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

The T Cell Receptor (TCR) recognition of a peptide-major histocompatibility complex (pMHC) is a crucial component of the adaptive immune response. 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. We find that Colabfold generates starting configurations that require, on average, an ~2.5X reduction in simulation ti...