetically favorable binding modes in these interactions.

Purpose of the Study:

To introduce STEGG (Structural TCR-pMHC Ensemble Generator and Gallery), a computational framework for generating structural ensembles of TCR-pMHC complexes.
To capture the inherent flexibility and dynamic nature of TCR-pMHC interactions beyond static representations.
To provide a publicly available database of these structural ensembles for further research.

Main Methods:

STEGG utilizes a domain-specific sampling algorithm to efficiently generate 3D conformations from amino acid sequences.
It produces a range of distinct, low-energy 3D structures for each TCR-pMHC pair.
This approach avoids the computational expense and poor scalability of traditional molecular dynamics simulations.

Main Results:

STEGG successfully recovers conformations with low RMSD compared to experimentally determined structures.
The framework identifies a diverse set of biologically relevant binding modes and flexible poses.
It effectively captures the conformational diversity of TCRs, pMHCs, and their interactions.

Conclusions:

STEGG offers a novel computational method for studying the molecular basis of TCR-pMHC interactions by generating structural ensembles.
This approach moves beyond static modeling to represent the dynamic nature of these critical immune interactions.
The publicly available STEGG web server and database facilitate research in immunology and personalized medicine.