Automated protein-protein structure prediction of the T cell receptor-peptide major histocompatibility complex

The identification of TCR-pMHC pairs is a significant bottleneck in the implementation of TCR immunotherapies and may be augmented by computational methodologies that accelerate the rate of TCR discovery. The ability to computationally design TCRs to a target pMHC will require an automated integration of next-generation sequencing, homology modeling, molecular dynamics (MD), and TCR ranking.

We present a generic pipeline to evaluate patient-specific, sequence-based TCRs to a target pMHC. The most expressed TCRs from 16 colorectal cancer patients are homology modeled to target the CEA peptide using Modeller and ColabFold. Then, these TCR-pMHC structures are compared by performing an automated molecular dynamics equilibration.