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Computational Reprogramming of T Cell Antigen Receptor Binding Properties.

Timothy P Riley1,2, Nishant K Singh1,2, Brian G Pierce3

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|April 21, 2016
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Computational design of T-cell receptors (TCRs) offers precise control over binding affinity and specificity. This method models mutations to optimize TCR-peptide/MHC interactions for therapeutic development.

Keywords:
BindingRosettaStructure-guided designT cell receptor

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Area of Science:

  • Immunology and Computational Biology
  • Protein Engineering and Design

Background:

  • T-cell receptor (TCR) binding to peptide/MHC complexes is crucial for cellular immunity.
  • Existing in vitro engineering methods for TCRs improve affinity but lack structural control and can reduce specificity.
  • Modulating TCR affinity and specificity is vital for developing novel therapeutics and imaging agents.

Purpose of the Study:

  • To develop a computational design approach for controlled manipulation of TCR binding properties.
  • To enable precise engineering of TCRs by leveraging structural information.
  • To improve TCR-based therapeutics and imaging reagents through rational design.

Main Methods:

  • Modeling point mutations in specific TCR regions to predict changes in binding energy.
  • Developing and optimizing scoring functions tailored to TCR-peptide/MHC interfaces.
  • Validating computational predictions against experimental data to refine the modeling methodology.

Main Results:

  • Demonstrated a strong correlation between predicted and experimentally measured changes in binding energy.
  • Achieved good agreement between computationally modeled and experimentally determined TCR structures.
  • Validated the potential for controlled manipulation of TCR binding properties through computational design.

Conclusions:

  • Computational design, starting with structural information, offers a more controlled alternative to molecular evolution for TCR engineering.
  • This approach has the potential to enhance TCR affinity and specificity with greater precision.
  • Refined modeling and scoring functions improve the design process for TCR-peptide/MHC interactions.