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Updated: Aug 4, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction
Published on: November 3, 2011
Prediction of Peptide and TCR CDR3 Loops in Formation of Class I MHC-Peptide-TCR Complexes Using Molecular Models
Nairuti Milan Mehta1, Yuhui Li1, Vini Patel1
1Department of Pharmacology and Pharmaceutical Sciences, Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, Los Angeles, CA, USA.
Abstract:
Formation of major histocompatibility (MHC)-peptide-T cell receptor (TCR) complexes is central to initiation of an adaptive immune response. These complexes form through initial stabilization of the MHC fold via binding of a short peptide, and subsequent interaction of the TCR to form a ternary complex, with contacts made predominantly through the complementarity-determining region (CDR) loops of the TCR. Stimulation of an immune response is central to cancer immunotherapy. This approach depends on identification of the appropriate combinations of MHC molecules, peptides, and TCRs to elicit an antitumor immune response. This prediction is a current challenge in computational biochemistry. In this chapter, we introduce a predictive method that involves generation of multiple peptides and TCR CDR 3 loop conformations, solvation of these conformers in the context of the MHC-peptide-TCR ternary complex, extraction of parameters from the generated complexes, and use of an AI model to evaluate the potential for the assembled ternary complex to support an immune response.
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